JP6062979B2 - Image processing apparatus and method, inkjet printing system, and program - Google Patents

Description

  The present invention relates to an image processing apparatus and method, an ink jet printing system, and a program, and more particularly to an image processing technique for generating a halftone image for printing from a continuous tone image.

  In a printing system that forms an image using a printing device such as an inkjet printing device or an offset printing device, the image output method of the printing device is achieved by applying halftone processing to continuous tone image data expressed in multiple tones. Corresponding halftone image data is generated. The data of the halftone image is used as printing dot image data indicating a dot pattern in which the dot arrangement of halftone dots and the size of each dot are reproduced by a printing apparatus. The printing apparatus forms an image based on halftone image data.

  There are various methods of halftone processing, such as a dither method, an error diffusion method, and a direct binary search (DBS) method. For example, the dither method uses a threshold matrix called a dither mask, compares the pixel value of the pixel to be processed and the threshold value, assigns dot ON when the pixel value is equal to or greater than the threshold, and sets the pixel value to If it is less than the threshold value, dot off is assigned to convert multi-value continuous tone image data into binary dot data.

  Patent Document 1 proposes a printing system capable of selecting a halftone process suitable for a printed material in consideration of the productivity of the printed material. The printing system described in Patent Document 1 selects one signal processing condition from a plurality of signal processing conditions for halftone processing with different dot distribution characteristics, and executes halftone processing using the signal processing conditions related to the selection. be able to.

  Non-Patent Documents 1 to 3 disclose a technique called model-based halftoning. In Non-Patent Document 1, due to the characteristics of the printing system, the dispersibility of dots in a halftone is improved based on an image that reproduces the overlap of dots in consideration of dot spread and dot size during printing. A technique for performing halftone design is disclosed. The term “halftone design” means designing the specific content of halftone processing, ie generating halftone processing rules.

  In Non-Patent Document 2 and Non-Patent Document 3, in addition to considering overlapping of dots, a bidirectional error characteristic that is a positional deviation characteristic in which the position of the dot is displaced between the forward path and the backward path due to the reciprocal operation of serial scanning is provided. A method of performing halftone design based on a reproduced image is disclosed.

  Further, Patent Document 2 discloses a method for performing halftone design that is resistant to bidirectional errors and paper conveyance errors in the serial scan method. Further, Patent Document 3 discloses a method for designing a halftone that is resistant to positional deviation of a print head in a line printer that uses a line head configured by arranging a plurality of print heads.

  Patent Document 2 is multi-pass and Patent Document 3 is single-pass, both of which are designed to design halftones that improve dot dispersibility on a pass-by-pass basis. Can be classified.

JP 2012-222433 A JP 2013-038643 A JP 2009-018479 A

“Digital Halftoning Techniques for Printing” Thrasvoulos N. Papas IS & T ’s 47Th Annual Conference, Rochester, NY, May 15-20, 1994 “Model-Based Digital Halftoning” Thrasvoulos N. Papas, Jan P. Allebach, and David L. Neuhoff, IEEE SIGNAL PROCESSING MAGAZINE JULY 2003, p14-27 "Inkjet Printer Model-Based Halftoning" Je-Ho Lee and Jan P. Allebach, IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL.14. NO.5 MAY 2005, 647-689

  The printing result based on the halftone image generated by the halftone process depends on the characteristics of the printing system. Therefore, it is desirable to generate a halftone processing rule suitable for the printing system based on the characteristic parameters regarding the characteristics of the printing system.

  The model-based halftoning technique described in Non-Patent Documents 2 and 3 is a state in which there is a bidirectional error by reproducing the bidirectional error characteristic and generating an optimal halftone processing rule for the serial scan method. However, halftone processing that achieves good image quality is realized.

  In addition, the path dispersion halftoning techniques disclosed in Patent Documents 2 and 3 generate halftone processing rules that are resistant to print head misalignment errors, bidirectional errors, or paper transport errors. .

  The system error considered in Patent Documents 2 and 3 is a print head misalignment error, a bidirectional error, or a paper transport error. During actual printing, system errors other than these errors are also added. There is a case. Examples of system error items that are not taken into account in Patent Documents 2 and 3 include head vibration error due to carriage movement, error of each nozzle, ejection failure (non-ejection), or error for each droplet type. The term “print head” is a term corresponding to “recording head”.

  Further, in the case of an ink jet printing apparatus, when ink droplets are deposited adjacently on a recording medium, landing interference may occur between adjacent overlapping dots on the recording medium. Landing interference refers to a phenomenon in which ink droplets move on a recording medium when ink droplets adjacent on the recording medium attract each other due to the influence of the surface energy of the liquid. Due to the landing interference, dots are formed at a position shifted from the original landing position, so that the graininess of the image is deteriorated, the gloss is non-uniform, and the like, resulting in a decrease in image quality.

  The present invention has been made in view of such circumstances, and can suppress the deterioration in image quality due to landing interference and can realize generation of a halftone image capable of forming a high-quality image. It is an object to provide a processing apparatus and method, an inkjet printing system, and a program.

  In order to achieve the above object, the following aspects of the invention are provided.

  The image processing apparatus according to the first aspect is based on an analysis unit that analyzes a contact state with other dots for each dot of a plurality of pixels recorded by the inkjet printing system, and information indicating a contact state obtained by the analysis unit, Group classification means for performing group classification processing for classifying each dot into a plurality of groups, dispersion evaluation value calculation means for calculating a dispersion evaluation value for evaluating the dispersion of the dot group for each classified group, and dispersion The halftone processing rule half using the dispersibility evaluation value calculated by the dispersibility evaluation value calculating means or using the evaluation value generated based on the dispersibility evaluation value calculated by the dispersibility evaluation value calculating means. Signal processing means for performing at least one of a process for generating a tone parameter and a process for generating a halftone image. It is a device.

  The image processing apparatus according to the first aspect functions as an image processing apparatus that performs at least one of processing for generating a halftone processing rule that defines the content of halftone processing used in the inkjet printing system and halftone processing. The “dots recorded by the ink jet printing system” are dots in a dot image (that is, a halftone image) representing an arrangement form of dots assumed to be recorded by the ink jet printing system. The “dots recorded by the inkjet printing system” may be all the dots constituting the dot image, or may be a part of the dots.

  “Contact state” means a contact direction and / or a contact amount. The moving direction and moving amount of dot movement due to landing interference differ depending on the contact state between dots, and the moving direction and moving amount due to landing interference can be estimated from the contact state. Therefore, each dot can be classified from the viewpoint of the influence of landing interference based on the information indicating the contact state. Here, “influence by landing interference” includes a combination of a moving direction and a moving amount of dot movement due to landing interference.

  The dot groups having the same or similar contact state can be estimated to have the same or similar influence due to landing interference, and the dot groups having the same or similar contact state can be classified into the same group. Here, “similar” indicates that there is an approximation that falls within a range that can be handled as substantially the same range depending on the fineness of the classification. It can be classified into a plurality of groups according to different contact states. When the group classification is performed by paying attention to only a specific contact state, it is interpreted that the group is classified into at least two groups of a dot group corresponding to the specific contact state of interest and a non-corresponding group.

  “For each classified group” includes not only each of all classified groups but also means that at least one group that is a part of a plurality of classified groups is in group units. The dispersibility evaluation value calculation means calculates a dispersibility evaluation value for evaluating the dispersibility of the dot group in units of all or some of the classified groups. The case where the dispersibility evaluation value is calculated for only one (single) group among the plurality of classified groups is also included in the concept of “for each classified group”.

  The “dispersibility evaluation value” is an evaluation value for quantitatively indicating the dispersibility of the dot group numerically. The degree of influence of dot movement due to landing interference is quantitatively evaluated based on the dispersibility evaluation value for each group that has been classified into groups. The dispersibility evaluation value can be used as a landing interference evaluation value for evaluating the influence of landing interference.

  The “evaluation value generated based on the dispersibility evaluation value” is another evaluation value that is secondarily generated based on the dispersibility evaluation value. The “evaluation value generated based on the dispersibility evaluation value” is a value reflecting the dispersibility evaluation value.

  “Using a dispersibility evaluation value or using an evaluation value generated based on a dispersibility evaluation value” means “dispersion evaluation value” or “an evaluation value generated based on a dispersibility evaluation value” The value of “dispersion evaluation value” or “evaluation value generated based on dispersibility evaluation value” calculated from different dot images, or a process that compares the value with a specific numerical value (for example, a prescribed reference value) It is possible to use processing results such as processing that captures the increasing / decreasing tendency of “dispersibility evaluation value” or “evaluation value generated based on dispersibility evaluation value” by comparing themselves, or processing of a combination of these. Is included.

  The halftone processing rule can be specified by a combination of a halftone algorithm and a halftone parameter. Examples of the halftone processing rule include a dither mask in the dither method, information on an error diffusion matrix in the error diffusion method and its applicable gradation range, and the number of pixel updates and an exchange pixel range in the direct binary search method.

  According to the first aspect, for each group of dot groups having the same or similar influence of landing interference, the dispersibility of each dot group can be evaluated, and the halftone parameter that makes the dispersibility of each dot group good. And / or a halftone image can be obtained. According to the first aspect, it is possible to suppress deterioration in image quality due to landing interference and to generate a high-quality image.

  As a second aspect, in the image processing apparatus according to the first aspect, the signal processing means is based on a dispersion evaluation value or a result of a comparison process using an evaluation value generated based on the dispersion evaluation value. At least one of a halftone parameter and a halftone image having resistance to dot movement can be generated.

  “Tolerant of dot movement due to landing interference” means that there is robustness to maintain an appropriate image quality level with respect to the phenomenon of landing interference, in other words, image quality deterioration due to landing interference is acceptable. It means that there is robustness within the range.

  As a third aspect, in the image processing apparatus according to the second aspect, the comparison process is a process of comparing the dispersibility evaluation value with a specified reference value, or an evaluation value generated based on the dispersibility evaluation value and a specified reference The signal processing means includes a process for generating a halftone parameter having a dot arrangement that falls within an allowable range represented by a specified reference value based on a comparison result of the comparison process, and a specified reference It can be configured to generate at least one of the processes for generating a halftone image having a dot arrangement that falls within the allowable range represented by the value.

  The “standard reference value” can be set as appropriate from the viewpoint of the allowable range of the dispersibility evaluation value, the allowable range of the target image quality, and the like. Different reference values can be set for the reference value compared with the dispersibility evaluation value and the reference value compared with the evaluation value generated based on the dispersibility evaluation value.

  As a fourth aspect, in the image processing apparatus according to the second aspect, the signal processing unit compares the dispersibility evaluation value with a specified reference value, thereby achieving a dot equivalent to or higher than the dispersibility reference represented by the reference value. It can be set as the structure which produces | generates at least one among the halftone parameter and halftone image from which the dispersibility of a group becomes favorable.

  As a fifth aspect, in the image processing apparatus according to any one of the first to fourth aspects, the moving direction and the moving amount of the dot movement due to the landing interference are calculated based on the information indicating the contact state obtained by the analyzing unit. A movement amount calculation unit may be provided, and the group classification unit may perform a group classification process based on information indicating the movement direction and the movement amount obtained by the movement amount calculation unit.

  It is also possible to perform group classification processing directly from the information indicating the contact state, and as in the fifth aspect, the movement direction and amount of dot movement due to landing interference are obtained based on the information indicating the contact state. A configuration in which group classification processing is performed from information indicating the movement direction and movement amount may be employed.

  As a sixth aspect, in the image processing apparatus according to any one of the first to fifth aspects, at least one of a dot diameter, a dot shape, a dot formation position shift, and an undischarge that is an error factor in the inkjet printing system. An error reflection processing unit that generates an arrangement of dots reflecting two errors, and the group classification unit can perform a group classification process based on information indicating a contact state of dots reflecting the error. .

  “Dot formation position deviation” is a concept that comprehensively represents a deviation of positions where dots are actually formed with respect to an ideal position where dots should be formed. The “ideal position where a dot is to be formed” is a design target position, and indicates a dot formation position in a state where there is no error. There are various factors for the deviation of the dot formation position. Deviations in timing, deviations in the positions of forward and backward scanning in bidirectional scanning, bends in the ejection direction of forward scanning and backward scanning in bidirectional scanning, and ejection timing of each scanning pass in multiple scanning passes Examples include deviation, deviation of the position of each scanning pass, or bending of the ejection direction of each scanning pass. The dot formation position shift occurs due to a factor including at least one of the factors exemplified here. The “bending in the discharge direction” of the nozzle is referred to as “discharge bending”.

  As a seventh aspect, in the image processing apparatus of the sixth aspect, the group classification means can be configured to perform group classification processing only with a dot group that reflects an error.

  According to the seventh aspect, the amount of calculation can be reduced and the influence of landing interference can be easily evaluated.

  As an eighth aspect, in the image processing apparatus according to the sixth aspect or the seventh aspect, when the dot formation position deviation is reflected as an error, the group classification means determines that the moving direction of the dot movement due to landing interference is an error adding direction. It is possible to adopt a configuration in which group classification processing is performed only for dots that are in parallel directions.

  As a ninth aspect, in the image processing apparatus according to any one of the sixth aspect to the eighth aspect, when the dot formation position deviation is reflected as an error, the dispersibility evaluation value calculation unit moves the dot movement due to landing interference. The dispersibility evaluation value can be calculated only for the group to which the dot belongs in a direction whose direction is parallel to the direction in which the error is added.

  An ink jet printing system according to a tenth aspect includes an image processing apparatus according to any one of the first aspect to the ninth aspect, a halftone image generated through halftone processing defined by a halftone processing rule, or signal processing And an inkjet printing apparatus that performs printing on a print medium based on a halftone image generated by the means.

  The image processing method according to the eleventh aspect is based on an analysis step for analyzing a contact state with other dots for each dot of a plurality of pixels recorded by the inkjet printing system, and information indicating a contact state obtained by the analysis step. A group classification process for performing group classification processing for classifying each dot into a plurality of groups, a dispersion evaluation value calculation process for calculating a dispersion evaluation value for evaluating the dispersibility of the dot group for each classified group, and dispersion Half of the halftone processing rule using the dispersibility evaluation value calculated by the dispersibility evaluation value calculating step or using the evaluation value generated based on the dispersibility evaluation value calculated by the dispersibility evaluation value calculating step. A signal processing step for performing at least one of a process for generating a tone parameter and a process for generating a halftone image. It is a method.

  About the 11th aspect, the matter similar to the matter specified by the 2nd aspect to the 9th aspect can be combined suitably. In this case, the means responsible for the process and function specified in the image processing apparatus can be grasped as an element of the “process (step)” of the corresponding process and operation.

  The image processing method of the eleventh aspect in the case where the signal processing step performs the process of generating the halftone parameter of the halftone processing rule can be grasped as an invention of the method of generating the halftone processing rule. The halftone processing rule is information used for halftone processing, and can be understood as conforming to a program. Therefore, the image processing method of the eleventh aspect in the case of having a signal processing step for generating a halftone parameter can be interpreted as an invention of a method for producing a halftone processing rule.

  Further, the image processing method of the eleventh aspect in the case where the signal processing step performs halftone processing for generating a halftone image can be grasped as an invention of the halftone processing method, and a method for generating a halftone image It can be grasped as the invention. The “halftone image” may be in the form of image data as information provided for print control processing, or may be in the form of a printed image printed according to the image data. The image processing method according to the eleventh aspect in the case of having a signal processing step for generating a halftone image can be interpreted as an invention of a method for producing a halftone image.

  The program according to the twelfth aspect is based on analysis means for analyzing a contact state of each dot of a plurality of pixels recorded by the inkjet printing system with other dots, and information indicating the contact state obtained by the analysis means. A group classification unit that performs group classification processing to classify each dot into a plurality of groups; a dispersibility evaluation value calculation unit that calculates a dispersibility evaluation value for evaluating the dispersibility of the dot group for each classified group; Using the dispersibility evaluation value calculated by the dispersibility evaluation value calculating means, or using the evaluation value generated based on the dispersibility evaluation value calculated by the dispersibility evaluation value calculating means, the halftone processing rule Signal processing means for performing at least one of a process for generating a halftone parameter and a process for generating a halftone image; Is a program to function Te.

  Regarding the program of the twelfth aspect, matters similar to the matters specified in the second aspect to the ninth aspect can be appropriately combined. In this case, the means responsible for the process and function specified in the image processing apparatus can be grasped as an element of the program that realizes the corresponding process and operation means.

  According to the present invention, it is possible to generate a halftone processing rule that can suppress image quality deterioration due to landing interference, or to perform halftone processing. As a result, it is possible to obtain an image with good image quality that is resistant to landing interference.

FIG. 1 is a block diagram showing a configuration example of a printing system according to an embodiment of the present invention. FIG. 2 is a block diagram illustrating a hardware configuration example of the image processing apparatus. FIG. 3 is a block diagram for explaining functions of the image processing apparatus according to the first embodiment. FIG. 4 is a flowchart showing an example of a halftone processing rule generation method. FIG. 5 is a diagram showing an example of the characteristic parameter acquisition chart. FIG. 6 is a schematic plan view of the serial scan type inkjet printing apparatus used for drawing the characteristic parameter acquisition chart of FIG. FIG. 7 is an explanatory diagram of characteristic parameters related to landing interference. FIG. 8 is a diagram showing an example of landing interference parameters expressed as a function of the inter-dot distance. FIG. 9 is a chart showing the pros and cons of various halftone algorithms for a plurality of required items. FIG. 10 is a flowchart regarding a halftone parameter generation process. FIG. 11 is a conceptual diagram of a simulation image. FIG. 12A shows the order of droplet ejection in the drawing mode in which drawing is performed in eight scan passes, and FIG. 12B shows the drawing mode shown in FIG. It is a conceptual diagram in the case of adding a predetermined amount of error to the dots of the pixels in the first pass when drawing. FIG. 13 is an explanatory diagram in the case of giving an error that the dot diameter is reduced by a predetermined amount for the dots of the pixels belonging to the third pass when drawing is performed in the drawing mode shown in FIG. FIG. 14 is a flowchart of an example of creating a dither mask using the void-and-cluster method. FIG. 15 is a schematic diagram showing an example of a halftone selection chart. FIG. 16 is a flowchart showing a procedure for generating a halftone image of a halftone selection chart by the DBS method. FIG. 17 is a graph showing qualitative tendencies of various halftone processing rules. FIG. 18 is a graph showing the relationship between tolerance to system instability and granularity. FIG. 19 is a block diagram for explaining the functions of the image processing apparatus according to the second embodiment. FIG. 20 is a flowchart showing another example of a halftone processing rule generation method. FIG. 21 is a diagram showing another example of the characteristic parameter acquisition chart. FIG. 22 is a schematic plan view of the single-pass inkjet printing apparatus used for drawing the characteristic parameter acquisition chart of FIG. FIG. 23 is a schematic diagram illustrating an example of a chart for measuring a head vibration error associated with carriage movement. FIG. 24 is an explanatory diagram showing the shift amount of the recording position. FIG. 25 is a graph showing an example of head vibration error, FIG. 25A is a graph showing the positional deviation amount in the main scanning direction, and FIG. 25B is a graph showing the positional deviation amount in the sub-scanning direction. FIG. 26 is a schematic diagram illustrating an example of a chart for measuring a sheet conveyance error. FIG. 27 is a distribution diagram showing an example of the distribution of measured values of paper transport error. FIG. 28 is a schematic diagram showing an example of a chart for acquiring a head vibration error parameter in the single-pass method. FIG. 29 is a schematic diagram illustrating an example of a chart for obtaining a parameter of a head module mounting error. FIG. 30A is a schematic diagram for explaining the shift of the center of gravity position of the dot row, and FIG. 30B is an explanatory diagram of the inclination angle of the dot row. FIG. 31 is a graph showing the relationship between the system error distribution and the level of the random system error reflected in the generation of the simulation image. FIG. 32 is an explanatory diagram for explaining the relationship between a plurality of random system error levels and weighting factors. FIG. 33 is a diagram showing the two-dimensional error distribution in the main scanning direction and the sub-scanning direction in shades. FIG. 34 is a cross-sectional view of the error distribution along the main scanning direction in the two-dimensional error distribution shown in FIG. FIG. 35 is a cross-sectional view of the error distribution along the sub-scanning direction in the two-dimensional error distribution shown in FIG. FIG. 36 is a block diagram showing a main part of an image processing apparatus according to the third embodiment. FIG. 37 is a flowchart relating to processing for generating a halftone parameter as an example of means for suppressing image quality deterioration due to landing interference. FIG. 38 is a flowchart showing an example of further detailed processing contents of the steps S504 and S505 in FIG. FIG. 39 is an explanatory diagram for explaining a method of calculating a moving direction and a moving amount of dot movement due to landing interference. FIG. 40 shows an example of a dot arrangement that reflects an error due to a dot formation position shift of a specific nozzle in the recording head. FIG. 41 is a principal block diagram for explaining functions of the image processing apparatus according to the fourth embodiment. FIG. 42 is a flowchart when the void-and-cluster method is used in halftone design of the dither method as an example of a means for suppressing image quality deterioration due to landing interference. FIG. 43 is a flowchart showing an example of further detailed processing contents of the steps S523 and S524 of FIG. FIG. 44 is a flowchart in the case of performing halftone processing by the DBS method as an example of means for suppressing image quality deterioration due to landing interference. FIG. 45 is a flowchart showing an example of further detailed processing contents of the portions of steps S534 and S535 of FIG. FIG. 46 is a principal block diagram for explaining functions of the image processing apparatus according to the fifth embodiment. FIG. 47 is an explanatory diagram showing that the influence of landing interference can be estimated from the contact direction and the contact amount of dots.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

  FIG. 1 is a block diagram showing a configuration example of a printing system according to an embodiment of the present invention. The printing system 10 includes a DTP (Desk Top Publishing) device 12, a database server 14, a management computer 16, an image processing device 20, a print control device 22, a printing device 24, an image reading device 26, Is provided. The image processing device 20 is connected to the DTP device 12, the database server 14, the management computer 16, the print control device 22, and the image reading device 26 through an electric communication line 28.

  The telecommunication line 28 may be a local area network (LAN), a wide area network (WAN), or a combination thereof. The electric communication line 28 is not limited to a wired communication line, and a part or all of the electric communication line 28 can be a wireless communication line. Further, in this specification, the notation of “connection” between devices capable of passing signals includes not only wired connection but also wireless connection.

  The DTP device 12 is a device that generates document image data indicating the content of an image to be printed. The DTP device 12 is realized by a combination of computer hardware and software. The term software is synonymous with program. The DTP device 12 is used for editing various types of image parts such as characters, figures, patterns, illustrations, and photographic images to be printed and laying them out on a printing surface.

  Original image data as print source image data is generated by an editing operation by the DTP device 12 or the like. The DTP device 12 generates an electronic document in a page description language (PDL). The document image data generated by the DTP device 12 is transferred to the database server 14 and the image processing device 20. The means for generating the document image data is not limited to the form created by the DTP device 12, but can be created by another computer, an image creating / editing apparatus (not shown) or the like. The document image data can be input to the database server 14, the image processing device 20, the print control device 22, or the like through the electric communication line 28 or using a removable medium (external storage medium) such as a memory card.

  The database server 14 is a device that manages various data such as electronic original job tickets, color sample data, target profiles, and device profiles suitable for the combination of the printing device 24 and paper. Note that the job ticket can be in the form of a JDF (Job Definition Format) file, for example.

  The management computer 16 performs various types of management in the printing system 10. For example, image management, print job management, operation status management of one or a plurality of printing apparatuses 24 are performed.

  The image processing device 20 functions as a means for rasterizing original image data for printing (for example, data described in a page description language) generated by the DTP device 12 or the like. The rasterization process is called RIP (Raster Image Processor) process. The image processing device 20 can be realized as a function of the RIP device.

  The image processing device 20 includes a color conversion processing function and a halftone processing function for converting original document image data for printing, which is a continuous tone image, into dot pattern data for each color suitable for output by the printing device 24. Further, the image processing apparatus 20 of the present example has a function of generating two or more types of halftone processing rules based on the characteristic parameters of the printing apparatus 24 in the printing system 10 regarding the halftone processing function. That is, the image processing apparatus 20 includes a halftone processing generation function that generates a halftone processing rule, and a halftone processing function that performs halftone processing on a continuous tone image using the generated halftone processing rule. Yes. The image processing apparatus 20 can be realized by a combination of computer hardware and software.

  The halftone processing rule is a processing rule for performing halftone processing for converting continuous tone image data into halftone image data that is dot pattern data. The halftone processing rule is defined by a combination of a halftone algorithm and a halftone parameter. The halftone processing rule means a specific calculation mechanism of the halftone processing, and specifies the contents of the halftone processing.

  Examples of the halftone algorithm include a dither method, an error diffusion method, and a direct binary search method. The halftone parameter is a specific parameter used for arithmetic processing according to the halftone algorithm. The halftone parameter is determined for each halftone algorithm. For example, the size and threshold value of the dither matrix are determined as halftone parameters in the case of the dither method. As the halftone parameters in the error diffusion method, there are the setting of the matrix size of the error diffusion matrix, the error diffusion coefficient, and the applicable gradation section of each error diffusion matrix. As the halftone parameters in the direct binary search method, there are a pixel update count indicating the number of times of pixel replacement (exchange), and an exchange pixel range indicating a pixel range for pixel replacement. In addition, for each halftone algorithm, a parameter for evaluating tolerance to system errors can be added to the halftone parameter. When generating the halftone processing rule, at least one of the plurality of parameters exemplified above is specified as the halftone parameter.

  Specific contents of the processing functions in the image processing apparatus 20 will be described later. By supplying the halftone image data generated by the image processing device 20 to the print control device 22, the printing device 24 prints the target image.

  The print control device 22 controls the printing operation by the printing device 24 based on the print image data generated by the image processing device 20. The printing device 24 is an image forming unit that executes printing under the control of the printing control device 22. There are no particular limitations on the printing method and the type of color material used in the printing apparatus 24. As the printing device 24, for example, various printing devices such as an inkjet printing machine, an electrophotographic printer, a laser printer, an offset printing machine, and a flexographic printing machine can be adopted. The term “printing apparatus” is understood to be synonymous with terms such as a printing press, a printer, an image recording apparatus, an image forming apparatus, and an image output apparatus. As the color material, ink, toner, or the like can be used according to the type of the printing device 24.

  Here, an example will be described in which an inkjet printer, which is an example of a plateless digital printer, is used as the printing device 24. In the printing system 10 of the present embodiment, as an example of the printing device 24, a color image can be formed using four colors of ink of cyan (C), magenta (M), yellow (Y), and black (K). An ink jet printer is used. However, the number of ink colors and combinations thereof are not limited to this example. For example, in addition to CMYK four colors, a mode in which light color inks such as light cyan (LC) and light magenta (LM) are added, and a mode in which special color inks such as red and green are used are also possible.

  In FIG. 1, the printing control device 22 and the printing device 24 are shown as separate blocks, and a signal is exchanged between the two by wired or wireless communication connection. It is also possible to configure a printing device in which the control device 22 and the printing device 24 are combined together.

  When a plate-type printing machine using a printing plate is used as the printing device 24, a system including a plate making device (not shown) such as a plate recorder that makes a printing plate from image data in addition to the printing control device 22. It becomes composition. In this case, a plate making apparatus such as a plate recorder and its controller, and a printing machine that performs printing using a printing plate created by the plate making apparatus are connected to the electric communication line 28. In the case of a plate-type printing machine, a configuration in which the printing control device 22, a plate making device (not shown), and the printing device 24 are combined can be grasped as a “printing device” as a whole. The printing device 24 corresponds to a form of “image forming unit”.

  The image reading device 26 is a unit that reads an image of a printed matter (printed matter) printed by the printing device 24 and generates electronic image data indicating the read image. The image reading device 26 captures an image of a printed matter and converts the image information into an electrical signal, and a signal that processes a signal obtained from the image sensor and generates digital image data. And a processing circuit.

  As the image reading device 26, a scanner separate from the printing device 24 (for example, a so-called offline scanner that can be used offline, such as a flatbed scanner) can be used. Further, the image reading device 26 may be incorporated in the printing device 24. For example, a configuration may be adopted in which an image reading line sensor (imaging unit) is installed in the paper conveyance path of the printing apparatus 24 and a printed image is read by the line sensor while conveying a printed matter after image formation. The line sensor for image reading installed in the paper conveyance path in the printing apparatus 24 may be called by the term “inline scanner” or “inline sensor”. The image reading device 26 corresponds to a form of “image reading means”.

  The read image data of the print image generated by the image reading device 26 is input to the image processing device 20. The image processing device 20 has a function of analyzing the read image data obtained from the image reading device 26.

<System configuration variations>
The functions of the DTP device 12, the database server 14, the management computer 16, the image processing device 20, and the print control device 22 can be realized by a single computer, or can be realized by a plurality of computers. is there. Further, there may be various forms of sharing of roles and functions for each computer. For example, the DTP device 12 and the image processing device 20 may be integrated to realize these functions with a single computer, or the function of the image processing device 20 may be installed in the management computer 16. Also good. Further, a form in which the functions of the image processing apparatus 20 and the print control apparatus 22 are realized by a single computer is also possible. Furthermore, a configuration in which the functions of the image processing device 20 are shared by a plurality of computers is also possible.

  The number of the DTP device 12, the database server 14, the management computer 16, the image processing device 20, the print control device 22, the printing device 24, the image reading device 26, the plate making device, etc. included in this system is not particularly limited.

  In this example, the DTP device 12, the database server 14, the management computer 16, the image processing device 20, the print control device 22, and the like are illustrated as an example of a network system connected to the electric communication line 28. In implementing the invention, each element does not necessarily have to be connected to a communication network.

<Hardware Configuration of Image Processing Device 20>
FIG. 2 is a block diagram illustrating a hardware configuration example of the image processing apparatus 20. The image processing apparatus 20 of this example is realized using a personal computer (PC). That is, the image processing apparatus 20 includes a PC main body 30, a display device 32, and an input device 34. The notation “PC” represents a personal computer and includes various types of computers such as a desktop type, a notebook type, and a tablet type. The PC main body 30 includes a central processing unit (CPU) 41, a memory 42, a hard disk device (HDD: Hard Disk Drive) 43 as a storage device for storing and storing various programs and data, and an input interface. Unit 44, a communication interface unit 45 for network connection, a display control unit 46, and a peripheral device interface unit 47.

  The image reading device 26 described with reference to FIG. 1 can also be connected to the image processing device 20 via the peripheral device interface unit 47 of FIG.

  As the display device 32, for example, a liquid crystal display, an organic EL (Organic Electro-Luminescence) display, or the like can be used. The display device 32 is connected to the display control unit 46. The input device 34 may employ various means such as a keyboard, a mouse, a touch panel, and a trackball, and may be an appropriate combination thereof. In this example, a keyboard and a mouse are used as the input device 34. The input device 34 is connected to the input interface unit 44. The display device 32 and the input device 34 function as a user interface (UI). An operator (user) can input various information using the input device 34 while viewing the contents displayed on the screen of the display device 32, and can operate the image processing device 20, the printing device 24, and the like. . Further, it is possible to grasp (confirm) the state of the system through the display device 32.

  The hard disk device 43 stores various programs and data necessary for image processing. For example, chart data for a characteristic parameter acquisition chart, a calculation program for generating a characteristic parameter, an image processing program including generation processing for a halftone processing rule, a generation program for a halftone selection chart, and the like are stored. When the program stored in the hard disk device 43 is loaded into the memory 42 and executed by the CPU 41, it functions as various means defined by the program.

  The hardware configuration similar to that of the PC main body 30, the display device 32, and the input device 34 shown in FIG. 2 includes the hardware such as the DTP device 12, the database server 14, the management computer 16, and the print control device 22 described in FIG. It can be adopted as a hardware configuration.

<Description of Functions of Image Processing Device 20>
FIG. 3 is a block diagram for explaining functions of the image processing apparatus 20 according to the first embodiment. The image processing apparatus 20 includes a control unit 50, a characteristic parameter acquisition unit 52, a characteristic parameter storage unit 54, a priority parameter holding unit 56, a halftone processing generation unit 58, and a halftone processing rule storage unit 60. Prepare.

  The control unit 50 controls the operation of each unit in the image processing apparatus 20. The characteristic parameter acquisition unit 52 is a means for acquiring characteristic parameters relating to characteristics of the printing system 10 including the printing apparatus 24 described in FIG. In the case of an inkjet printing system, for example, the resolution, the number of nozzles, the ink type, the average dot density, the average dot diameter, the average dot shape, the dot density of each printing element, the dot diameter, the dot shape , Dot formation position misalignment, discharge failure, landing interference, and the like. Information regarding at least one of the parameters exemplified here, preferably a plurality of parameters, is acquired through the characteristic parameter acquisition unit 52.

  Among the various characteristic parameters exemplified above, the dot density, dot diameter, dot shape, and landing interference parameters of each printing element vary depending on the combination of ink used, print medium, and recording head characteristics, Since the dot formation position deviation and non-discharge also vary depending on the state of the recording head, it is a heavy workload for the user to input appropriate values for these various parameters. The characteristics of the recording head include the waveform and frequency of the drive signal applied to the recording head when ink is ejected. The recording head state includes, for example, the inclination and bending of the recording head, and the print medium. Indicates the distance and the state of each printing element.

  The printing element refers to a recording element responsible for dot recording in the printing device 24. In the case of an ink jet printing apparatus, an ink ejection nozzle in an ink jet head corresponds to a “printing element”. In the case of a printing apparatus using a relief plate, the relief of the convex portion of the halftone dot in the plate corresponds to a “printing element”.

  The characteristics of the printing system include at least one of individual recording characteristics of the plurality of printing elements and characteristics common to the plurality of printing elements. The individual recording characteristics of the printing element include at least one of dot density, dot diameter, dot shape, dot recording position error, and unrecordable abnormality. In the case of an ink jet printing apparatus, the dot recording position error corresponds to a dot formation position shift, and the recording impossible error corresponds to “no discharge”.

  “Common characteristics” for a plurality of printing elements include at least one of average dot density, average dot diameter, average dot shape, and landing interference.

  The characteristic parameter acquisition method according to the present embodiment outputs a characteristic parameter acquisition chart by the printing device 24, reads the characteristic parameter acquisition chart by an image reading device 26 (see FIG. 1) such as an inline scanner or an offline scanner, and the like. Each parameter is obtained by analyzing the read image.

  Resolution, number of nozzles, ink type, average dot density, average dot diameter, average dot shape, dot density of each printing element, dot diameter, dot shape, dot formation position deviation, undischarge, landing interference Among the items, the resolution, the number of nozzles, and the ink type are characteristic parameters related to system specifications.

  Therefore, it is preferable that the characteristic parameters relating to these system specifications are stored in the system in advance. Then, based on the resolution parameters, the number of nozzles, and the ink type, which are characteristic parameters related to these system specifications, characteristic parameter acquisition chart data for acquiring parameters related to the individual characteristics of the system is generated or stored in the system in advance Is selected from a plurality of characteristic parameter acquisition chart data, the characteristic parameter acquisition chart is output by the printing device 24 of the printing system 10, and the characteristic parameter acquisition chart is output from the image reading device 26 (see FIG. 1). Is preferable, and various characteristic parameters relating to characteristics unique to the printing apparatus 24 are acquired.

  Other characteristic parameters related to system specifications include drop type, unidirectional scanning or bidirectional scanning, scanning speed, print medium conveyance amount, ejection frequency, etc., and at least these characteristic parameters are included. A configuration is preferred in which data for a characteristic parameter acquisition chart is generated based on characteristic parameters relating to one system specification.

  The image processing apparatus 20 of this example includes a characteristic parameter acquisition chart generation unit 62 and an image analysis unit 64 as means for automatically acquiring characteristic parameters relating to the characteristics of the printing system 10.

  The characteristic parameter acquisition chart generation unit 62 is a processing unit that generates chart data of a characteristic parameter acquisition chart including a pattern for obtaining characteristic parameters related to the characteristics of the printing system. The chart data generated by the characteristic parameter acquisition chart generation unit 62 is sent to the print control device 22 (see FIG. 1) through the data output unit 66, and the characteristic parameter acquisition chart is printed by the printing device 24.

  A combination of the characteristic parameter acquisition chart generation unit 62 and a configuration in which the printing apparatus 24 (see FIG. 1) outputs the characteristic parameter acquisition chart based on the chart data generated by the characteristic parameter acquisition chart generation unit 62 is “ This corresponds to one form of “characteristic parameter acquisition chart output means”. Further, the characteristic parameter acquisition chart generation unit 62 corresponds to one form of “characteristic parameter acquisition chart generation means”.

  Although an example of the characteristic parameter acquisition chart will be described in detail later, the characteristic parameter acquisition chart may be, for example, a single dot pattern of each printing element by the head of each color of ink. A single dot pattern is a pattern in which each dot is isolated from each other without overlapping with other dots and ejected individually as a single dot. By reading such a single dot pattern chart, the dot density, dot diameter, dot shape, dot formation position deviation, and discharge failure parameters of each printing element can be read.

  The characteristic parameter acquisition chart can include a continuous dot pattern in which a plurality of dots overlap in addition to a single dot pattern. As a continuous dot pattern, a dot-to-dot distance between two dots can be changed to include a continuous dot pattern in which droplets are deposited so that some of the dots overlap each other. Such a continuous dot pattern is used for acquiring a parameter of dot deformation amount due to landing interference.

  When the printing system 10 has one type of droplet, one type of dot may be ejected independently to form a single dot pattern, and a plurality of droplets may be deposited to form a continuous dot pattern. When there are a plurality of droplet types, each type of dot is ejected individually to form a single dot pattern, and a combination of each type of dot is ejected to form a continuous dot pattern.

  When outputting the characteristic parameter acquisition chart, a single dot of the same printing element is printed a plurality of times, and the dot density, the dot diameter, the dot shape, the average value of the dot formation position deviation, the dot density of the printing element, The dot diameter, dot shape, and dot formation position deviation may be used. Further, the dot density, dot diameter, and dot shape of each printing element may be averaged to obtain the average dot density, average dot diameter, and average dot shape.

When the resistance design for system errors, the variance sigma ² showing a variation from the average value of the obtained measurement values by reading the characteristic parameter acquisition chart calculated, the standard deviation sigma is the square root of the variance sigma ² May be a predetermined amount of error to be used later.

  The print result of the characteristic parameter acquisition chart printed by the printing device 24 is read by the image reading device 26, and the read image data of the characteristic parameter acquisition chart is obtained.

  The image analysis unit 64 functions as a characteristic parameter generation processing unit that analyzes the read image read by the image reading device 26 and generates characteristic parameter information. The image analysis unit 64 automatically obtains characteristic parameter information from the characteristic parameter acquisition chart. The image analysis unit 64 corresponds to one form of image analysis means.

  That is, the characteristic parameter acquisition unit 52 in the image processing apparatus 20 is configured to automatically acquire the characteristic parameter from the measurement result obtained by analyzing the read image of the characteristic parameter acquisition chart. The combination of the image analysis unit 64 and the characteristic parameter acquisition unit 52 corresponds to one form of the characteristic parameter acquisition unit.

  Information on the characteristic parameters acquired through the characteristic parameter acquisition unit 52 is stored in the characteristic parameter storage unit 54. In the characteristic parameter storage unit 54, characteristic parameters related to system specifications can be stored in advance.

  The halftone processing generation unit 58 defines halftone processing rules that define the processing contents of two or more types of halftone processing with different priority balances for a plurality of request items required for halftone processing based on the characteristic parameters. Is generated. The image processing apparatus 20 includes an image quality evaluation processing unit 74 including a simulation image generation unit 68 and an evaluation value calculation unit 70, and the halftone processing generation unit 58 cooperates with the image quality evaluation processing unit 74 in two or more types. Generate halftoning rules for The halftone process generation unit 58 corresponds to one form of a halftone process generation unit. The evaluation value calculation unit 70 corresponds to one form of evaluation value calculation means. The image quality evaluation processing unit 74 corresponds to one form of image quality evaluation means.

  The image quality evaluation processing unit 74 performs optimization search processing for improving the evaluation value while repeating the generation of the simulation image and the calculation of the evaluation value of the image quality for the simulation image. The halftone parameter is determined by the processing by the image quality evaluation processing unit 74.

  A plurality of types of halftone processing rules generated by the halftone processing generation unit 58 are registered in the halftone processing rule storage unit 60. In FIG. 3, for convenience of illustration, two different halftone processing rules 1 and 2 are generated, and the halftone processing rules 1 and 2 are stored and stored in the halftone processing rule storage unit 60. When K is an integer of 2 or more, a plurality of types of halftone processing rules of K or more can be generated. Then, all or part of the generated K types of halftone processing rules 1, 2,... K can be registered in the halftone processing rule storage unit 60 as a lineup. The halftone processing rule storage unit 60 corresponds to a form of halftone registration means. In the halftone processing rule storage unit 60, a plurality of types of halftone processing rules as candidates for halftone processing that can be used in the printing system 10 can be registered. A halftone processing rule used for actual printing is determined from the plurality of halftone processing rules generated by the halftone processing generation unit 58 in this way.

  The image processing apparatus 20 of this example includes a halftone selection chart generation unit 76 as selection support means for selecting any one halftone processing rule from a plurality of halftone processing rules.

  The halftone selection chart generation unit 76 generates chart data of a halftone selection chart in which print results of halftone images obtained by each of two or more types of halftone processing rules are arranged in a comparable manner. The chart data generated by the halftone selection chart generation unit 76 is sent to the print control device 22 (see FIG. 1) through the data output unit 66, and the halftone selection chart is printed by the printing device 24.

  The combination of the halftone selection chart generator 76 and the printing device 24 corresponds to one form of a halftone selection chart output unit.

  The user can select a desired halftone processing rule by looking at the output result of the halftone selection chart. The selection operation of the halftone processing rule by the user is performed using the input device 34. The input device 34 functions as “halftone selection operation means” for the user to perform an operation of selecting a desired halftone processing rule. That is, the input device 34 is a halftone that accepts a user operation for the user to select one of the halftone processing types from among two or more types of halftone processing used to generate the halftone selection chart. It functions as a selection operation means.

  In addition to such a function for selecting halftone processing rules by the user, the system may have a function for automatically selecting one halftone processing rule. In this case, it is necessary to hold in advance a priority parameter related to the priority of a plurality of request items for halftone processing. The priority parameter holding unit 56 stores a priority parameter designating a balance of priorities regarding a plurality of request items. The priority parameter holding unit 56 corresponds to a form of priority parameter holding means.

  The priority parameter can be freely input by the user through the input device 34, and the priority balance can be set and the setting contents can be changed. Alternatively, as the priority parameter, one type or a plurality of types of selection candidates may be prepared in advance on the system. When a plurality of types of selection candidates related to the setting of the priority parameter are prepared, the user can select one of the selection candidates through the input device 34 in consideration of the printing purpose, application, productivity, and the like.

  By specifying the balance of priority with respect to the request item by the priority parameter, one optimal halftone processing rule recommended on the system according to the priority parameter specified by the priority parameter holding unit 56 Can be determined uniquely. Such an automatic selection function can be realized by the control unit 50, and the configuration of the control unit 50 responsible for the automatic selection processing corresponds to one form of a halftone automatic selection unit.

  The input device 34 functions as a priority input unit for the user to input settings related to the priority for each request item. Depending on the priority set by the user, halftone processing rules based on the priority setting (ie, a combination of halftone algorithm and halftone parameters), and the priority balance and symmetric priority according to the user setting There may be a mode in which halftone processing rules that are balanced in degree are generated and compared.

  Further, there may be a mode in which a plurality of halftone processing rules are generated based on a priority balance set by a plurality of priority balances by slightly allocating the priority balance based on the priority set by the user.

  The image processing apparatus 20 has a function of performing halftone processing on continuous tone image data in accordance with the generated halftone processing rules. That is, the image processing apparatus 20 includes an image input unit 77, a color conversion processing unit 78, and a halftone processing unit 80.

  The image input unit 77 is an input interface unit that captures document image data, and functions as an image data acquisition unit. The image input unit 77 can be configured by a data input terminal that takes in document image data from an external or other signal processing unit in the apparatus. As the image input unit 77, a wired or wireless communication interface unit may be employed, a media interface unit for reading and writing an external storage medium (removable disk) such as a memory card, or the like. An appropriate combination of these may be used.

  The color conversion processing unit 78 performs color conversion processing of document image data using a color profile that conforms to the ICC profile format by the International Color Consortium (ICC), and is suitable for output by the printing device 24. A color image signal is generated. When the CMYK four-color ink is used in the printing device 24, the color conversion processing unit 78 generates a CMYK image signal. Further, in the case of using six colors of ink including light magenta (LM) and light cyan (LC) in addition to CMYK, the color conversion processing unit 78 generates an image signal including CMYK, LM, and LC color components. .

  The halftone processing unit 80 performs halftone processing on the continuous tone image of each color using the halftone processing rule generated by the halftone processing generation unit 58, and generates a halftone image. The data of the halftone image generated by the halftone processing unit 80 is sent to the print control device 22 (see FIG. 1) through the data output unit 66, and printing is performed by the printing device 24.

  A method of obtaining a printed material by printing on a printing medium by the printing device 24 based on a halftone image generated through the processing by the halftone processing unit 80 can be grasped as a printed material manufacturing method.

  The image quality evaluation processing unit 74 of the image processing apparatus 20 can calculate the evaluation value of the printing halftone image in cooperation with the halftone processing unit 80. Information of evaluation values related to the halftone image generated by the halftone processing unit 80 can be displayed on the screen of the display device 32, and can be provided to the outside through the data output unit 66.

<Procedure for determining halftone processing rules in the printing system>
A method for determining the halftone processing rules in the printing system 10 of the present embodiment will be described in detail. FIG. 4 is a flowchart showing an example of a halftone processing rule generation method according to this embodiment.

  First, in order to obtain characteristic parameters relating to the characteristics of the printing system 10, a characteristic parameter acquisition chart is generated, and the characteristic parameter acquisition chart is output by the printing device 24 (see FIG. 1) (step S10 in FIG. 4). Step S10 corresponds to a form of the characteristic parameter acquisition chart output step.

  Next, the characteristic parameter acquisition chart output in step S10 is read (step S11). In step S11, the print of the characteristic parameter acquisition chart is read by the image reading device 26 (see FIG. 1), and a read image of the characteristic parameter acquisition chart is obtained. Step S11 in FIG. 4 corresponds to one form of the image reading process.

  Next, the read image acquired in step S11 is analyzed to acquire characteristic parameters relating to the characteristics of the printing system (step S12). Step S12 is a process corresponding to one form of the characteristic parameter acquisition process.

  Next, two or more types of halftone processing rules having different priority levels of request items for halftone processing are generated (step S14). When generating the halftone processing rules, a plurality of types of halftone processing rules are generated based on the priority parameter and the characteristic parameter. Step S14 is one form of a halftone process generation process.

  Then, a halftone selection chart is output using each generated halftone processing rule (step S16). Step S16 corresponds to one form of a halftone selection chart output step.

  The user can select one of the halftone processing rules by looking at the output result of the halftone selection chart. Based on the user's selection operation, a halftone processing rule used for printing is determined (step S18). That is, step S18 accepts a user operation for the user to select one of the halftone processing types from the two or more types of halftone processing used to generate the halftone selection chart, and the user selects A halftoning rule is determined based on the operation. Step S18 corresponds to one form of a halftone selection operation process.

<Example of characteristic parameter acquisition chart>
A specific example of the characteristic parameter acquisition chart used in the characteristic parameter acquisition process described in step S12 of FIG. 4 will be described.

  FIG. 5 is a diagram illustrating an example of the characteristic parameter acquisition chart 100. Here, a single dot pattern 102C, 102M, 102Y, and 102K, and a first continuous dot pattern 104C, are formed on the print medium 101 by nozzles that are printing elements in the recording heads of cyan, magenta, yellow, and black. 104M, 104Y, and 104K and the second continuous dot patterns 106C, 106M, 106Y, and 106K are ejected. The single dot patterns 102C, 102M, 102Y, and 102K are discrete dot patterns that are discretely recorded in an isolated state in which a single dot is separated from other dots. The first continuous dot patterns 104C, 104M, 104Y, and 104K, and the second continuous dot patterns 106C, 106M, 106Y, and 106K are patterns of continuous dots that are recorded by bringing two or more dots into contact with each other.

  The single dot patterns 102C, 102M, 102Y, 102K, the first continuous dot patterns 104C, 104M, 104Y, 104K, and the second continuous dot patterns 106C, 106M, 106Y, 106K are all patterns for obtaining characteristic parameters. It corresponds to one form. The single dot patterns 102C, 102M, 102Y, and 102K correspond to one form of discrete dot patterns. The first continuous dot patterns 104C, 104M, 104Y, and 104K and the second continuous dot patterns 106C, 106M, 106Y, and 106K correspond to one form of a continuous dot pattern.

  FIG. 6 is a schematic plan view of the serial scan type inkjet printing apparatus used for drawing the characteristic parameter acquisition chart of FIG. In FIG. 6, for convenience of illustration, only four nozzles for each color are shown by reducing the number of nozzles of the recording head for each color. Various designs are possible for the number of nozzles, nozzle arrangement, and nozzle density.

  As shown in FIG. 6, the head unit 110 in the serial scan type ink jet printing apparatus includes a cyan recording head 112C that discharges cyan ink, a magenta recording head 112M that discharges magenta ink, and a yellow recording that discharges yellow ink. A head 112Y and a black recording head 112K that discharges black ink are mounted on a carriage 114 and configured to be reciprocable along the X direction in FIG. The Y direction orthogonal to the X direction is the conveyance direction of the print medium 101. The X direction corresponds to the “main scanning direction”, and the Y direction corresponds to the “sub scanning direction”.

  Although the detailed structure of each of the cyan recording head 112C, the magenta recording head 112M, the yellow recording head 112Y, and the black recording head 112K is not shown, each ink jet recording head ejects ink corresponding to each nozzle. An ejection energy generating element (for example, a piezoelectric element or a heating element) that generates necessary ejection energy is provided. Each recording head (112C, 112M, 112Y, 112K) ejects ink droplets on demand in accordance with a drive signal and an ejection control signal given from the print control device 22 (see FIG. 1).

  A single dot pattern indicated by reference numeral 102C in FIG. 5 can be formed by performing droplet ejection from each nozzle 118C of the cyan recording head 112C at an appropriate timing while moving the carriage 114 in FIG. 6 in the X direction. . After drawing the single dot pattern 102C with cyan ink, the print medium 101 is conveyed in the Y direction, the recording area on the print medium 101 is changed, and then the carriage 114 is moved in the X direction, and cyan recording is performed at an appropriate timing. By performing droplet ejection from each nozzle 118C of the head 112C, a first continuous dot pattern indicated by reference numeral 104C in FIG. 5 can be formed. In addition, after drawing the first continuous dot pattern 104C using cyan ink, the print medium 101 is conveyed in the Y direction, the recording area on the print medium 101 is changed, and then the carriage 114 is moved in the X direction while performing cyan recording. By performing droplet ejection from each nozzle 118C of the head 112C at an appropriate timing, a second continuous dot pattern indicated by reference numeral 106C in FIG. 5 can be formed.

  In the first continuous dot pattern 104C and the second continuous dot pattern 106C, the setting of the inter-dot distance between overlapping dots is different. By recording a plurality of types of continuous dot patterns by changing the inter-dot distance, it is possible to grasp a characteristic parameter related to the relationship between the inter-dot distance d and the amount of change due to the influence of landing interference.

  5 illustrates two types of continuous dot patterns (104C, 106C) with different inter-dot distances, but three or more types of continuous dot patterns may be formed by changing the inter-dot distances. .

  Subsequent to the recording of the dot pattern (102C, 104C, 106C) with cyan ink, droplet ejection by each nozzle 118M of the magenta recording head 112M, droplet ejection by each nozzle 118Y of the yellow recording head 112Y, and black recording head 112K in the same manner. The characteristic parameter acquisition chart 100 shown in FIG. 5 is generated by sequentially performing droplet ejection by each of the nozzles 118K.

From the single dot patterns 102C, 102M, 102Y, and 102K for each color, information on the dot density, dot diameter, dot shape, dot formation position deviation, and discharge failure for each color printing element can be obtained. Further, by statistically processing the measurement results of a large number of single dots, the average dot density, average dot diameter, average dot shape, and standard deviation σ (square root of variance σ ² ) can be obtained. The standard deviation σ or variance σ ² calculated for at least one of the dot density, dot diameter, dot shape, and dot formation position deviation of each printing element corresponds to one form of dispersion information regarding dot variation.

  Also, characteristic parameter information relating to landing interference can be obtained from the first continuous dot patterns 104C, 104M, 104Y, and 104K for each color and the second continuous dot patterns 106C, 106M, 106Y, and 106K. The characteristic parameter related to landing interference refers to information related to a change in inter-dot distance, a change in dot density, a change in dot shape, and the like due to the influence of landing interference that is an interaction between overlapping dots.

<Characteristic parameters related to landing interference>
7 and 8 are explanatory diagrams of characteristic parameters relating to landing interference. The left column of FIG. 7 shows how the setting values of the inter-dot distances of two dots when two droplets are partially overlapped and continuously ejected are varied in three stages, d1, d2, and d3. The right column in FIG. 7 shows how the inter-dot distance changes due to the impact of landing interference when droplet ejection is performed with the inter-dot distances d1, d2, and d3 set. In addition, the distance between dots here means the distance between the centers of dots.

  As shown in the figure, the actual inter-dot distances are u1, u2, u3 (u1> u2> u3) with respect to the interdot distances d1, d2, d3 (d1> d2> d3) as set values. Since dots are attracted by landing interference, d1> u1, d2> u2, and d3> u3.

  By changing the setting of the inter-dot distance and acquiring the data of the change in the inter-dot distance due to the influence of the landing interference, the landing interference data as shown in FIG. 8 can be obtained. The horizontal axis in FIG. 8 is the setting value of the inter-dot distance, and “R” indicates the radius of the dot. The vertical axis in FIG. 8 indicates the amount of change in the inter-dot distance due to the impact of landing interference, and indicates the absolute value of | di-ui | in FIG. 7 (i = 1, 2, 3). “2R” on the horizontal axis in FIG. 8 indicates a position where two dots circumscribe. If the inter-dot distance is greater than 2R, the dots do not overlap and are not affected by landing interference. When the setting of the inter-dot distance is smaller than 2R, the dots overlap each other and the dots are attracted by landing interference, and the inter-dot distance changes.

  Although described as “amount of change in inter-dot distance” in FIG. 8, the influence of landing interference can also be measured as a change in dot density or a change in dot shape.

  A function of the inter-dot distance d from the read results of the first continuous dot patterns 104C, 104M, 104Y, 104K and the second continuous dot patterns 106C, 106M, 106Y, 106K in the characteristic parameter acquisition chart 100 described in FIG. Can be obtained as parameterized landing interference data.

  Such parameters relating to landing interference are obtained and averaged for each printing element (here, for each nozzle). A value averaged for each color may be held for each color, or a value obtained by averaging all colors may be held as a common parameter.

  FIG. 5 illustrates a single dot pattern and a continuous dot pattern assuming that there is one type of droplet for each color of CMYK. However, when there are a plurality of droplet types, each type of dot is ejected independently and is simply applied. A one-dot pattern is formed, and a plurality of overlapping combinations of each type of dot are ejected to form a continuous dot pattern. And the parameter regarding landing interference will be acquired about the combination of each drop type. Alternatively, a continuous dot pattern may be formed by overlapping a plurality of CMYK dot combinations to form a continuous dot pattern, and parameters relating to landing interference may be acquired for each color dot combination.

  As a chart for acquiring parameters related to landing interference, a chart in which not only the distance between dots of a plurality of dots is changed but also the recording time difference between the dots is changed may be output. For example, as a time difference for recording a plurality of dots, a time difference of a plurality of levels is set such as one pass, two passes, three passes, etc., and the dots are brought into contact with each other with the time differences of the plurality of levels. A chart may be output. The recording time difference corresponds to the droplet ejection time difference.

  For example, two dots that are overlapped in the first continuous dot pattern and the second continuous dot pattern for each color of CMYK in FIG. 5 are set as dot 1 and dot 2, respectively, and dot 1 and dot 2 are set on the carriage 114. A continuous dot pattern is formed in which droplets are continuously ejected by one movement in the X direction, and after the dots 1 are ejected by the first movement in the X direction of the carriage 114, the print medium 101 is not conveyed in the Y direction. A continuous dot pattern in which the dot 2 is ejected by the second movement of the carriage 114 in the X direction, and after the dot 1 is ejected by the first movement of the carriage 114 in the X direction, the print medium 101 is not conveyed in the Y direction. A continuous dot pattern in which dots 2 are ejected by the third movement of the carriage 114 in the X direction, and so on. Continuous dot pattern contacting the sheet 1 and dot 2 may be formed.

<Requirements for halftone processing>
The required items required for the halftone process are as follows, for example. That is, the first classification (a) of the request items includes image quality, system cost, halftone generation time, and halftone processing time. As the second classification (b) of the requirement items, there are further “granularity” and “resistance to system error” regarding the image quality. These multiple requirement items are in a trade-off relationship. Further, among the tolerances for system errors, there is “tolerance against environmental fluctuations”. With regard to resistance to environmental fluctuations, for example, since the density of ink and the amount of spread of dots vary due to the influence of temperature and humidity, it is conceivable to design the halftone processing rule by simulating the influence.

  In the present embodiment, two or more types of halftone processing rules with different priority balances for a plurality of request items required for halftone processing are generated. At least two items are included in the image quality, system cost, halftone generation time, halftone processing time, system error tolerance, and environmental fluctuation tolerance exemplified above.

<Halftone algorithm and benefits for each requirement>
The pros and cons of various halftone algorithms for the required items of image quality, system cost, halftone generation time, and halftone processing time in the first classification (a) are as shown in the chart of FIG. Here, three types of halftone algorithms were compared: a dither method, an error diffusion method, and a direct binary search (DBS) method.

  The system cost includes costs related to CPU (Central Processing Unit) performance, memory capacity, and other system specifications necessary for realizing the halftone processing function. The halftone generation time is a time required to generate a halftone processing rule, and includes, for example, a time required to calculate a halftone parameter. The halftone processing time is a time required for processing for converting from continuous tone image data to halftone image data using the generated halftone processing rule.

  Comparing the three types of halftone algorithms of the dither method, error diffusion method, and DBS method, with respect to image quality, the dither method has a relatively low image quality, the DBS method has a relatively high image quality, and the error diffusion method The image quality is intermediate between the two. Regarding the system cost, the dither method has a relatively low cost, and the DBS method has a relatively high cost. The system cost of the error diffusion method is an intermediate level between the dither method and the DBS method. With respect to halftone generation time and halftone processing time, the dither method is relatively short, and the DBS method is relatively time consuming. The error diffusion method is an intermediate level between the dither method and the DBS method.

  Further, not only the relative profit and loss depending on the type of the halftone algorithm shown in FIG. 9, but also the profit and loss for each request item changes depending on the setting of the halftone parameter in the same halftone algorithm. For example, when the halftone algorithm is the dither method, the larger the dither mask size, the higher the image quality, but on the other hand, the system cost increases, and the halftone generation time and halftone processing time become longer.

  When the halftone algorithm is the error diffusion method, the larger the error diffusion matrix size and the more the gradation sections to which the error diffusion matrix is applied, the higher the image quality. Increases the system cost and increases the halftone generation time and halftone processing time.

  When the halftone algorithm is the DBS method, the larger the number of pixel updates, and the wider the replacement pixel range, the higher the image quality, but the system cost increases for other requirements, and Halftone generation time and halftone processing time are long.

  With regard to the second category (b) of required items, errors may occur in characteristic parameters such as dot density, dot diameter, dot shape, dot formation position deviation, and discharge failure, depending on the printing order, drawing pass, and droplet ejection timing. On the other hand, the tolerance design against the system error can be performed so as to suppress the reduction in graininess and the generation of streaks. However, the graininess in the state without error is lowered by this tolerance design. In other words, the granularity and the tolerance to system errors are in a trade-off relationship.

  The printing order that can cause a system error is, for example, the order in which ink colors are superimposed. Further, the print order can include the order of the forward pass and the return pass in the serial scan type head scan. The pass is the pass order in the drawing mode in which drawing is completed by multipass using a serial scan type inkjet head. In the case of a single pass printer, one line in the main scanning direction corresponds to “pass”. The timing is assumed, for example, in the case where droplets are ejected while feeding the print medium, and an error occurs in the landing position or dot shape due to the droplet ejection timing due to the influence of the conveyance error of the print medium. Is.

  As other system errors, characteristic parameters such as dot density, dot diameter, dot shape, dot formation position deviation, and discharge failure change due to changes in the state of the printing element over time. . In addition, it is difficult to accurately reproduce and simulate the change in dot density, shape, and position due to the impact of landing interference only from the characteristic parameter acquisition chart as shown in FIG. 5, and this deviation from the reality is also a system error. It is considered.

  In other words, the difference between the simulation image and the reality caused by changes in the state of the system over time, restrictions on the chart for obtaining characteristic parameters and the image reading device 26, limitations of the simulation model, etc. is regarded as a system error, and there is no deviation. A design is made to optimize the graininess and to provide resistance so as to suppress the deterioration of graininess and the occurrence of streaks in the actual image even if there is a deviation between them.

  In the case of the dither method, for example, in the case of a printing system in which each printing element is independently present in a wide range in the width direction of the printing medium, such as a single pass printer, the dot density, dot diameter, dot shape of each printing element, It is difficult to design a halftone that optimizes graininess by directly reflecting characteristics such as misalignment of dot formation position or discharge failure.

  Therefore, in this case as well, the granularity is optimized based on the average dot density, dot diameter, and dot shape information for each ink type, and the dot density, dot diameter, and dot shape are determined by the individual characteristics of multiple printing elements. In other words, the design is made to be resistant to errors such as misalignment of dot formation position or discharge failure.

<Description by specific example>
In the image processing apparatus 20 of this example, two or more types of halftone processing rules are set according to the priority of each request item based on the pros and cons for each request item described above. The halftone processing rule is specified by a combination of a halftone algorithm and a halftone parameter.

  [Setting Example 1] As an example of setting priority, for example, when priority is given to image quality for the first classification (a) and granularity is important for the second classification (b). As a halftone processing rule corresponding to (Setting Example 1), the following halftone processing rule can be defined.

-Halftone algorithm: DBS method-Halftone parameter: Pixel update count = large and replacement pixel range = large-System error tolerance design: None Note that specific numerical values for specifying the pixel update count related to the halftone parameter As specific numerical values for specifying the exchange pixel range, appropriate numerical values belonging to relatively large values are set from among a plurality of numerical value candidates that can be selected on the system.

  With regard to the DBS method, the halftone processing rule is determined only by designating the pixel update count and the replacement pixel range as the halftone parameters.

    [Setting Example 2] As another setting example of priority, for example, when the first classification (a) is focused on halftone processing time, and the second classification (b) is focused on system error tolerance. As a halftone processing rule corresponding to this priority setting (setting example 2), the following halftone processing rule can be determined.

-Halftone algorithm: Dither method-Halftone parameter: Dither mask size = small-System error tolerance design: Adds error of ± 10 micrometers [μm] and considers "streaks" tolerance Granularity evaluation parameter α = 1 and the line evaluation parameter β = 1.

  As specific numerical values for specifying the dither mask size related to the halftone parameter, appropriate numerical values belonging to relatively small values are set from among a plurality of numerical value candidates that can be selected on the system. In the above setting example 2, the degree of system error may not be known for the second classification (b), and how much the system error affects the actual image graininess and streak quality is still unclear. Since it is not known, a plurality may be set according to the priority of system error tolerance. For example, a plurality of error amounts such as “± 10 micrometers [μm]”, “± 20 micrometers [μm]”, etc. may be set. Regarding the simulation of landing interference, “setting not to be performed”, “setting to be performed”, “setting to simulate only dot movement due to landing interference when performing”, “simulation not only dot movement but also changes in dot density and shape A plurality of settings such as “setting” may be set. Regarding the setting of dot movement due to landing interference and changes in density and shape, a plurality of parameters may be set by changing the parameters acquired from the characteristic parameter acquisition chart.

  Further, when a simulation considering landing interference is performed, dot movement and / or dot deformation due to landing interference may be given not only as a function of the distance between dots but also as a function of time.

  Not only the setting examples 1 and 2 described above but also halftone processing rules corresponding to various priority settings can be generated.

  When the dither method or the error diffusion method is selected as the halftone algorithm, a process for generating a halftone parameter corresponding to each halftone algorithm is further performed according to the flowchart shown in FIG.

  FIG. 10 is a flowchart regarding a halftone parameter generation process. The flowchart of FIG. 10 is a flowchart common to both the dither method and the error diffusion method. Here, the dither method will be described as an example.

  First, halftone parameters are provisionally set (step S22). In the case of the dither method, determining the matrix size of the dither mask (that is, the dither mask size) and each threshold value corresponds to determining the halftone parameter. There are various dither mask sizes such as 32 × 32, 64 × 64, 128 × 128, and 256 × 256. The halftone parameter when the dither mask size is designated indicates the threshold value of the dither mask, and the flowchart of FIG. 10 is repeated from the threshold value 0 to the maximum value.

After temporarily setting the halftone parameters in step S22, next, halftone processing is performed using the temporarily set halftone parameters (step S24). In the case of the dither method, this step S24 corresponds to obtaining dot ON pixels from the threshold value “0” to the current threshold value. That corresponds to obtaining the input image of a single tone having a tone of the current threshold, the halftone image after the halftone processing using the dither mask (dot arrangement).

  Next, a simulation image of the print image is generated for the halftone image obtained in step S24 by using the characteristic parameter relating to the characteristics of the printing system (step S26). In step S26, for the dot pattern data indicated by the halftone image, characteristic parameters relating to the dot density, dot diameter, dot shape, dot formation position deviation, discharge failure, or an appropriate combination thereof of each printing element are set. By arranging the reflected dots so as to overlap the pixels of the halftone image, a simulation image of the print image is generated.

  FIG. 11 is a conceptual diagram of a simulation image. In FIG. 11, each grid-like cell represents a pixel of image data. In the halftone image data, the “dot ON” pixel cell is displayed in a screen tone pattern, and the “dot OFF” pixel is outlined.

  When generating a simulation image, dots that reflect recording characteristics such as dot density, dot diameter, dot shape, dot formation position deviation, discharge failure, or an appropriate combination thereof of each printing element responsible for recording dot-on pixels Are arranged at the position of the dot ON pixel.

  At this time, based on the arrangement state including the surrounding dots or the arrangement state after overlapping the dots, the dot shape after the landing interference may be calculated from the already acquired deformation parameter of the dot shape due to the landing interference and rearranged. . For example, dot movement represented by a function of f (ya) in the Y direction due to the influence of landing interference due to the inter-dot distance ya in the “sub-scanning direction” (Y direction in FIG. 11), which is parallel to the print medium conveyance direction. And is expressed as a function of f (xb) in the X direction due to the impact of landing interference due to the inter-dot distance xb in the “main scanning direction” (X direction in FIG. 11) which is a direction perpendicular to the print medium conveyance direction. Assuming that the dot movement occurs, the dot rearrangement is performed assuming that the dot shape changes due to the dot movement of f (ya) + f (xb) due to the influence of such landing interference.

Surrounding dots that interfere with landing are present not only in the “sub-scanning direction” and “main scanning direction” but also in the oblique direction, and are affected by this, so not only the “sub-scanning direction” and “main scanning direction” but also any direction as dot movement is generated due to the influence of landing interference by the distance between dots c _n of the surrounding dots n is expressed by a function of f (c _n) in the direction of the dots, f (ya) + f ( xb) + f The dots may be moved by (c ₁ ) + f (c ₂ ) +... + F (c _n ) and rearranged. Of course, since the influence of landing interference differs depending on the drop type, the function f (*) differs depending on the surrounding dot type. “*” Represents a variable. Dots may be rearranged on the assumption that not only dot movement but also changes in dot density and dot shape occur due to landing interference.

The inter-dot distance c _n and the function f (*) representing dot movement can be handled as vectors. That is, the functions f (ya) + f (xb) and f (ya) + f (xb) + f (c ₁ ) + f (c ₂ ) +... + F (c) representing the movement of the dots described with reference to FIG. _{Also for n} ), the parameters ya, xb, c ₁ to c _n are treated as vectors having directions. The functions f (ya) + f (xb) and f (ya) + f (xb) + f (c ₁ ) + f (c ₂ ) +... + F (c _n ) are also handled as vectors having directions. .

  Here, dot movement due to landing interference, changes in density and shape may be given by functions including not only the inter-dot distance but also the droplet ejection time difference between the dots. That is, the function f (*) may be a function based on the inter-dot distance and the droplet ejection time difference between the dots.

  In FIG. 11, the simulation image needs to have a higher resolution than the halftone image data in order to reflect the recording characteristics such as dot diameter, dot shape, dot formation position deviation, and landing interference. For example, when the resolution of halftone image data is 1200 dot per inch [dpi] in both the main scanning direction and the sub-scanning direction, the size of each cell is about 21 micrometers [μm] × 21 micrometers [μm]. If the dot formation position deviation is about 3 micrometers [μm], the simulation image needs to have a resolution of 8400 dot per inch [dpi], which is at least 7 times. However, it is possible to reduce the memory capacity required for the simulation image by temporarily arranging the dots on the high-resolution simulation image and then converting them to a low-resolution simulation image. That is, a high-resolution simulation image is required only in the vicinity where dots are arranged, and the entire simulation image only needs to be held at a low resolution, so that memory capacity can be reduced.

  When generating a simulation image in step S26 of FIG. 10, in the case of a printing system in which each printing element is independently present over a wide range in the width direction of the printing medium, such as a single-pass printer, the printing device 24 is individually printed for each printing element. Instead of using the dot density, dot diameter, and dot shape information, the average values of the dot density, dot diameter, and dot shape of each printing element may be used for each ink type.

  Next, image quality evaluation is performed on the simulation image generated in step S26 (step S28 in FIG. 10).

  The image quality evaluation is performed by applying a low-pass filter such as a Gaussian filter or a visual transfer function (VTF: Visual Transfer Function) representing human visual sensitivity to the simulation image, then converting the frequency and integrating the value, RMS granularity (Root This is done by calculating at least one evaluation value such as Mean Square granularity), an error from the input image, or a standard deviation. The value calculated in the image quality evaluation step in step S28 is stored in the memory as “image quality evaluation value”.

  Here, when designing for system error tolerance, the dot ON pixel corresponding to the current threshold value of the halftone processing result and the dot of the pixel belonging to the same condition at least one of the printing order, pass, and timing, A simulation image is generated (step S26) and an image quality evaluation value is calculated (step S26) by adding at least one error among a predetermined dot density, dot diameter, dot shape, dot formation position deviation, and discharge failure (step S26). S28) is performed.

  Furthermore, in the case of designing the tolerance so that not only the deterioration of the graininess but also the generation of streaks is suppressed as the tolerance to the system error, the above error is added to the simulation image as a streak evaluation value, and a low-pass filter or A value obtained by applying VTF, integrating in the main scanning direction, performing one-dimensional frequency conversion and integrating, an error from the integrated value in the main scanning direction of the input image, a standard deviation, and the like are calculated. In addition, as a method for calculating the quantitative evaluation value of graininess and stripes, a known method described in JP-A-2006-67423, JP-A-2007-172512, or the like can be used.

  In this example, the image quality evaluation value is calculated by the following equation, and the obtained value is held.

Image quality evaluation value = granularity evaluation value [no system error] + α × {granularity evaluation value [with system error (+ predetermined amount)] + granularity evaluation value [with system error (−predetermined amount)} + β × {strip evaluation Value [with system error (+ predetermined amount)] + streaked evaluation value [with system error (-predetermined amount)]} Expression (1)
The granularity evaluation value [no system error] in the calculation formula of the image quality evaluation value is a granularity evaluation value calculated from a simulation image that does not add a system error corresponding to a fluctuation component of the characteristic parameter. The granularity evaluation value [with system error (+ predetermined amount)] is a granularity evaluation value calculated from a simulation image to which a positive (positive) predetermined amount is added as a system error. The granularity evaluation value [with system error (−predetermined amount)] is a granularity evaluation value calculated from a simulation image to which a negative (negative) predetermined amount is added as a system error. The streak evaluation value [with system error (+ predetermined amount)] is a streak evaluation value calculated from a simulation image to which a positive (positive) predetermined amount is added as a system error. The streak evaluation value [with system error (−predetermined amount)] is a streak evaluation value calculated from a simulation image to which a negative (negative) predetermined amount is added as a system error. The coefficients α and β are evaluation parameters, the coefficient α is a graininess evaluation parameter, and the coefficient β is a streak evaluation parameter. When trying to increase tolerance to system errors, α and β are set to larger values. In particular, when not only the graininess but also “streak” is not conspicuous, the value of β is increased. Predetermined amount of additional error, type of additional error (density, dot diameter, dot shape, misalignment of dot formation, discharge failure, landing interference), and coefficient as evaluation parameter according to the priority of system error tolerance already explained α and β are defined.

  As the predetermined amount of additional error, the standard deviation σ of each item such as dot density, dot diameter, dot shape, and dot formation position deviation obtained by reading the characteristic parameter acquisition chart can be used. As the predetermined amount of additional error, at least one of the standard deviation of the dot density, the standard deviation of the dot diameter, the standard deviation of the dot shape, and the standard deviation of the dot formation position deviation can be used, and an appropriate combination thereof can be used. You can also.

  The image quality evaluation value is calculated in step S28 of FIG. 10, and when the image quality evaluation value is improved, the halftone parameter is updated (step S30). In step S32, it is determined whether or not the processing from step S22 to step S30 has been repeatedly performed a predetermined number of times. The “predetermined number of times” in step S32 in the case of the dither method is the total number of pixels as threshold candidates.

  If it is determined in step S32 that the predetermined number of repetitions has not been completed, the process returns to step S22, and the processes from step S22 to step S30 are repeated. If it is determined in step S32 that the predetermined number of repetitions has been completed, the process ends.

<In case of error diffusion method>
An example in which the flowchart of FIG. 10 is applied to generation of a halftone parameter of the error diffusion method will be described. In the case of the error diffusion method, the halftone parameter indicates the setting of the size of the error diffusion matrix, the diffusion coefficient, and the applicable gradation section of each error diffusion matrix. Here, in order to simplify the description, the size of the error diffusion matrix is assumed to be one type of common size.

  By repeating the flowchart of FIG. 10 for all applicable gradation intervals, the diffusion coefficient of the error diffusion matrix for each applicable gradation interval is determined.

  The applicable gradation interval of the error diffusion matrix can be divided into five stages of 0-50, 51-100, 101-150, 151-200, and 201-256, for example, in the case of 8-bit gradation. There are various ways of dividing the applicable gradation section, and it may be equally divided into m stages as an integer m of 2 or more, or may be divided into arbitrary uneven gradation areas.

  For a certain gradation interval, a diffusion coefficient of an error diffusion matrix to be applied to the corresponding gradation interval is temporarily set (step S22), and an input image (single gradation uniform image) of each gradation in the gradation interval is set. A halftone process is performed (step S24 in FIG. 10), a simulation image is generated (step S26), an image quality evaluation value is calculated (step S28), and an average value of each evaluation value for each gradation is determined as an image quality evaluation value. To do.

  When the halftone parameter is temporarily set in step S22, the initial value of the diffusion coefficient of the error diffusion matrix is set to 1 / matrix size. In the temporary setting (step S22) of the second and subsequent error diffusion matrix coefficients when performing a predetermined number of repetitions, “± predetermined range of random numbers” is added to each coefficient of the best error diffusion matrix so far. The provisional setting is performed by normalizing the sum of the coefficients to “1”.

  The initial value of the diffusion coefficient related to the error diffusion matrix in the adjacent gradation section is preferably the diffusion coefficient of the error diffusion matrix in the adjacent gradation section that has already been optimized.

  The generation of the simulation image in step S26 is performed in the same manner as in the dither method. The image quality evaluation (step S28) is performed in the same manner as in the dither method. However, when designing tolerance for system errors, add errors to the dots of pixels belonging to each printing order, pass, and timing, generate simulation images, and calculate graininess and streak evaluation values. The sum is defined as an “evaluation value”. For example, the granularity evaluation value with a system error is expressed by the following equation.

Graininess evaluation value [with system error]
= [Evaluation value of graininess [with system error (addition of “+ predetermined amount” error to group 1)]
+ Graininess evaluation value [with system error (addition of “+ predetermined amount” error to the second group)] +…
+ Graininess evaluation value [with system error (addition of "-predetermined amount" error to group 1)]
+ Graininess evaluation value [with system error (addition of “−predetermined amount” error to the second group)] + ...] Equation (2)
Here, the grouping such as the first group, the second group,... Indicates a pixel group belonging to the same condition with respect to at least one of the printing order, the pass, and the timing. For example, in the case of the drawing mode for completing the drawing of the round-trip 8-pass, the pixel group recorded in the first pass is grouped sequentially into the first group, and the pixel group recorded in the second pass is grouped sequentially into the second group, The pixel group recorded in the eighth pass can be the eighth group.

For the pixels in each group that are grouped, the "predetermined amount" of additional to error may be the same value among groups, the value may be different for each group. Further, “+ predetermined amount” and “−predetermined amount” may have the same absolute value or may have different absolute values.

  FIG. 12A shows the order of droplet ejection in the drawing mode in which drawing with a predetermined recording resolution is performed in eight scanning passes, by pass numbers. FIG. 12B is a conceptual diagram in the case where a predetermined amount of error is added to the dots of the pixels in the first pass when drawing is performed in the drawing mode shown in FIG. In FIG. 12B, an error in dot formation position deviation is given in the X direction to the dots of each pixel group ejected in the first pass. An error can be similarly applied to the pixel groups having other pass numbers.

  FIG. 13 is given an error that the dot diameter is reduced by a predetermined amount for the dots of the pixels of the third pass when drawing is performed in the drawing mode shown in FIG. The dot diameter shown by the broken line in FIG. 13 indicates an average dot diameter without error.

<Other examples of dithering>
In the case of the dither method, not only the flowchart described in FIG. 10 but also a known void-and-cluster method (Void-and-Cluster method) may be used. FIG. 14 is a flowchart thereof.

  First, an initial halftone image is prepared (step S42). The generation method of the halftone initial image follows the well-known Void-and-Cluster method. In other words, in an energy image obtained by convolving a filter with a simulation image of a specific gradation, pixels with the maximum energy value are regarded as cluster pixels with dense dots, pixels with the minimum energy are regarded as void pixels with sparse dots, and cluster pixels By repeating the exchange of void pixels, an initial image is generated. The specific gradation is, for example, a gradation value of about 50% of the maximum density, and an initial image having a gradation value “128” in the image data represented by 0 to 256 gradations is generated.

  Next, a simulation image is generated from the halftone image using the characteristic parameters relating to the printing system (step S44). The generation of the simulation image is the same as the example described in FIG. A filter is convoluted with respect to the simulation image generated in step S44, and a threshold value is set for the minimum energy pixel (that is, a void pixel) among pixels in which dots are not set in the halftone image, and the void pixel in the halftone image is set. A dot is set (step S46). As a filter used when the filter is convoluted, for example, a Gaussian filter is used.

  In step S48, it is determined whether or not threshold setting (that is, dot setting) has been completed for all gradations. If it has not been completed, the process returns to step S44, and steps S44 and S46 are repeated. That is, in step S46, a simulation image is generated for the halftone image in which dots are newly added (step S44), an energy image obtained by convolving the filter with the simulation image is generated, and a threshold value is set to the minimum energy pixel. Is set (step S46).

  When the processing for all the gradations is completed in step S48, the processing in FIG.

  The flowchart shown in FIG. 14 is processing in a direction in which the threshold value is increased from the initial image, but the method of lowering the threshold value (that is, the gradation value) from the initial image also follows the known void and cluster method. In other words, in the energy image obtained by convolving the filter with the simulation image, the pixel having the maximum energy among the pixels for which the dot is set is regarded as a cluster pixel having a dense dot, the threshold is set, and the dot of the pixel is set. In addition, the process of generating a simulation image, convolving a filter, setting a threshold value, and removing dots is sequentially repeated. For example, a Gaussian filter is used as a filter used when the filter is convoluted.

  When carrying out tolerance design against system errors, as in the example described with reference to FIG. 10, pixels corresponding to the current threshold value and dots of pixels that belong to the same condition of at least one of the printing order, pass, and timing are: A simulation image is generated by adding at least one type of error among a predetermined amount of dot density error, dot diameter error, dot shape error, dot formation position error, and undischarge error (step S44), The filter is folded (step S46).

  Furthermore, when implementing streak tolerance design, as the streak energy, the above-mentioned predetermined amount of error is added to the simulation image, and the filter is convoluted and integrated in the main scanning direction (one-dimensional energy ( That is, streak energy) is calculated. Then, as the energy of the entire print image, a pixel having a minimum image evaluation value including a streak energy component shown below is searched.

Image evaluation value = energy [no system error] + α × {energy [with system error (+ predetermined amount)] + energy [with system error (−predetermined amount)]} + β × {strip energy [with system error (+ predetermined amount) )] + Streak energy [with system error (−predetermined amount)]} Equation (3)
The halftone parameters in the dither method and the error diffusion method are determined by the method described with reference to FIGS. 10 and 14, and a halftone processing rule specified by a combination of the halftone algorithm and the halftone parameters is generated. In this way, a plurality of types of halftone processing rules are generated.

<About halftone selection chart>
The printing system 10 according to the present embodiment provides a judgment material for selecting one type of halftone processing rule used for printing from among a plurality of types of halftone processing rules generated by the image processing apparatus 20. Then, a halftone selection chart is output (step S16 in FIG. 4).

  The halftone selection chart is a floor in which primary colors such as cyan, magenta, yellow, and black, secondary colors such as red, green, and blue, tertiary colors, and quaternary colors are arranged in predetermined gradation steps. It can be a chart that includes patches for toning. In addition, the halftone selection chart changes a gradation image in which gradation values are continuously changed by changing to a patch in which gradation values are discretely changed at predetermined gradation steps for each color, or in combination with this. It can be set as the structure containing.

  Furthermore, the halftone selection chart can include a patch having a predetermined gradation and a gradation image in a special color such as sky blue or pale orange. Various types of “special colors” can be set. Sky blue and pale orange are examples of colors where graininess is particularly problematic in printed materials. In this way, a color that is particularly important in printed materials can be set as a “special color” and included in the image of the halftone selection chart.

  The halftone selection chart can be used as a judgment material when the user selects an appropriate halftone process by comparing the quality of each halftone process based on the result of the halftone process shown in the chart. Is.

  In order to be able to compare the quality of a plurality of types of halftone processing, it is preferable to generate a halftone selection chart in which processing results of a plurality of types of halftone processing are juxtaposed on a single print medium.

  FIG. 15 is a schematic diagram showing an example of a halftone selection chart. FIG. 15 shows an example of a halftone selection chart 150 in which the processing results of two types of halftone processing rules are arranged and printed on one print medium 101.

  The chart area shown on the left side of FIG. 15 is a chart showing the processing result of the first halftone processing rule (indicated as “halftone 1”), and the chart area shown on the right side is the second halftone processing rule ( It is a chart showing the processing result of “Halftone 2”.

  In the halftone selection chart 150 of this example, regarding the halftone processing of each of the two types of halftone processing rules, a gradation range of gradation values 0 to 256 is provided for each primary color of C, M, Y, and K. A total of 32 primary color patches 151 and 152 divided into 16 stages in increments of “16” are arranged.

  In FIG. 15, for convenience of illustration, a part of the gradation step is omitted and the number of patches is reduced, but gradation values 16, 32, 48, 64, 80, 96, 112 are shown for each color of CMYK. , 128, 144, 160, 176, 192, 208, 224, 240, 256, primary color patches 151, 152 corresponding to the gradation values are recorded. Reference numeral 151 denotes a primary color patch based on the processing result of the first halftone processing rule, and reference numeral 152 denotes a primary color patch based on the processing result of the second halftone processing rule.

  In addition, in the halftone selection chart 150, in addition to the arrangement of primary color patches 151 and 152 for each color of CMYK, gradation images 161 and 162 for each color, sky blue patches 171 and 172 with a predetermined tone of sky blue, and a pale. Pale orange patches 181 and 182 with predetermined orange gradations are included. Reference numeral 161 represents a gradation image resulting from the processing result of the first halftone processing rule, and reference numeral 162 represents a gradation image resulting from the processing result of the second halftone processing rule. The gradation images 161 and 162 are grayscale image areas in which gradation values are continuously changed in a gradation range from the minimum gradation value to the maximum gradation value for the primary colors of CMYK.

  Reference numeral 171 indicates a sky blue patch based on the processing result of the first halftone processing rule, and reference numeral 172 indicates a sky blue patch based on the processing result of the second halftone processing rule. Reference numeral 181 indicates a pale orange patch based on the processing result of the first halftone processing rule, and reference numeral 182 indicates a pale orange patch based on the processing result of the second halftone processing rule.

  Further, the halftone selection chart 150 is printed with information on the system cost, ink cost, and processing time for each halftone processing rule.

  Although not shown in FIG. 15, for some or all of the primary color patches 151 and 152, information indicating the evaluation value of graininess and / or the evaluation value of streaks has an association with the patch. It may be printed. As a method of printing information having an association with a patch, there are, for example, a mode of printing information on a patch, a mode of printing information near a patch, and the like.

  Similarly, for the sky blue patches 171 and 172 and the pale orange patches 181 and 182, the granularity evaluation value information and / or for some or all of these patches (171, 172, 181, 182) Information on the evaluation value of the streaks may be printed in association with the patch.

  The user can select a preferable halftone processing rule by comparing the chart of the processing result based on the first halftone processing rule with the chart of the processing result based on the second halftone processing rule.

  The primary color patches 151 and 152, the gradation images 161 and 162, the sky color patches 171 and 172, and the pale orange patches 181 and 182 in the halftone selection chart 150 shown in FIG. This is an image area for evaluation and corresponds to one form of the image area for comparative evaluation.

  Not only the form of the halftone selection chart 150 illustrated in FIG. 15 but also various chart forms are possible. A gradation image of another color such as a secondary color, a tertiary color, or a quaternary color may be formed instead of or in combination with the primary color gradation images 161 and 162 illustrated in FIG. Various forms are possible for the color type and layout of the patch or gradation image as the image area for comparative evaluation.

  In addition, when outputting the halftone selection chart, the same chart is arranged on the entire drawing range of the print medium in order to evaluate the tolerance against system errors in halftone processing (suppression of graininess reduction and streak generation). Alternatively, a plurality of contents of the same chart may be output. The configuration in which the same charts are arranged on the entire drawing range of the print medium is useful when evaluating tolerance to a system error depending on a printing position (printing location) within the drawing range. Also, the configuration in which a plurality of contents of the same chart are output is useful when evaluating tolerance against system errors over time. “The content of the same chart” is a form of an image of the same halftone processing result. A configuration in which the same chart is arranged and output on the entire drawing range of the print medium corresponds to one form of a configuration in which a plurality of images of the same halftone processing result are output to different positions on the print medium. A configuration in which a plurality of contents of the same chart are output corresponds to one form of a configuration in which the same halftone processed image is output a plurality of times at different printing timings.

  In a configuration in which multiple copies of the same chart are output in time, when the same chart is output continuously, halftone processing can be switched and continuous chart output can be performed for multiple types of halftone processing. it can. In this case, it is preferable to fix the print location (print position on the print medium) of the processing result of the same halftone process. When outputting a plurality of charts of the processing results of the same halftone processing, the influence of the system error depending on the location can be excluded by printing the chart at the same location on each print medium.

  In the case of a configuration in which a plurality of the same charts are spatially output, adjacent halftone processing results on one print medium can be processing results of different types of halftone processing. Further, in the case of a configuration in which a plurality of the same charts are spatially shifted, the same halftone processing result can be stored in the same single print medium. As a result, the influence of system errors over time can be excluded.

  Further, as described in FIG. 15, as information useful for the judgment and selection by the user, not only the image showing the processing result of the halftone processing, but also the quantitative evaluation value of the granularity and stripes, the system cost, At least one piece of information such as ink cost, halftone generation time, and halftone processing time may be printed on the printed matter of the halftone selection chart. The “system cost” is indicated as, for example, an additional optional cost for enhancement of functions required to realize a system specification required to meet a required halftone processing time. With regard to “ink cost”, since there is a slight difference in the amount of ink used depending on the type of halftone, the ink cost is calculated from the amount of ink used for each halftone type when the same image content is printed. Information is presented. At least one of the system cost and the ink cost corresponds to “cost”.

  At least one piece of information on the halftone processing results, such as graininess and streak quantitative evaluation values, system cost, ink cost, halftone generation time, and halftone processing time, is printed when the halftone selection chart is output. Instead of, or in combination with, the configuration presented by the user interface, it can be configured to be displayed on the screen of the user interface. Such a configuration for printing evaluation value information relating to quantitative evaluation together with a halftone selection chart and a configuration for displaying it on a screen of a user interface correspond to one form of “information presenting means”. That is, the display device 32 (see FIGS. 2 and 3) of the image processing device 20 can function as an information presentation unit.

  Graininess and streak quantitative evaluation values may be calculated by generating a simulation image by the method described above from the halftone processing result of the halftone selection chart and calculating the graininess evaluation value and the streak evaluation value. The output result of the tone selection chart may be read by an image reading device 26 such as an inline scanner, and the graininess evaluation value and the streak evaluation value may be calculated from the read image.

  It should be noted that in order to generate a simulation image related to the halftone selection chart, in order to evaluate the tolerance to system errors, the dots of the pixel group to which at least one of the printing order, pass and timing belongs to the same condition are applied. Adding a predetermined amount of error to generate a simulation image.

  When calculating quantitative evaluation values of graininess and stripes from a simulation image, the calculated values can be printed on a printed matter of a halftone selection chart.

  On the other hand, when the output result of the halftone selection chart is read and the quantitative evaluation value of graininess and stripes is calculated from the read image, the calculation result can be displayed on the screen of the user interface. The user can select an appropriate halftone process by referring to the quantitative evaluation value displayed on the screen of the user interface and confirming the printed matter of the halftone selection chart.

  As another method, when the output result of the halftone selection chart is read and the quantitative evaluation value of graininess or streaks is calculated from the read image, the halftone selection chart that has been read is used. The calculation result may be additionally printed, or when the same halftone selection chart is output after the read halftone selection chart is output, It is good also as a structure which prints the quantitative evaluation value of a stripe.

  When presenting information on quantitative evaluation values of graininess and streaks, especially on the screen for differences in evaluation values that need to be alerted to users, and for patch portions where the evaluation values fluctuate. Also preferred is an embodiment in which highlighting is performed on a printed matter.

  For example, when a plurality of halftone selection charts are output at different printing timings in time and changes due to changes over time are checked, the quantitative evaluation value calculated from the read image of the halftone selection chart is changed. There is a mode in which highlighting is performed to alert the user to a large thing exceeding the allowable range. In this case, the history of the quantitative evaluation value is stored in the memory, and when the amount of change in the quantitative evaluation value exceeds the allowable range, differentiated display or other highlighted display is performed.

  In addition to checking the system error over time, that is, the instability of the system with respect to time, using a halftone selection chart, the system error depending on the printing position (place) on the print medium, that is, the system against space (place) Instability can also be confirmed using a halftone selection chart. Also in this case, there is a mode in which highlighting is performed to alert the user to the fact that the difference in the quantitative evaluation value due to the difference in location exceeds the allowable range.

  In addition, after one halftone processing rule is selected by the automatic selection of the system or by the user's selection operation, the priority balance of the first classification (a) and the second classification (b) of the request item is Generate multiple other halftone processing rules that are close to the selected halftone processing rule and calculate image quality evaluation values and overall evaluation values based on priority parameters, or output a halftone selection chart, In addition, the system or the user may be able to select a more optimal halftoning rule. When the system automatically selects halftone processing, generation of the halftone processing rule may be repeated until the image quality evaluation value and the overall evaluation value are equal to or greater than a predetermined threshold.

<Regarding generation method of halftone selection chart by DBS method>
FIG. 16 is a flowchart showing a procedure for generating a halftone image of a halftone selection chart by the DBS method. In the case of the DBS method, a halftone image of a halftone selection chart is acquired according to the flowchart of FIG.

  First, an initial halftone image is prepared (step S52). The initial halftone image is generated by subjecting the halftone selection chart to a dither mask generated in a simple manner or a dither process according to the halftone processing rule of the dither method generated in step S14 of FIG. The

  Next, a process for replacing dots in the halftone image is performed (step S54 in FIG. 16). Then, for each of the dots before and after the replacement, a simulation image is generated using the characteristic parameters regarding the characteristics of the printing system (step S56). Image quality evaluation is performed on the generated simulation image (step S58), and when the evaluation value is improved before and after replacement, the halftone image is updated (step S60). The image quality evaluation value calculated at the time of image quality evaluation in step S58 is obtained by applying an error (difference) to the input image after applying a low-pass filter such as a Gaussian filter or a visual transfer function (VTF) representing human visual sensitivity to the simulation image. Obtained by calculation.

  In accordance with the “pixel update count” set in advance, the dots are replaced a predetermined number of times, and the processing from step S54 to step S60 is repeated.

  In step S62, it is determined whether or not the predetermined number of dot replacement processes have been completed. If the predetermined number of processes has not been completed, the process returns to step S54, and the processes from step S54 to step S60 are repeated. If it is determined in step S62 that the predetermined number of processes has been completed, this process ends.

<Means for compensating image quality degradation due to impact of landing interference>
Up to now, in each halftone parameter generation of the dither method and error diffusion method represented by the flowcharts of FIGS. 10 and 14, or in the halftone processing of the DBS (Direct Binary Search) method represented by the flowchart of FIG. In order to obtain a satisfactory halftone processing result in consideration of the impact of landing interference, the description has been made on the assumption that a simulation image including landing interference is generated. However, since simulation of landing interference requires a lot of time and simulation accuracy is also an issue, it is desirable that image quality degradation due to the influence of landing interference can be compensated by a simple method without performing simulation. From this point of view, it is also a desirable form to have a configuration that includes means for compensating for image quality degradation due to landing interference at the time of dot contact.

  For example, in order to compensate for the deterioration of graininess due to the influence of landing interference, the movement direction and the movement amount are estimated based on the type of the surrounding dots, the contact direction and the contact amount for each pixel dot, and the movement direction and / or the movement amount is calculated. Based on this, each dot may be classified into small groups having the same movement direction and / or the same movement amount, and halftone parameter generation or halftone processing may be performed while keeping the granularity of each small group good. Furthermore, pixels that belong to the same printing order, pass, and timing to compensate for streaking, unevenness, and graininess deterioration due to landing interference when there is an error in dot diameter, dot shape, dot formation position, and non-discharge. After adding at least one error among a predetermined dot diameter, dot shape, dot formation position deviation, and non-discharge to the dots of the group, the type, contact direction and contact of the surrounding dots for the dots of each pixel of the group Approximate the moving direction and moving amount based on the amount, classify each dot into small groups with the same moving direction and / or the same moving amount based on the moving direction and / or moving amount, and improve the granularity of each small group The halftone parameter generation or the halftone process may be performed while maintaining the same.

  Alternatively, in order to compensate for streak, unevenness, and graininess deterioration due to landing interference when there is at least one error among dot diameter, dot shape, dot formation position deviation, and undischarge, the same printing order and pass Even if at least one error among a predetermined dot diameter, dot shape, dot formation position deviation, and non-discharge is added to a dot of a group of pixels belonging to the timing, the contact state of the dots of the group with surrounding dots Halftone parameter generation or halftone processing may be performed so as to reduce the change.

  A further specific example of a configuration for generating halftone parameters or performing halftone processing so as to impart resistance to landing interference will be described later.

<Significance of outputting a halftone selection chart>
The halftone selection chart has a first meaning of outputting in order to compare the processing results of two or more types of halftone processing rules, and a second meaning of outputting in order to confirm system instability, Has at least one of the following meanings. A chart configuration in which the processing results of two or more types of halftone processing rules are juxtaposed on one print medium 101 is useful in the first sense. On the other hand, when paying attention to the second significance, it is not always necessary to place the processing results of two or more types of halftone processing rules on one print medium 101. Rather, for the purpose of confirming the instability of the system depending on the location and the purpose of confirming the instability of the system with respect to time, only the processing result of one type of halftone processing rule is recorded on one print medium 101. It may be in the form of a chart.

<About generation of two or more types of halftone processing rules and comparison of the processing results>
In this embodiment, at least two types of halftone processing rules are generated, but more preferably, more than two types of halftone processing rules are generated.

  FIG. 17 is a graph showing qualitative tendencies of various halftone processing rules when the horizontal axis represents image quality and the vertical axis represents system cost or halftone processing time. Comparing the halftone algorithms of the dither method, error diffusion method, and DBS method relative to each other, the image quality is improved in the order of the dither method, error diffusion method, and DBS method. Regarding time, the cost increases and the time increases in the order of the dither method, the error diffusion method, and the DBS method. However, among the algorithms of the dither method, the error diffusion method, and the DBS method, the balance between the image quality and the system cost or the halftone processing time can be changed depending on the setting of the halftone parameter.

  Although various types of halftone processing with different balances of required items can be set, in the example shown in FIG. 17, the level of “image quality” is low / medium for each of the dither method, error diffusion method, and DBS method. A state is shown in which a total of nine types of settings are made in three different levels. In FIG. 17, D1, D2, and D3 indicate three types of settings in the dither method, ED1, ED2, and ED3 indicate three types of settings in the error diffusion method, and DBS1, DBS2, and DBS3 indicate three types in the DBS method. Shows the type settings.

  Further, apart from the pros and cons for each request item depending on the halftone algorithm described in FIG. 17, as shown in FIG. 18, if the granularity is improved with one parameter regardless of the halftone algorithm, the instability of the system There is a tendency that the tolerance to becomes worse.

  The horizontal axis of FIG. 18 indicates the granularity, and the vertical axis indicates the tolerance to the instability of the system. In FIG. 18, the tolerance against the instability of the system includes both viewpoints of graininess tolerance and streak tolerance, both of which have the same qualitative tendency. FIG. 18 shows only the tolerance of graininess. That is, as shown in FIG. 18, when the graininess is increased, the resistance to instability of the system is deteriorated and the resistance of streaks is also decreased. Conversely, at the expense of granularity, there is a relationship that resistance to system instability is improved and streak resistance is also improved.

  As an example of setting the tolerance against the instability of the system, for example, it is conceivable to perform three types of settings in which the tolerance level is changed in three stages of high / medium / low. T1, T2, and T3 in FIG. 18 indicate three types of settings for tolerance to system instability.

  Based on the qualitative tendency described with reference to FIGS. 17 and 18, two or more types of halftone processing rules having different balances of a plurality of requirement items for halftone processing are generated. For example, a total of 27 types of halftone processing rules can be generated by default by combining the nine types of settings described with reference to FIG. 17 and the three types of settings regarding the tolerance of graininess described with reference to FIG.

  A halftone selection chart based on the processing results of each of the 27 types of halftone processing rules can be output, and the user can select one halftone processing rule from among them.

  In addition, as another method, the user specifies the priority setting for the request item, and two or several types of halftone processing rules close to the priority setting are generated to reflect the user's intention in advance. Thus, the presentation range of the type of halftone processing may be narrowed down.

  For example, when the image quality-oriented setting is specified, the DBS method or the error diffusion method is narrowed down. When the image quality and cost balance are emphasized, the error diffusion method is used. When the cost-oriented setting is used, the dither method is used. In this way, halftone processing rules may be generated by restricting the types of halftone algorithms in advance.

  Of the required items, for the halftone processing time and cost, a target quantitative required value is often assumed in advance. That is, it can be considered that there are many cases where the user can set a target value in advance for the target halftone processing time and cost based on the demand for productivity and the like.

  Therefore, it is also possible to select a plurality of halftone processing rules from 27 types within a range that satisfies the user's request (target value) and actually output the halftone selection chart as a halftone selection chart.

<About selection of halftone processing>
As a method of selecting one halftone processing rule from two or more types of halftone processing rules, the chart output of the halftone selection chart is confirmed, and the user selects any one of the halftone processes. It is possible to adopt a configuration in which the system automatically selects one halftone process.

  In this case, the system holds in advance priority parameters for a plurality of request items. For example, regarding the first classification (a), there are requirements for image quality, system cost, halftone generation time, and regarding the second classification, granularity, tolerance to system errors, and the system has the following priority parameters A, B, C, D and p, q, r are held in advance, and a comprehensive evaluation value is calculated by the following equation.

Overall Evaluation Value = A × Image Quality Evaluation Value + B × System Cost + C × Halftone Generation Time + D × Halftone Processing Time Image Quality Evaluation Value = p × Granularity Evaluation Value [No System Error] + q × {Granularity Evaluation Value [System Error Existence (addition of “+ predetermined amount” error to the first group)] + graininess evaluation value [with system error (addition of “+ predetermined amount” error to the second group)] +… + granularity evaluation value [system error Existence (addition of “−predetermined amount” error to first group)] + granularity evaluation value [existence of system error (addition of “−predetermined amount” error to second group)] +…}
+ R × {streaks evaluation value [with system error (addition of “+ predetermined amount” error to the first group)] + streaks evaluation value [with system error (addition of “+ predetermined amount” of error to the second group)] +… + Streak evaluation value [with system error (addition of "-predetermined amount" error to first group)] + streak evaluation value [with system error (addition of "-predetermined amount" error to second group)] + ...} ..Formula (4)
Here, in order to obtain an image quality evaluation value, a simulation image is generated by the above-described method from the halftone processing result of the halftone selection chart, and a granularity evaluation value and a streak evaluation value are calculated. The evaluation values are averaged for each gradation, sky blue, and pale orange.

  For each ink type, the graininess evaluation value and the streak evaluation value may or may not be averaged. In order to obtain the granularity and streak evaluation values for system errors, simulation images are generated by adding errors to the dots of pixel groups (groups) that belong to the same conditions for each printing order, pass, and timing. Generating a simulation image.

  It should be noted that the simulation conditions applied when generating halftone processing rules for generating two or more types of halftone processing rules as a previous step and one selected from two or more halftone processing rules by user selection or automatic system selection. The simulation conditions applied at the time of simulation image quality evaluation in halftone selection for selecting two halftone processing rules do not necessarily match. For example, in the simulation of halftone processing generation, in order to promptly generate the halftone processing rules, the conditions that do not include the landing interference factor or only “dot movement” among the landing interference factors are considered. The simulation is performed under the conditions for simulation. In order to reproduce the actual image as faithfully as possible, the simulation includes all of the dot movement due to landing interference, each change in dot shape, and dot density. May be. Here, “halftone processing generation” indicates generation of a halftone parameter when the halftone algorithm is a dither method or an error diffusion method, and generation of a halftone image when the halftone algorithm is a DBS method.

  The predetermined amount of error to be added (that is, the predetermined error amount) may be determined as an appropriate value separately, or may be a standard deviation calculated from the result of reading the characteristic parameter acquisition chart. .

  Alternatively, instead of calculating the evaluation value based on the simulation image, the image reading device 26 reads the halftone selection chart output by the printing device 24, and calculates the graininess evaluation value and the stripe evaluation value from the read image. Then, the evaluation value values may be averaged as appropriate for each color, each gradation, sky blue, and pale orange, and an image quality evaluation value may be obtained by the following equation.

Image quality evaluation value = p × graininess evaluation value + r × streaks evaluation value Also, image quality evaluation value, system cost, halftone generation time, halftone processing time, graininess evaluation value [no system error], graininess evaluation value [system With an error], an allowable threshold value is set for each of the streak evaluation values, and a halftone processing rule in which each value is equal to or greater than the threshold value is extracted first, and based on the above comprehensive evaluation value, Optimal halftone processing may be determined.

  For example, to determine halftone processing with the lowest system cost, image quality evaluation value, system cost, halftone generation time, halftone processing time and graininess evaluation value [no system error], graininess evaluation value [with system error ], For each of the streak evaluation values, after first extracting a halftone process that exceeds the permissible threshold, the priority parameter B is set to a large value to obtain a comprehensive evaluation value.

  The comprehensive evaluation value is a form of “determination evaluation value”. Each of the priority parameters A, B, C, D, p, q, and r is set to a real number representing the priority.

  The priority balance of the first classification (a) and the second classification (b) of the request items is selected after one halftone processing rule is selected by automatic selection of the system or by user selection operation. A plurality of other halftone processing rules that are close to the selected halftone processing rule are generated, and an image quality evaluation value and a comprehensive evaluation value are calculated based on the priority parameter, or a halftone selection chart is output, Including these, the system or the user may be able to select a more optimal halftoning rule. When the system automatically selects halftone processing, generation of the halftone processing rule may be repeated until the image quality evaluation value and the overall evaluation value are equal to or greater than a predetermined threshold.

<Description of Functions of Image Processing Device According to Second Embodiment>
FIG. 19 is a block diagram for explaining functions of the image processing apparatus according to the second embodiment. Instead of the configuration of the image processing apparatus according to the first embodiment described in FIG. 3, the image processing apparatus according to the second embodiment shown in FIG. 19 can be used. 19, elements that are the same as or similar to the elements described in FIG. 3 are given the same reference numerals, and descriptions thereof are omitted.

  The halftone processing generation unit 58 in the image processing apparatus 20 according to the second embodiment shown in FIG. 19 includes a previous halftone processing generation unit 58A and a halftone automatic selection unit 58B. The pre-stage halftone process generation unit 58A defines halftones that define the processing contents of two or more types of halftone processes having different priority balances for a plurality of request items required for the halftone process based on the characteristic parameters. Generate processing rules. The halftone automatic selection unit 58B is based on the priority parameter among the types of halftone processing defined by the two or more types of halftone processing rules generated by the previous-stage halftone processing generation unit 58A. Processing for automatically selecting the type of halftone processing used for 10 printing is performed.

  The halftone automatic selection unit 58B has a configuration corresponding to one form of halftone automatic selection means. The halftone automatic selection unit 58B includes a determination evaluation value calculation unit 59 as one form of a determination evaluation value calculation unit.

  The determination evaluation value calculation unit 59 is a calculation unit that calculates a determination evaluation value for evaluating the appropriateness of the halftone process defined by the halftone processing rule generated by the previous-stage halftone process generation unit 58A. The determination evaluation value calculation unit 59 calculates a determination evaluation value based on the priority parameter held in the priority parameter holding unit 56. That is, the determination evaluation value calculation unit 59 calculates a comprehensive evaluation value that is a form of the determination evaluation value. Specific examples of the comprehensive evaluation value are as described above. The halftone automatic selection unit 58B automatically selects the type of halftone processing used for printing in the printing system 10 based on the determination evaluation value calculated by the determination evaluation value calculation unit 59.

  The priority parameter holding unit 56 stores a priority parameter designating a balance of priorities regarding a plurality of request items. The step of storing the priority parameter in the priority parameter holding unit 56 corresponds to one form of the priority parameter holding step.

  The priority parameter can be freely input by the user through the input device 34, and the priority balance can be set and the setting contents can be changed.

  Further, the image processing apparatus 20 includes an image quality evaluation processing unit 74 including a simulation image generation unit 68 and an evaluation value calculation unit 70, and the halftone processing generation unit 58 cooperates with the image quality evaluation processing unit 74 to perform half-processing. Generate tone processing rules. The simulation image generation unit 68 corresponds to one form of simulation image generation means. The evaluation value calculation unit 70 corresponds to one form of image quality evaluation value calculation means.

  The image quality evaluation processing unit 74 performs optimization search processing for improving the evaluation value while repeating the generation of the simulation image and the calculation of the evaluation value of the image quality for the simulation image. The halftone parameter is determined by the processing by the image quality evaluation processing unit 74. The simulation image generation unit 68 generates a simulation image when a halftone image obtained by applying the halftone process defined by the halftone processing rule generated by the previous-stage halftone process generation unit 58A is printed. The evaluation value calculation unit 70 calculates an image quality evaluation value from the simulation image generated by the simulation image generation unit 68. The determination evaluation value calculation unit 59 of the halftone automatic selection unit 58B can calculate the determination evaluation value using the image quality evaluation value calculated by the image quality evaluation processing unit 74.

  A plurality of types of halftone processing rules generated by the previous-stage halftone processing generation unit 58A are registered in the halftone processing rule storage unit 60.

  The image analysis unit 64 shown in FIG. 19 functions as a means for generating a characteristic parameter by analyzing the read image of the characteristic parameter acquisition chart, and also reads the halftone selection chart output from the printing device 24. It functions as means for analyzing the image and calculating a quantitative evaluation value of the halftone image. The determination evaluation value calculation unit 59 of the halftone automatic selection unit 58B determines at least one of the granularity evaluation value and the streak evaluation value calculated by the image analysis unit 64 based on the output result of the halftone selection chart. Evaluation value information can be obtained from the image analysis unit 64 and a determination evaluation value can be calculated. The halftone automatic selection unit 58B can perform a process of automatically selecting an optimum halftone processing rule based on the quantitative evaluation value calculated from the read image of the halftone selection chart.

  FIG. 20 is a flowchart showing a halftone processing rule generation method in a printing system including an image processing apparatus according to the second embodiment.

  20, steps (steps) common to the steps in the flowchart described in FIG. 4 are given the same step numbers, and descriptions thereof are omitted. In FIG. 20, the process from step S10 to step S14 is the same as the flowchart of FIG.

  In step S14, after two or more types of halftone processing rules are generated based on the characteristic parameter, one type of halftone is selected based on the priority parameter from among the generated two or more types of halftone processing rules. A processing rule is determined (step S17). That is, the combination of step S14 and step S17 corresponds to one form of a halftone process generation process. In step S14, two or more types of halftone processing rules are generated as a pre-stage for obtaining one optimum halftone processing for the system. In step S17, priority is given to the two or more types of halftone processing rules generated in step S14. A step-by-step process of selecting an optimum degree parameter is performed.

  However, the embodiment of the present invention is not necessarily limited to the configuration through the stepwise processing steps as shown in FIG. For example, an evaluation function that reflects the setting of the priority parameter is defined, and an optimization method that searches for an optimal solution that maximizes or minimizes the evaluation value as the evaluation function value for the combination of the halftone algorithm and the halftone parameter It can be configured to generate one type of halftone processing rule.

  In this case, it can be said that multiple types of halftone processing rules are generated in the process of calculating the optimum solution, but the halftone processing that is finally generated as a type of halftone processing that can be used in the system The rule can be interpreted as one type of halftone processing rule as an optimal solution.

  Even if it is configured to automatically select (determine) one halftone processing rule by the system according to the setting of the priority parameter, the user selects the halftone processing rule determined by the automatic selection thereafter. It is good also as a structure which can be changed suitably. In addition, various halftone processing rules generated by the image processing apparatus 20 can be changed so that the priority parameter setting can be changed and the halftone processing rules can be selected again by a user operation or a system program. It is preferable to register as a lineup.

  In addition, the information on halftone processing rules such as granularity, streak quantitative evaluation values, halftone generation time, halftone processing time, and system cost can be referred to as needed. It is preferable to store it in association with the tone processing rule.

  The image quality evaluation value, the system cost, the halftone generation time, and the halftone processing time are calculated for each ink color used in the printing apparatus 24, that is, for each ink type. You can select tone parameters, or calculate the image quality evaluation value, system cost, halftone generation time, and halftone processing time for all colors, and select the same common halftone algorithm and halftone parameters for all colors. May be.

<Other example of characteristic parameter acquisition chart>
FIG. 21 is a diagram showing another example of the characteristic parameter acquisition chart. A characteristic parameter acquisition chart 200 shown in FIG. 21 is an example of a characteristic parameter acquisition chart output by a single pass printer.

  A characteristic parameter acquisition chart 200 shown in FIG. 21 includes single dot patterns 202C, 202M, 202Y recorded on a print medium 201 by nozzles that are printing elements in cyan, magenta, yellow, and black recording heads. 202K, first continuous dot patterns 204C, 204M, 204Y, and 204K, and second continuous dot patterns 206C, 206M, 206Y, and 206K.

  The single dot patterns 202C, 202M, 202Y, and 202K are discrete dot patterns that are discretely recorded in an isolated state in which a single dot is separated from other dots. The first continuous dot patterns 204C, 204M, 204Y, and 204K and the second continuous dot patterns 206C, 206M, 206Y, and 206K are patterns of continuous dots that are recorded by bringing two or more dots into contact with each other.

  The single dot patterns 202C, 202M, 202Y, and 202K correspond to the single dot patterns 102C, 102M, 102Y, and 102K in the characteristic parameter acquisition chart 100 described with reference to FIG. 21 corresponds to the first continuous dot patterns 104C, 104M, 104Y, and 104K in the characteristic parameter acquisition chart 100 described in FIG. 5, and the first continuous dot patterns 204C, 204M, 204Y, and 204K in FIG. The second continuous dot patterns 206C, 206M, 206Y, and 206K in FIG. 21 correspond to the second continuous dot patterns 106C, 106M, 106Y, and 106K in the characteristic parameter acquisition chart 100 described in FIG. However, the first continuous dot patterns 104C, 104M, 104Y, and 104K and the second continuous dot patterns 106C, 106M, 106Y, and 106K in FIG. 5 are a plurality of dots that are in contact with each other in the main scanning direction. On the other hand, the first continuous dot patterns 204C, 204M, 204Y, and 204K and the second continuous dot patterns 206C, 206M, 206Y, and 206K in FIG. 21 are adjacent to each other in the sub-scanning direction. It is different in that it has become.

  In the case of the single pass method, as in the case of the serial scan method, a continuous dot pattern with multiple levels that changes not only the distance between the two dots that are deposited in an overlapping manner but also the droplet ejection time is formed. May be. In the case of the single pass method, it is possible to change the droplet ejection time difference between two dots of the continuous dot pattern by changing the conveyance speed of the printing medium 201.

  FIG. 22 is a schematic plan view of a recording head portion of an ink jet printing apparatus as a single pass printer used for outputting the characteristic parameter acquisition chart 200 shown in FIG. In FIG. 22, the vertical direction from top to bottom is the conveyance direction of the print medium 201. Various means such as a drum conveyance method, a belt conveyance method, a nip conveyance method, a chain conveyance method, and a pallet conveyance method can be adopted as a means for conveying the print medium 201 (medium conveyance means), and these methods are appropriately combined. be able to. The conveyance direction of the print medium 201 is referred to as “medium conveyance direction”. In FIG. 22, the medium conveyance direction is indicated by a white arrow. The medium conveyance direction corresponds to the “sub-scanning direction”. The horizontal direction in FIG. 22, that is, the direction parallel to the paper surface and orthogonal to the medium transport direction is referred to as “medium width direction”. The medium width direction corresponds to the “main scanning direction”.

  An inkjet printing apparatus as a single pass printer shown in FIG. 22 includes a cyan recording head 212C that discharges cyan ink, a magenta recording head 212M that discharges magenta ink, a yellow recording head 212Y that discharges yellow ink, and black ink. And a black recording head 212K for discharging.

  Each of the cyan recording head 212C, the magenta recording head 212M, the yellow recording head 212Y, and the black recording head 212K has a plurality of nozzles arranged over a length corresponding to the maximum width of the image forming area in the medium width direction orthogonal to the medium conveyance direction. It is a line head which has the nozzle row made.

  Various designs are possible for the number of nozzles, the nozzle arrangement, and the nozzle density in each color recording head (212C, 212M, 212Y, 212K). The print heads for each color (212C, 212M, 212Y, 212K) may have a common head design for all colors, or may have a different head design for some colors or for each color print head.

  Here, in order to simplify the illustration, it is assumed that the recording heads (212C, 212M, 212Y, 212K) of each color have a common structure by the head design common to all colors, and the recording heads (212C, 212M, 212Y, 212K). ), Only 40 nozzles are shown. Although FIG. 22 illustrates an inkjet printing apparatus that uses four colors of CMYK inks, the combination of ink colors and the number of colors is not limited to this embodiment. As described in FIG. 6, light ink, dark ink, and special color ink may be added as necessary. Further, the arrangement order of the recording heads for each color is not limited to the example shown in FIG.

  On the ink discharge surface of the cyan recording head 212C shown in FIG. 22, a plurality of ink discharge nozzles 218C have a row direction along the main scanning direction and a fixed angle that is non-parallel and non-orthogonal to the main scanning direction. They are arranged in a regular arrangement pattern in each direction with the oblique row direction. Here, an example of a nozzle arrangement by a matrix arrangement of 4 rows × 10 columns in which 10 rows of nozzle rows in which four nozzles 218C are arranged at regular intervals along the oblique row direction are formed in different positions in the main scanning direction. It is shown.

  In such a two-dimensional nozzle array, there are four row-direction nozzle columns in which ten nozzles 218C are arranged at regular intervals along the row direction at different positions in the sub-scanning direction. For these four row direction nozzle columns, from the bottom to the top of FIG. 22 (that is, from the downstream side to the upstream side in the medium width direction), the first row, the second row, the third row, and the fourth row When row numbers are assigned in the order of the eyes, the nozzle positions in the main scanning direction are different between the first row and the second row. Similarly, the nozzle positions in the main scanning direction are different between the second row, the third row, the third row, the fourth row, the fourth row, and the first row.

When the main scanning direction of the nozzle spacing of nozzles 218C arranged in a row at regular intervals to L _N in the row direction nozzle row, the first row and the second row, second row and third row, the third row and the fourth row The amount of shift of the nozzle positions in the main scanning direction of the fourth and first rows is L _N / 4, which is a value obtained by dividing L _N by the total number of rows. Such a two-dimensional nozzle arrangement can be considered as a nozzle row in which the nozzles 218C are arranged at equal intervals (interval “L _N / 4”) in the main scanning direction.

  The cyan recording head also includes the arrangement of the ink ejection nozzles 218M in the magenta recording head 212M, the arrangement of the ink ejection nozzles 218Y in the yellow recording head 212Y, and the arrangement of the ink ejection nozzles 218K in the black recording head 212K. It is the same as the nozzle arrangement form of 212C.

  In general, in the case of a recording head having a two-dimensional nozzle array, the nozzles in the two-dimensional nozzle array are projected so as to be aligned along the medium width direction (corresponding to the main scanning direction). The (normally projected) projected nozzle array can be considered to be equivalent to a single nozzle array in which the nozzles are arranged at approximately equal intervals at a nozzle density that achieves the recording resolution in the main scanning direction (medium width direction). Here, “equal intervals” means substantially equal intervals as droplet ejection points that can be recorded by the ink jet printing apparatus. For example, the concept of “equally spaced” also includes cases where the intervals are slightly different in consideration of manufacturing errors and movement of droplets on the medium due to landing interference. Considering projection nozzle rows (also referred to as “substantial nozzle rows”), nozzle positions (nozzle numbers) can be associated with the order of projection nozzles arranged along the main scanning direction. The number of nozzles constituting the two-dimensional nozzle array and the nozzle arrangement form are appropriately designed according to the recording resolution and the drawable width.

  Further, in configuring the line head, there is also an aspect in which a line head having a nozzle row of a required length in the medium width direction is formed by connecting a plurality of short head modules in which a plurality of nozzles are two-dimensionally arranged. Is possible.

  As shown in FIG. 22, an ink jet printing apparatus using a recording head (212C, 212M, 212Y, 212K) as a line head having a nozzle row having a length corresponding to the entire width of the image forming area of the printing medium 201 is not shown. The print medium 201 is transported at a constant speed by the medium transport means, and droplets are ejected from the respective recording heads (212C, 212M, 212Y, 212K) at an appropriate timing in accordance with the transport of the print medium 201. The image forming area of the print medium 201 can be moved only once (i.e., in one sub-scan) by moving the print medium 201 relative to each recording head (212C, 212M, 212Y, 212K) in the transport direction. Can record images.

  According to the configuration of FIG. 22, the print medium 201 is transported at a constant speed in the medium transport direction by a medium transport means (not shown), and each of the recording heads (212C, 212M, 212Y, 212K) is appropriately timed. By performing droplet ejection from the nozzles (218C, 218M, 218Y, 218K), single dot patterns 202C, 202M, 202Y, 202K shown in FIG. 21 and first continuous dot patterns 204C, 204M, 204Y, 204K Second continuous dot patterns 206C, 206M, 206Y, and 206K can be formed.

  That is, by performing droplet ejection from each nozzle 218C of the cyan recording head 212C, the single dot pattern 202C, the first continuous dot pattern 204C, and the second continuous dot pattern 206C in FIG. 21 can be formed. . The first continuous dot pattern 204C and the second continuous dot pattern 206C have different inter-dot distances between two overlapping dots. That is, the first continuous dot pattern 204C and the second continuous dot pattern 206C differ in the interval between two droplet ejection timings for recording two overlapping dots.

  The same applies to each of the colors M, Y, and K. When the printing medium 201 is transported and droplets are ejected from each nozzle 218M of the magenta recording head 212M in FIG. A dot pattern 202M, a first continuous dot pattern 204M, and a second continuous dot pattern 206M can be formed.

  Further, by transporting the printing medium 201 and performing droplet ejection from each nozzle 218Y of the yellow recording head 212Y of FIG. 22 at an appropriate timing, the single dot pattern 202Y of FIG. 21 and the first continuous dot pattern 204Y of FIG. , And the second continuous dot pattern 206Y can be formed.

  Similarly, by transporting the printing medium 201 and performing droplet ejection from each nozzle 218K of the black recording head 212K of FIG. 22 at an appropriate timing, the single dot pattern 202K of FIG. 204K and the second continuous dot pattern 206K can be formed.

  In FIG. 21, in order to prevent dots adjacent in the horizontal direction (main scanning direction) from overlapping, in FIG. 22, the droplet ejection timing of nozzles adjacent in the horizontal direction needs to be separated by a predetermined time (a time difference is provided). There is. The “nozzle adjacent in the horizontal direction” here is a nozzle adjacent in the projection nozzle row as the “substantial nozzle row” arranged in the horizontal direction.

  In the case of the configuration shown in FIG. 22, droplets are ejected in the order of K → Y → M → C in accordance with the conveyance of the print medium 201, and for each color, the first line of the four lines in the two-dimensional nozzle array By performing droplet ejection in the order of the second line, the third line, and the fourth line, a pattern as shown in FIG. 21 can be formed. However, the droplet ejection timing of the nozzles of each color and each row needs to be separated by a predetermined amount (a time difference is provided) so that dots recorded by different nozzles do not overlap each other.

  The droplet ejection timing control as described above is realized by a combination of the already described characteristic parameter acquisition chart generation unit 62 (see FIGS. 3 and 19) and the print control device 22 (see FIG. 2). Instead of the configuration described in FIGS. 5 and 6, the configuration described in FIGS. 21 and 22 can be employed.

<Inclusion of system characteristic parameters based on the concept of system error>
In the description so far, the term “system error” in the terms “no system error” or “system error tolerance” refers to an error that mainly changes over time and / or from place to place as a fluctuation component of a characteristic parameter. I explained it with meaning.

  On the other hand, the system error includes reproducible errors such as non-discharge due to nozzle failure and nozzle position error due to manufacturing error, as already described. These reproducible errors can be grasped as parameters indicating the characteristics of the system, and can be considered as parameters of “system error”. That is, among the system errors, those that can be definitely defined by measurement based on the reading result of the test chart, input from the user, or the like, that is, reproducible errors can be considered as characteristic parameters of the system. This reproducible error is referred to as “characteristic error” in this specification. The characteristic error represents the meaning of an error as a system characteristic. Among system errors, a characteristic error, which is a reproducible error, becomes a system characteristic parameter. For the characteristic error, it is possible to generate an optimum halftone processing rule that allows for the characteristic error.

  On the other hand, system errors that change with time and / or from place to place, that is, errors that fluctuate irregularly, are referred to as “random system errors” in this specification. For random system errors, it is only possible to design halftones that provide tolerance to errors.

  The relationship between the characteristic error and the random system error is expressed by the representative values such as the expected value (average value) and median of the measured value distribution of a certain error item of interest, and the variation from the representative value or the fluctuation range. It can be understood that this corresponds to the relationship of “

  A further specific example of the system error will be described. Examples of “system error” common to the serial scan inkjet printing system and the single-pass inkjet printing system include head nozzle error, ejection failure, and positional deviation for each droplet type.

  The nozzle error includes an error in the flying direction of droplets of each nozzle, an error in ejection speed, an error in droplet amount, or an error in dot shape. The discharge speed may be expressed by the term “droplet speed”. The drop amount error can be grasped as a dot density error. The dot shape is synonymous with “dot profile”. In addition, since the error in the flying direction, the error in the ejection speed, the error in the droplet amount, and the error in the dot shape may be errors depending on the droplet type, it is possible to grasp these errors for each droplet type. preferable.

  Nozzle error is a comprehensive representation of nozzle position error, dot density error, dot diameter error, dot shape error, or an appropriate combination of these errors in the main scanning direction and / or sub-scanning direction. It is a term to do.

  The droplet type is a type of droplet corresponding to a dot size that can be recorded and controlled by the head. For example, in the case of a configuration capable of controlling ejection of small droplets, medium droplets, and large droplets corresponding to three types of dot sizes of small dots, medium dots, and large dots, the droplet types are three types. The positional deviation for each droplet type means a landing position error in the main scanning direction and / or the sub-scanning direction for each droplet type.

  The nozzle error of each nozzle can define a value that can be treated as a “characteristic error” that is observed approximately averagely for each nozzle, while changing over time and / or from place to place “random system error” Can be the target of.

  Examples of “system error” in an inkjet printing system of a serial scan method include a bidirectional positional deviation of scanning, a bidirectional positional deviation of each droplet type, a head vibration error due to carriage movement, or a paper conveyance error. .

  Bidirectional misregistration is an error in the main scanning direction between the dot recording position when a droplet is ejected while moving in the forward direction in the reciprocating operation of the carriage and the dot recording position when a droplet is ejected while moving in the backward direction. .

  The bi-directional positional deviation for each droplet type is an error in the position in the main scanning direction and the sub-scanning direction for each droplet type when droplets are ejected while moving in the forward and backward directions of the carriage movement.

  The head vibration error is observed as a change in dot position in the main scanning direction and / or sub-scanning direction due to vibration of the driving belt of the carriage. The paper transport error is a paper feed amount error in the sub-scanning direction that is the paper transport direction. The paper transport error is observed as a recording position error in the sub-scanning direction.

  As an example of “system error” in a single-pass inkjet printing system, an error due to vibration of a head module constituting a line head (referred to as “head module vibration error”) or an error in the mounting position of each head module. (Head module mounting error). The head module vibration error is observed as an error in the dot position in the main scanning direction and / or the sub-scanning direction. Head module mounting errors can also be observed as dot position errors in the main scanning direction and / or sub-scanning direction.

  The head module mounting error corresponds to a characteristic error.

[Chart for obtaining system error parameters]
FIG. 5 illustrates the “characteristic parameter acquisition chart” for acquiring characteristic parameters. As described above, since the characteristic parameter can be grasped as a parameter indicating the characteristic error among the system errors, it can be understood that the characteristic parameter is a kind of system error parameter. Therefore, it is understood that the “characteristic parameter acquisition chart” corresponds to one form of the “system error parameter acquisition chart”.

  The following chart can be used as a system error parameter acquisition chart in the serial scan type inkjet printing system.

  (Example 1) Of the system errors, the chart for obtaining each nozzle error, discharge failure parameter, etc. can be the characteristic parameter acquisition chart described in FIG.

  (Example 2) In order to grasp the nozzle error for each drop type, such as a position shift for each drop type (including bidirectional position shift), the characteristic parameter acquisition chart described in FIG. Create for each outbound and inbound trip. For example, in the case of a system capable of controlling droplet ejection of three types of droplets, small droplets, medium droplets, and large droplets, the characteristic parameter acquisition chart illustrated in FIG. 5 for each droplet type of small droplets, medium droplets, and large droplets. Is output and measured. With respect to each droplet type, it is possible to obtain positional shift information indicating how much the position of the dot actually recorded is shifted from the target recording position (pixel position). Further, the characteristic parameter acquisition chart described in FIG. 5 is created for each drop type for each of the forward path and the return path. From the measurement results of the respective charts, it is possible to acquire positional deviation information regarding the carriage movement direction (main scanning direction) of each of the forward path and the backward path for each droplet type.

  (Example 3) FIG. 23 shows an example of a chart for measuring head vibration error due to carriage movement. Here, for simplicity of illustration, only the black recording head 112K is schematically shown. As shown in FIG. 23, a chart for head vibration error measurement is created by continuously ejecting with a specific nozzle 118S of the recording head while moving the carriage. “Continuous ejection” here means that the dots are not overlapped but are repeatedly ejected in a cycle with a time interval so that they are recorded as individually separated (isolated) independent dots. .

  In FIG. 23, for convenience of explanation, the dot interval in the main scanning direction and the head vibration error are drawn extremely greatly (deformed). Along with the movement of the carriage, the head vibrates and the amount of deviation in the main scanning direction and / or the sub-scanning direction varies.

  The output result of the chart as shown in FIG. 23 is read by an image reading device 26 (see FIG. 1) such as an in-line sensor, and the main scanning direction and the sub-scanning direction with respect to the ideal position where each dot is supposed to be hit. Measure the amount of each deviation. Measure how much the actual landing position is shifted from each pixel position. The ideal positions that should be hit are determined by pixel positions in a line in the main scanning direction. The position of the pixel to be originally hit in the main scanning direction is represented by “n”, and the deviation amount Δx (n) in the main scanning direction and the deviation amount Δy (n) in the sub scanning direction with respect to each pixel position n can be measured (FIG. 24). “N” indicates the position coordinate (X coordinate) of the pixel in which the ejection has been performed in the main scanning direction. n can be an integer from 0 to N. In this case, N represents an integer corresponding to the number of dots to be ejected. Δx (n) and Δy (n) represent deviations from the ideal landing position.

  25A and 25B show examples of head vibration errors. In FIG. 25A, the horizontal axis represents the pixel position n in the main scanning direction, and the vertical axis represents the positional deviation amount in the main scanning direction. In FIG. 25B, the horizontal axis represents the pixel position n in the main scanning direction, and the vertical axis represents the positional deviation amount in the sub-scanning direction.

  Thus, the amount of deviation Δx (n) in the main scanning direction and the amount of deviation Δy (n) in the sub-scanning direction are obtained as a function of the pixel position n.

  In addition, in FIG. 23, although the example which performs continuous droplet ejection from the specific single nozzle 118S was demonstrated, continuous droplet ejection was similarly performed from a plurality of specific nozzles and obtained from each measurement. The deviation amounts Δx (n) and Δy (n) to be generated may be statistically processed to generate a head vibration error parameter.

  (Example 4) The paper transport error is an error indicating variation in the paper feed amount. The paper transport error is an error in which the dot position is shifted due to the paper transport mechanism in the printing system. FIG. 26 is an example of a chart for obtaining information on the paper transport error. Here, for simplicity of illustration, only the black recording head 112K is schematically shown. When acquiring the parameters of the paper transport error, as in the example of FIG. 23, continuous droplet ejection is performed by a specific nozzle 118S of the recording head, and a line of dot rows along the main scanning direction is drawn. Note that the specific nozzle 118S in FIG. 23 and the specific nozzle 118S in FIG. 26 may be the same nozzle or different nozzles.

As shown in FIG. 26, after the dot row DL1 in the first row is drawn, a certain amount of paper is conveyed in the sub-scanning direction. “Paper transport” is synonymous with “paper feed” and “paper feed”. A control amount for a certain amount of paper conveyance is assumed to be Δy ₀ . Similarly, the dot row DL2 in the second row is drawn. A plurality of dot rows DL1, DL2, DL3,... Are drawn by repeating such a constant amount Δy ₀ of paper conveyance and continuous droplet ejection. This chart is preferably recorded by scanning only one of the carriage movement forward path and the backward path only.

The pixel position as the ejection command position of each dot in the k-th dot row is represented as (n, k). k is an integer from 1 to m, and m is an integer of 2 or more. The average value yav (k) of the sub-scanning direction position of each dot in the k-th dot row and the average value yav (k + 1) of the sub-scanning direction position of each dot in the (k + 1) -th dot row. The difference yav (k + 1) −yav (k) is measured as the k-th paper feed amount Δyk. Error of the k-th sheet conveyance can be represented by Δyk-Δy _0.

  FIG. 27 shows an example of the distribution of measured values of Δyk (k = 1, 2... M−1) measured from the sheet conveyance error measurement chart. The horizontal axis indicates the paper conveyance error Δy. The paper feed amount distribution shown in the figure is a distribution according to the normal distribution.

  The following chart can be used as a system error parameter acquisition chart in the single-pass inkjet printing system.

  (Example 5) Of the system errors, the chart for obtaining each nozzle error, discharge failure parameter, etc. can use the characteristic parameter acquisition chart described with reference to FIG.

  (Example 6) In order to grasp the nozzle error for each drop type, such as positional deviation for each drop type (including bidirectional positional deviation), the characteristic parameter acquisition chart described in FIG. 21 is created for each drop type. To do. For example, in the case of a system capable of controlling droplet ejection of three types of droplets, small droplets, medium droplets, and large droplets, the characteristic parameter acquisition chart illustrated in FIG. 5 for each droplet type of small droplets, medium droplets, and large droplets. Is output and measured. With respect to each droplet type, it is possible to obtain positional shift information indicating how much the position of the dot actually recorded is shifted from the target recording position (pixel position).

  (Example 7) FIG. 28 shows an example of a chart for acquiring a head vibration error parameter in the single pass method. In FIG. 28, only the cyan recording head 212C is shown for convenience of illustration. The cyan recording head 212C of FIG. 28 is a line head configured by connecting a plurality of head modules 220-j (j = 1, 2,..., Nm). In the figure, an example of Nm = 5 is shown as an example of the number of head modules connected, but the number of connections is not particularly limited and can be designed to an arbitrary number.

  The plurality of head modules 220-j (j = 1, 2,..., Nm) are fixed to a common support frame 222 and are in the form of one head bar as a whole. The dot recording position varies due to the vibration of the head bar itself. As shown in FIG. 28, while the print medium 201 is conveyed at a constant speed in the sub-scanning direction, ejection is continuously performed from a specific single nozzle 228S, and dot rows arranged in the sub-scanning direction are recorded. As in the example described with reference to FIG. 23, “continuous ejection” is a cycle in which the dots are not overlapped but are spaced apart so as to be recorded as individually separated (isolated) independent dots. It means repeating the discharge.

  Similarly to FIG. 23, FIG. 28 is drawn with extremely large emphasis (deformation) on the dot interval in the sub-scanning direction and the head vibration error for convenience of explanation. The deviation in the main scanning direction and / or the sub-scanning direction varies due to the vibration of the head bar.

  28 is read by an image reading device 26 (see FIG. 1) such as an in-line sensor, and the main scanning direction and the sub-scanning direction with respect to the ideal position where each dot is supposed to be hit. Measure the amount of each deviation. Measure how much the actual landing position is shifted from each pixel position. The ideal positions to be hit are determined in a line in the sub-scanning direction. The position of the pixel to be originally hit in the sub-scanning direction is represented by “n”, and the shift amount Δx (n) in the main scanning direction and the shift amount Δy (n) in the sub-scanning direction with respect to each pixel position n can be measured. Here, “n” indicates the position coordinate (Y coordinate) in the sub-scanning direction of the pixel on which ejection has been performed.

  Similarly to the example described with reference to FIG. 23, the head vibration error parameter in the single-pass method can be obtained from the measurement result of the chart of FIG.

  (Example 8) There is a head module mounting error as a system error peculiar to the single pass method. FIG. 29 is an example of a chart for obtaining a parameter of the head module mounting error. Each head module 220-j (j = 1, 2,... Nm) may be mounted with a deviation from the designed mounting position (ideal mounting position). The mounting position of each head module 220-j (j = 1, 2,... Nm) may include a main scanning direction error, a sub-scanning direction error, and an in-plane rotation direction error. Due to the head module mounting error, the dot recording position deviates from the ideal position.

  In the chart shown in FIG. 29, each nozzle group of the head module 220-j (j = 1, 2,... Nm) ejects a pixel row arranged in a line in the main scanning direction, and the head module 220-j. A dot row Ds (j) in units of (j = 1, 2,... Nm) is recorded.

  Then, from the read image of the chart, for each dot row Ds (j) for each head module 220-j (j = 1, 2,... Nm), the cluster of dot rows Ds (j) is determined from the respective density distributions. The center-of-gravity position G (j) and the inclination angle θ (j) with respect to the main scanning direction are calculated (see FIGS. 30A and 30B).

Each dot row Ds (j) has a center of gravity position G ₀ (j) that is originally aimed (that is, ideal in design). Therefore, as shown in FIG. 30A, the barycentric position G (j) of the dot row Ds (j) calculated from the chart reading is changed from the ideal barycentric position G ₀ (j) to the main scanning direction, and It is possible to grasp the deviation of the center of gravity position indicating how much the deviation is in each of the sub-scanning directions. The main scanning direction error and the sub-scanning direction error can be grasped from the deviation of the center of gravity position. Further, since it is also assumed that the head module 220-j (j = 1, 2,... Nm) is mounted in rotation in the plane, as shown in FIG. The inclination angle θ (j) of the dot row Ds (j) with respect to the direction is also measured. This inclination angle θ (j) indicates an error in the in-plane rotation direction.

[Accumulation and utilization of system error parameters]
The “head module mounting error” exemplified above does not change with time, but corresponds to a characteristic error that is definitely determined by mounting the head module. On the other hand, each error such as each nozzle error (including each nozzle error for each droplet type), bidirectional positional deviation (including bidirectional positional deviation for each droplet type), head vibration error, and paper transport error. Items can change over time.

  Therefore, the system error parameter acquisition results obtained from each chart described above are accumulated in a memory or other storage unit, and the accumulated system error parameter data acquired in the past and the newly acquired system error parameter are In addition, it is also preferable to update the distribution data of the system error, determine a “random system error” based on the updated updated system error distribution, and perform tolerance design against the system error.

  For characteristic errors included in system errors, the value of "characteristic error" can be updated from the distribution of data including accumulated data of system error parameters acquired in the past and newly acquired system error parameters. preferable.

[Generation of simulation images and evaluation of image quality in system error tolerance design]
When system errors are classified from the viewpoints of characteristic errors and random system errors, when generating halftone processing rules, simulation image generation and image quality evaluation when designing tolerance to system errors are performed. The total value (weighted sum) of evaluations for each level is used as the image quality evaluation value.

  In the generation of the simulation image, “a plurality of levels” of the random system error to be added is configured in accordance with the system error distribution in the printing system.

  FIG. 31 is a graph showing the relationship between the system error distribution and the level of the random system error reflected in the generation of the simulation image.

  The horizontal axis in FIG. 31 is the system error. Specific items of the system error may be each nozzle error, bi-directional positional deviation, head vibration error, or paper conveyance error.

  As shown in FIG. 31, the system error is distributed in the positive and negative directions with the characteristic error value A as the center. A plurality of levels of random system errors are determined within such a range of the system error distribution. In the example of FIG. 31, an example in which four levels of ± σ and ± 2σ are determined using the standard deviation σ of the system error distribution is shown. The characteristic error value A corresponds to an average value in the system error distribution. The level is not limited to the configuration that defines the level using the standard deviation σ, and the level can be determined by an arbitrary numerical value.

  When the four levels of “−2σ”, “−σ”, “+ σ” and “+ 2σ” are defined as error amounts to be added as random system errors when generating a simulation image, A level error amount is added to generate a simulation image for each level, and the image quality of each simulation image is evaluated.

  Also, an image quality evaluation value as a total value is calculated from the evaluation of the simulation image performed for each level. In this case, the frequency of applying each of the random system errors at a plurality of levels may follow the distribution shown in FIG. “Frequency” follows the system error distribution means that, for the vicinity of the central value of the distribution, more simulation images are generated and respective evaluation values are calculated.

  Alternatively, a weighted sum may be calculated by multiplying a simulation image of random system errors at each level, or evaluation values thereof, by a weighting factor according to the distribution shown in FIG.

  For example, as shown in FIG. 32, four levels of “+ a1”, “+ a2”, “−a1” and “−a2” are defined as a plurality of levels of random system errors from the system error distribution. Explain the case. Here, a1 and a2 are numerical values satisfying “0 <a1 <a2”. In order to simplify the explanation, the central value (average value) of the system error distribution is set to “0”, and the distribution function f (x) is assumed to be a normal distribution, and the level is set symmetrically.

  In this case, the evaluation values of each simulation image to which random system errors of each level are given are expressed as Val [+ a1], Val [+ a2], Val [-a1] and Val [-a2], respectively. An image quality evaluation value Total_Value as a comprehensive evaluation value, which is a comprehensive evaluation value of a simulation image to which a system error is added, is expressed by the following equation.

Total_Value = A1 × Val [+ a1] + A2 × Val [+ a2] + A3 × Val [−a1] + A4 × Val [−a2] (5)
The weighting factors A1, A2, A3, and A4 follow the system error distribution of FIG. That is, if the distribution function of the system error distribution is represented by f (x), f (−a1) = f (a1) and f (−a2) = f (a2), and a positive proportional constant u is used. Thus, A1 = A3 = u * f (a1) and A2 = A4 = u * f (a2).

  In FIG. 32, for simplicity of explanation, the center value (average value) of the system error distribution is set to “0” and the distribution function f (x) is a normal distribution, and four levels are set symmetrically. Although an example has been described, the distribution function can be determined based on actual chart measurement values, and a plurality of levels can be arbitrarily set within the range of the spread of the distribution.

[Applied to the formula for calculating the image quality evaluation value]
The expressions (1) to (4) for evaluating the image quality described above are re-examined from the viewpoint of the characteristic error and the random system error as its fluctuation component as follows. That is, the description of the graininess evaluation value [no system error] described in the equations (1) to (4) can be understood by replacing the graininess evaluation value [no random system error (with characteristic error)]. The description of the evaluation value [with system error] can be understood as the granularity evaluation value [with random system error]. The description of the streak evaluation value [with system error] can be understood as the streak evaluation value [with random system error]. Hereinafter, for each of the formulas (1) to (4), the modified formula will be described by introducing the concept described in FIG. 32 and the formula (5).

[1] In the case of the dither method The following equation (6) can be used as a correction equation of the equation (1) in the case of the dither method.

Image quality evaluation value = granularity evaluation value [no random system error (with characteristic error)] +
α × {A1 × (granularity evaluation value [with system error (+ a1)] + granularity evaluation value [with system error (−a1)]) + A2 × (granularity evaluation value [with system error (+ a2)] + Graininess evaluation value [with system error (−a2)]) + ...}
+ Β × {A1 × (streaks evaluation value [with system error (+ a1)] + streaks evaluation value [with system error (−a1)]) + A2 × (streaks evaluation value [with system error (+ a2)] + streaks Evaluation value [with system error (−a2)]) + ...}
... Formula (6)
Note that a1, a2, A1, and A2 follow the relationship described in FIG. It can replace with Formula (1) and can evaluate using Formula (6).

[2] In the case of the error diffusion method The error diffusion method is the same as that in the case of the dither method, and the following equation (7) is used as a correction equation of the equation (2) in the case of the error diffusion method described above. Can be used.

“Evaluation value of graininess [with system error]
= Α × {A1 × {granularity evaluation value [with system error (addition of “+ a1” error to the first group)] + granularity evaluation value [with system error (addition of “+ a1” error to the second group)] + + Graininess evaluation value [with system error (addition of "-a1" error to the first group)] + Graininess evaluation value [with system error (addition of "-a1" error to the second group)] + ...}
+ A2 × {granularity evaluation value [with system error ("+ a2" error added to first group)] + graininess evaluation value [with system error ("+ a2" error added to second group)] + ...
+ Graininess evaluation value [with system error (addition of “−a2” error to the first group)] + Graininess evaluation value [with system error (addition of “−a2” error to the second group)] +…} +. .}
+ Β × {A1 × {streaks evaluation value [with system error (addition of “+ a1” error to the first group)] + streaks evaluation value [with system error (addition of “+ a1” error to the second group)] +…
+ Streak evaluation value [with system error (addition of "-a1" error to the first group)] + streak evaluation value [with system error (addition of "-a1" error to the second group)] +…}
+ A2 x {Strip evaluation value [with system error (addition of "+ a2" error to the first group)] + Stripe evaluation value [with system error (addition of "+ a2" error to the second group)] + ...
+ Streak evaluation value [with system error (addition of "-a2" error to the first group)] + streak evaluation value [with system error (addition of "-a2" error to the second group)] +…} + ...} ... Formula (7)
It can replace with Formula (2) and can evaluate using Formula (7).

[3] When using the void and cluster method for the dither method The following equation (8) can be used as a correction equation of the equation (3) in the case of the void and cluster method.
Image evaluation value = energy [no random error (with characteristic error)]
+ Α x {A1 x (energy [with system error (+ a1)] + energy [with system error (-a1)]) + A2 x (energy [with system error (+ a2)] + energy [with system error (-a2)] ) + ....}
+ Β × {A1 × (Strip energy [with system error (+ a1)] + Stripe energy [with system error (−a1)]) + A2 × (Strip energy [with system error (+ a2)] + Stripe energy [system error Yes (-a2)]) + ...} ... (8)
It can replace with Formula (3) and can evaluate using Formula (8).

[4] In the case of the DBS method Also in the case of the DBS method, the evaluation method similar to the example described in the above formulas (6) to (8) can be adopted when evaluating the simulation image.

[5] In the case of the evaluation formula in the automatic selection of halftone processing It has been described that one halftone processing rule is used for evaluation of image quality when the system automatically selects from two or more types of halftone processing rules. As a correction formula of the formula (4), the following formula (9) can be used.

Image quality evaluation value = p × granularity evaluation value [no random system error (with characteristic error)] + q × {A1 × {granularity evaluation value [with system error (addition of “+ a1” error to the first group)] + Graininess evaluation value [with system error (addition of "+ a1" error to the second group)] + ... + graininess evaluation value [with system error (addition of "-a1" error to the first group)] + graininess evaluation Value [with system error (addition of "-a1" error to the second group)] + ...}
+ A2 × {granularity evaluation value [with system error (addition of “+ a2” error in the first group)] + granularity evaluation value [with system error (addition of “+ a2” error to the second group)] +… + Graininess evaluation value [with system error (addition of "-a2" error to the first group)]
+ Graininess evaluation value [with system error (addition of "-a2" error to the second group)] +…} + ....}
+ R × {A1 × {Strip evaluation value [with system error (addition of “+ a1” error to the first group)]
+ Streak evaluation value [with system error (addition of "+ a1" error to the second group)] + ... + streak evaluation value [with system error (addition of "-a1" error to the first group)] + streak evaluation value [ With system error (addition of "-a1" error to the second group)] +…} +
A2 x {Strip evaluation value [with system error (addition of "+ a2" error to the first group)] + stripe evaluation value [With system error (addition of "+ a2" error to the second group)] + ... + streak evaluation Value [with system error (addition of "-a2" error to the first group)] + streak evaluation value [with system error (addition of "-a2" error to the second group)] +…} + ....}
... Formula (9)
In order to simplify the description, a case has been described in which a one-dimensional distribution is assumed as the system error distribution as shown in FIGS. 31 and 32, and the calculation formula of the image quality evaluation value is also assumed to be a one-dimensional error. However, actually, each nozzle error, head vibration error, and the like show a two-dimensional error distribution in the main scanning direction and the sub-scanning direction, as shown in FIGS.

  FIG. 33 is a diagram showing the two-dimensional error distribution in the main scanning direction and the sub-scanning direction in shades. FIG. 34 is a cross-sectional view of the error distribution along the main scanning direction in the two-dimensional error distribution shown in FIG. FIG. 35 is a cross-sectional view of the error distribution along the sub-scanning direction in the two-dimensional error distribution shown in FIG.

  For example, as shown in FIGS. 34 and 35, four levels “+ a1”, “+ a2”, “−” in the main scanning direction and the sub-scanning direction are obtained as a plurality of levels of random system errors from the system error distribution. When “a1”, “−a2”, “+ b1”, “+ b2”, “−b1”, “−b2” are defined, the image quality evaluation value Total_Value as an example is expressed by It is represented by Formula (10).

Total_Value = A1 * Val [+ a1,0] + A2 * Val [+ a2,0] + A3 * Val [-a1,0] + A4 * Val [-a2,0]
+ B1 × Val [0, + b1] + B2 × Val [0, + b2] + B3 × Val [0, -b1] + B4 × Val [0, -b2]
+ C1 x Val [+ a1, + b1] + C2 x Val [+ a1, -b1] + C3 x Val [-a1, + b1] + C4 x Val [-a1, -b1]
+ D1 × Val [+ a2, + b2] + D2 × Val [+ a2, −b2] + D3 × Val [−a2, + b2] + D4 × Val [−a2, −b2] Expression (10)
Here, the evaluation value of the simulation image to which a random system error of x in the main scanning direction and y in the sub scanning direction is added is expressed as Val [x, y]. The weighting factors A1 to A4, B1 to B4, C1 to C4, and D1 to D4 follow the system error distribution shown in FIGS. In other words, if the distribution function of the system error distribution is expressed by f (x, y),
A1 = A3 = u * f (a1,0), A2 = A4 = u * f (a2,0), B1 = B3 = u * f (0, b1), B2 = B4 = u * f (0, b2) ), C1 = C2 = C3 = C4 = u * f (a1, b1), and D1 = D2 = D3 = D4 = u * f (a2, b2). Here, u represents a positive proportionality constant.

  In the generation of the simulation image and the image quality evaluation expressed by the equations (1) to (10) described so far, the method of generating the simulation image with a system error and the image quality evaluation is a halftone image. In this embodiment, for each group of pixels belonging to each printing order, pass, and timing, a simulation image is generated by adding a predetermined system error and an evaluation value is calculated. However, a simulation image in which a predetermined system error is added to all the pixel groups belonging to each printing order, pass, and timing may be generated and image quality evaluation may be performed. In addition, each nozzle error (including misalignment for each drop type), undischarge, bi-directional misalignment (including bi-directional misalignment for each drop type), head vibration error, and paper transport error You can add the system error of each item to the halftone image independently to generate a simulation image and evaluate the image quality, or add the system error of all items to the halftone image at the same time to generate the simulation image The image quality may be evaluated. In addition, many embodiments are possible without departing from the spirit of the present invention with respect to generation of simulation images with system errors (including setting of error levels) and image quality evaluation methods.

[Configuration of Image Processing Apparatus According to Third Embodiment]
FIG. 36 is a principal block diagram for explaining functions of the image processing apparatus according to the third embodiment. 36, elements that are the same as or similar to the components described in FIG. 3 are given the same reference numerals, and descriptions thereof are omitted.

  The image processing apparatus 20 according to the third embodiment illustrated in FIG. 36 includes a system error parameter acquisition unit 53, a system error parameter storage unit 55, and a system error setting unit 67. The system error parameter acquisition unit 53 is a means for acquiring parameters relating to system errors. The system error parameter acquisition unit 53 corresponds to one form of parameter acquisition means. The system error parameter acquisition unit 53 plays the same role as the characteristic parameter acquisition unit 52 described with reference to FIG. 3, and has a role as the characteristic parameter acquisition unit 52.

  The system error parameter storage unit 55 is a unit that stores the system error parameters acquired from the system error parameter acquisition unit 53. The system error parameter storage unit 55 includes a characteristic error storage unit 55A and a random system error storage unit 55B. The characteristic error storage unit 55A is a storage unit that stores parameters of characteristic errors in the system error. The random system error storage unit 55B is a storage unit that stores a parameter of a random system error in the system error. The system error parameter storage unit 55 stores parameter data acquired in the past. The control unit 50 performs statistical processing from the distribution of the system error data group stored in the system error parameter storage unit 55, and calculates the characteristic error value corresponding to the central value of the system error distribution and the random system error. Define multiple standards.

  The system error parameter storage unit 55 serves as the characteristic parameter storage unit 54 described with reference to FIG. The system error parameter storage unit 55 corresponds to one form of storage means.

  The system error setting unit 67 is a means for setting parameters relating to system errors assumed when printing is performed by the printing system 10 (see FIG. 1). The system error setting unit 67 sets parameters as simulation conditions for generating a simulation image by the simulation image generation unit 68. The system error setting unit 67 corresponds to one form of setting means. The process in which the system error setting unit 67 sets the system error corresponds to one form of the system error setting process. Note that the function of the system error setting unit 67 may be mounted on the control unit 50.

  The simulation image generation unit 68 reflects the system error indicated by the parameter set by the system error setting unit 67 in the halftone processing result, and generates a simulation image having a higher resolution than the halftone processing result. Alternatively, once a high-resolution simulation image is generated, the simulation image is smoothed and then converted to a low resolution. The process of generating a simulation image by the simulation image generation unit 68 corresponds to one form of the simulation image generation process. The evaluation value calculation unit 70 calculates an evaluation value for evaluating the image quality of the simulation image generated by the simulation image generation unit 68. Further, the evaluation value calculation unit 70 functions as a calculation unit that calculates the weighted sum by multiplying the evaluation value of the simulation image for each level or the evaluation value of the simulation image for each level by a weighting factor.

  Further, the image processing apparatus 20 allows the user to directly input characteristic parameters regarding the characteristics of the printing system 10 using the input device 34. That is, the aspect of the characteristic parameter acquisition unit 52 in the image processing apparatus 20 may be configured such that the user directly inputs characteristic parameters related to the characteristics of the printing system 10 using the input device 34, or for characteristic parameter acquisition. The characteristic parameter may be automatically acquired from the measurement result of the chart (system error parameter acquisition chart), or a combination thereof may be used. The input device 34 corresponds to one form of information input means. The image processing apparatus 20 described with reference to FIGS. 3 and 19 can also be configured so that parameters can be directly input from the input apparatus 34.

  The image processing apparatus 20 illustrated in FIG. 36 is configured to be able to generate and evaluate the simulation image described in Expressions (6) to (9).

  The contents of the processing by the image processing apparatus 20 in each of the embodiments described above can be grasped as an image processing method.

[Specific examples of means for imparting resistance to landing interference]
Next, a specific example of a configuration for realizing halftone design or halftone processing for suppressing image quality deterioration due to landing interference will be described.

  In this specification, “Means for Compensating Image Quality Degradation Due to Impact of Landing Interference” has been outlined, and halftone parameter generation or halftone processing methods for suppressing image quality degradation due to dot movement during landing interference have been mentioned. . Here, a more detailed specific example of means for imparting resistance to landing interference will be described.

  The means for suppressing image quality degradation due to landing interference is to analyze the contact state of each dot with other adjacent dots (that is, surrounding dots) from the dot image data representing the arrangement of dots in a plurality of pixels, and the landing interference The halftone parameter is generated (that is, halftone design) or halftone processing is performed so as to give resistance against landing interference based on the evaluation result.

  Although several forms for realizing such a function are conceivable, in this specification, for each dot, the movement direction and movement amount of dot movement due to landing interference are estimated based on the contact direction and contact amount with surrounding dots. Explains the contents of the process of classifying dots according to the moving direction and moving amount, and performing halftone design or halftone processing that improves the dispersibility of dots for each group (that is, in units of groups). To do. By performing such halftone design or halftone processing, even if landing interference occurs, a halftone image with relatively small image quality degradation due to the influence can be obtained.

  In accordance with the examples of FIGS. 10, 14, and 16 already described, an example of processing for generating a halftone parameter in the dither method or error diffusion method, and a halftone parameter by a void and cluster method with respect to the dither method. Three examples of processing to be generated and halftone processing by the direct binary search method will be described.

  FIG. 37 is a flowchart relating to processing for generating halftone parameters in the dither method or error diffusion method.

  Instead of the flowchart described in FIG. 10, a flowchart shown in FIG. 37 can be employed.

  The flowchart shown in FIG. 37 is a flowchart common to both the dither method and the error diffusion method. Here, the dither method will be described as an example.

  First, halftone parameters are provisionally set (step S501). In the case of the dither method, determining each threshold value of the dither mask corresponds to determining a halftone parameter. The flowchart of FIG. 37 is repeated from the threshold value 0 to the maximum value.

  After temporarily setting halftone parameters in step S501, next, halftone processing is performed using the temporarily set halftone parameters (step S502). In the case of the dither method, step S502 corresponds to obtaining dot ON pixels from the threshold “0” to the current threshold. That is, this corresponds to obtaining a halftone image (dot arrangement) after halftone processing to which a dither mask is applied, for a single tone input image having the current threshold tone.

  Next, image quality evaluation of the halftone image generated in step S502 is performed (step S503). In the flowchart of FIG. 10, a case has been described in which a simulation image is generated using the characteristic parameters related to the characteristics of the printing system in the image quality evaluation (step S28) (step S26 of FIG. 10).

  However, in the image quality evaluation (step S503) in the flowchart shown in FIG. 37, generation of a simulation image is not an essential process. That is, the image quality of the halftone image itself generated by the halftone process in step S502 may be evaluated without simulation.

  Further, in the image quality evaluation in step S503, the simulation regarding the influence of the landing interference described in FIG. 11 is not performed even when the simulation considering the characteristic parameters of the system is performed as in the example of FIG. To do. This is because the influence of landing interference is separately evaluated in step S504 in FIG.

  The image quality evaluation in step S503 is a value obtained by applying a low-pass filter such as a Gaussian filter or a visual transfer function (VTF: Visual Transfer Function) representing human visual sensitivity to the halftone image and then integrating the result by frequency conversion, RMS This is performed by calculating at least one evaluation value among granularity (Root Mean Square granularity), an error from the input image, a standard deviation, and the like. The value calculated in the image quality evaluation step in step S503 is stored in the memory as “image quality evaluation value”.

  Next, the impact of landing interference is evaluated (step S504). Then, based on the impact interference evaluation result and the image quality evaluation evaluation result obtained in step S503, it is determined whether the halftone parameter can be updated, and the halftone parameter is updated (step S505).

  In the flowchart of FIG. 37, the process of step S504 and step S505 is significantly different from the flowchart of FIG. More detailed processing contents of steps S504 and S505 in FIG. 37 will be described later.

  In step S506 in FIG. 37, it is determined whether or not the processing from step S501 to step S505 has been repeatedly performed a predetermined number of times. The “predetermined number of times” in step S506 in the case of the dither method is the total number of pixels as threshold candidates.

  If it is determined in step S506 that the predetermined number of repetitions has not been completed, the process returns to step S501, and the processes from step S501 to step S505 are repeated. If it is determined in step S506 that the predetermined number of repetitions has been completed, the process ends.

  FIG. 38 is a flowchart showing an example of further detailed processing contents of the steps S504 and S505 in FIG.

  Steps S711 to S713 in FIG. 38 correspond to the step S504 in FIG. 37, and step S715 in FIG. 38 corresponds to the step S505 in FIG.

  As shown in FIG. 38, first, for each of a plurality of dots included in a halftone image, the movement direction and movement amount due to landing interference are calculated based on the contact direction and contact amount with surrounding dots (step S711). .

  FIG. 39 is an explanatory diagram for explaining a method of calculating a moving direction and a moving amount of dot movement due to landing interference. Each cell of the grid in FIG. 39 represents a pixel. An orthogonal coordinate system is introduced into the two-dimensional grid shown in FIG. 39, and the horizontal direction in FIG. 39 is taken as the X direction, and the vertical direction is taken as the Y direction. Here, the Y direction corresponds to the paper transport direction.

  A circle indicated by a wavy line in FIG. 39 indicates a dot spreading area. In FIG. 39, the numbers “1” to “6” shown in the cells indicate dot numbers. Each dot is described with a dot number, such as “dot 1” for the first dot, “dot 2” for the second dot, and so on.

  For each of the dots from No. 1 to No. 6 shown in FIG. 39, the movement direction and movement amount of the dot calculated based on the contact direction and the contact amount with surrounding dots that are other dots are indicated by arrows for each dot. It was. The direction indicated by the arrow indicates the moving direction of the dot, and the length of the arrow indicates the amount of movement. The moving direction and moving amount of dots due to landing interference can be handled as vectors. That is, the amount of movement of each dot due to landing interference can be represented by a vector amount having a moving direction and a magnitude of the moving amount.

  The range of surrounding dots is a range where landing interference can occur, that is, a range where adjacent dots may overlap. The larger the dot, the wider the range of surrounding dots.

  The “contact direction” can be classified into any of eight directions, for example, left direction, right direction, upward direction, downward direction, upper left direction, lower left direction, upper right direction, and lower right direction. Of course, it can be classified finer or coarser than eight directions.

The “contact amount” depends on the dot size and the distance between the dot centers. The contact amount can be simply expressed by the distance between the centers of the dots. In addition, the “contact amount” may be expressed as a distance where dots overlap on a line connecting the centers of dots, or may be expressed as an area where dots overlap. For example, in the case where D ₁ the diameter of the dot _1, the diameter of the dot 2 size X direction D _{2, 1} pixel was p _x, the distance between the centers of the dot 1 and dot 2 is p _x, dots distance are overlapped dot 1 and the line connecting the centers of the dots 2 can be expressed as _{(D 1/2) + (} D 2/2) -p x.

  By analyzing the arrangement of dots in a given halftone image, the contact direction and the amount of contact with surrounding dots can be grasped for each dot. Then, based on the information on the contact direction and the contact amount with the surrounding dots, it is possible to estimate the movement direction and the movement amount of the dot due to landing interference for each dot.

  Since the dot 1 is in contact with the dot 2 formed on the pixel adjacent to the right, the movement direction of the dot 1 due to the landing interference with the dot 2 is the right direction in FIG. 39, and the movement amount due to the landing interference is The size depends on the amount of contact. In FIG. 39, the movement vector representing the movement direction and movement amount due to the landing interference of dot 1 is indicated by Mv12. When i and j are integers indicating dot numbers, a movement vector due to landing interference between dot i and dot j is denoted as Mvij. The magnitude of the movement vector Mvij is denoted as | Mvij |. | Mvij | means the absolute value of the moving amount due to the landing interference of dot i with dot j.

  With respect to the dot 2, the landing interference with the dot 1 and the landing interference with the dot 3 are canceled out, resulting in “no moving amount”. That is, in the dot 2, the movement vector Mv21 due to the landing interference with the dot 1 and the movement vector Mv23 due to the landing interference with the dot 3 are equal in the opposite directions. Therefore, the movement vector Mv2 due to the landing interference for the dot 2 is expressed as a vector sum of the movement vector Mv21 and the movement vector Mv23 (Mv2 = Mv21 + Mv23), and the influence of the landing interference is offset, and there is no movement amount. That is, | Mv2 | = | Mv21 + Mv23 | = 0.

  Since the dot 3 is in contact with the dot 2 located on the left side of the dot 3, the movement direction of the dot 3 due to the landing interference with the dot 2 is the left direction in FIG. 39, and the movement amount is a size corresponding to the contact amount. Become. In FIG. 39, the movement vector of the dot 3 is indicated by Mv32.

  Since the dot 4 is in contact with the dot 5 located adjacent to the upper right direction, the movement direction of the dot 4 due to the landing interference with the dot 5 is the upper right direction, and the movement amount is a size corresponding to the contact amount. . In FIG. 39, the movement vector of the dot 4 is indicated by Mv45. Since the contact amount of the dot 4 with the dot 5 is smaller than the contact amount of the dot 1 with the dot 2, the movement amount | Mv45 | of the dot 4 is smaller than the movement amount | Mv12 | of the dot 1. .

The dot 5 is in contact with the dot 4 and the dot 6. For the dot 5, a movement vector Mv5 as a vector sum obtained by combining a movement vector Mv54 due to landing interference with the dot 4 adjacent in the lower left direction and a movement vector Mv56 due to landing interference with the dot 6 adjacent in the lower right direction. = Mv54 + Mv56. As shown in FIG. 39, the movement vector Mv5 of the dot 5 is the downward movement direction, and the movement amount | Mv5 | of the dot 5 is expressed as | Mv5 | = | Mv54 | × 2 ^1/2. Can do.

  Since the dot 6 is in contact with the dot 5 located adjacent to the upper left direction, the movement direction of the dot 6 due to the landing interference with the dot 5 is the upper left direction, and the movement amount is large according to the contact amount. It becomes. In FIG. 39, the movement vector of the dot 6 is indicated by Mv65.

  In this way, for each dot in the halftone image, a movement vector, that is, a movement direction and a movement amount due to landing interference with surrounding dots is obtained (step S711 in FIG. 38), and grouped based on the movement direction and the movement amount. (Step S712). There is no limitation on the direction of movement and the amount of movement for group classification. For example, the movement direction is divided into eight groups: left, right, top, bottom, top left, top right, bottom left, and bottom right, and the amount of movement is “no movement or minute movement”, “middle movement”, and “large movement”. Dividing into three groups of “movement” can be classified into 24 groups in total by combinations of movement direction and movement amount. “Minor movement”, “medium movement”, and “large movement” relating to the movement amount are classification categories in which the degree of movement amount is divided into three stages. The numerical range of the movement amount that defines each of the small movement, the middle movement, and the large movement can be set as appropriate.

  In the example of FIG. 39, the dot 2 is classified into a group of “no movement or minute movement”. Dot 3 is in the “move left” group, dot 1 is in the “move right” group, dot 5 is in the “move down” group, and dot 6 is the “move left in” group In addition, the dots 4 are classified into groups of “move to the upper right”.

  FIG. 40 is an explanatory diagram showing an example in which an error in dot formation position deviation is reflected in the dot image shown in FIG. The type of error to be reflected can be at least one error among the dot diameter, the dot shape, the dot formation position deviation, and the non-discharge, but here, in order to simplify the explanation, the dot formation is performed. An example in which an error of a dot formation position shift, which is a kind of position shift, is reflected will be described. FIG. 40 shows an example of a dot arrangement that reflects an error due to a dot formation position shift of a specific nozzle in the recording head. FIG. 40 illustrates a case where a dot formation position shift occurs for the nozzles responsible for recording dots 2 and 5.

40, the dot 2 and the dot 5 are shown with their landing positions shifted in the left direction in FIG. 40 due to the dot formation position shift. The amount of deviation between the direction of dot formation position deviation and the landing position is specified by a parameter indicating an error in dot formation position deviation. The amount of deviation of the landing position due to the dot formation position deviation is referred to as “dot formation position deviation amount”. In the example of FIG. 40, the direction of the dot formation position deviation is “−X direction”, and the amount of dot formation position deviation is ½ pixel. The dot formation position misalignment amount of the "half-pixel", in units of p _x is the size of the X-direction of one pixel, which means p x _{/ 2.}

  For each dot in the dot arrangement shown in FIG. 40, a movement amount due to landing interference is obtained based on the contact direction and the contact amount with the surrounding dots.

  The dot 1 in FIG. 40 is in contact with the dot 2 located on the right side thereof. Compared with the state before adding the error described with reference to FIG. 39 (the state without the dot formation position deviation), the landing position of the dot 2 to which the dot formation position deviation error is added is moved closer to the dot 1. Yes. Therefore, in FIG. 40, the contact amount of dot 1 with dot 2 is larger than the contact amount in FIG.

  In FIG. 40, the movement vector due to the landing interference between the dot 1 and the dot 2 is indicated by Me12. Landing interference between dot i and dot j when i and j are integers indicating dot numbers in the movement vector due to the impact of landing interference of each dot in the dot arrangement with the dot formation position error added The movement vector is expressed as Meij. The magnitude of the movement vector is denoted as | Meij |.

  The magnitude | Me12 | of the movement vector Me12 of the dot 1 shown in FIG. 40 is larger than the magnitude | Mv12 | of the movement vector Mv12 of the dot 1 described in FIG.

  40, the movement vector Me21 due to landing interference with the dot 1 and the movement vector Me23 due to landing interference with the dot 3 are in opposite directions and have a size of | Me21 |> | Me23 |. Therefore, for the dot 2, the movement vector Me21 and the movement vector Me23 are combined, and the movement vector Me2 = Me21 + Me23 is obtained as the sum of these vectors.

  The dot 3 in FIG. 40 is in contact with the dot 2 positioned on the left side of the dot 3, but the contact amount is smaller than that in the example of FIG. Therefore, with respect to the dot 3 in FIG. 40, the moving direction due to the landing interference with the dot 2 is the left direction, and the moving amount is a size corresponding to the contact amount. In FIG. 40, the movement vector of the dot 3 is indicated by Me32.

  The dot 4 in FIG. 40 is in contact with the dot 5 in which the dot formation position deviation has occurred. The contact amount between the dot 4 and the dot 5 is larger than the contact amount between the dot 4 and the dot 5 described with reference to FIG. In FIG. 40, the movement vector of the dot 4 is indicated by Me45. The magnitude | Me45 | of the movement vector Me45 of the dot 4 shown in FIG. 40 is larger than the magnitude | Mv45 | of the movement vector Mv45 of the dot 4 described in FIG.

  The dot 5 in FIG. 40 is not in contact with the dot 6 due to the deviation of the dot formation position, and is in contact with only the dot 4. Therefore, the dot 5 in FIG. 40 becomes a movement vector Me54 due to landing interference with the dot 4.

  Since the dot 6 in FIG. 40 is not in contact with other surrounding dots, the landing interference does not occur for the dot 6, and the movement amount due to the influence of the landing interference is “0”. That is, the magnitude of the movement vector Me6 due to the landing interference of the dot 6 is | Me6 | = 0, which means “no movement amount”.

  In this way, for each dot in the halftone image with a predetermined error added, a movement vector, that is, a movement direction and a movement amount due to landing interference with surrounding dots can be calculated.

  Therefore, for each dot in the halftone image after reflecting the error reflecting at least one error among the dot diameter, the dot shape, the dot formation position deviation, and the undischarge, the landing is based on the contact direction and the contact amount with the surrounding dots. A configuration may be adopted in which the movement direction and movement amount due to interference are obtained, and group classification processing is performed based on the obtained movement direction and movement amount.

  In the example shown in FIG. 40, when the movement direction of dot movement due to landing interference is divided into 8 groups and the movement amount is divided into 3 groups, and these combinations are classified into a total of 24 groups, “no movement or minute movement”. The dot 3 and the dot 6 are classified into the “movement” group. In FIG. 40, the dot 2 is moved to the “move left” group, the dot 1 is moved to the “move right” group, the dot 4 is moved to the “move right upper” group, and the dot 5 is moved “move left lower”. Are grouped into groups.

  A configuration for performing group classification processing and evaluating the dispersibility of each group may be employed only when at least one error is reflected among the dot diameter, the dot shape, the dot formation position deviation, and the discharge failure.

  Each dot group of each group classified in terms of the moving direction and moving amount of dot movement due to landing interference when reflecting at least one error among dot diameter, dot shape, dot formation position deviation, and discharge failure Halftone design or halftone processing with good dispersibility, good image quality with error added, or low image quality degradation even when error is added (that is, resistant to errors) Is possible.

  “Good dispersibility” indicates a state in which the distance between adjacent dots is uniform or a state in which the density is uniform. In this example, dot data is used as a dispersibility evaluation value serving as an index for evaluating dispersibility. RMS (Root Mean Square) granularity is calculated after multiplying by a visual transfer function (VTF) which is a function representing human visual characteristics.

RMS granularity is the square root of the root mean square of density variation and is expressed by the following equation.
SQRT (Σ (Di−D_ave) ² / (N−1))
Here, SQRT () represents a function for obtaining a square root of a numerical value designated by an argument described in (). Di represents the density of each pixel. D_ave represents the density average. N represents the number of pixels. Σ (Di−D_ave) ² represents the sum of all the pixels of (Di−D_ave) ² .

  A state where the value of the RMS granularity is small indicates that “dispersibility is good”.

  After the group classification process in step S712 of FIG. 38, the process proceeds to step S713. In step S713, a process for evaluating the dispersibility of the dots belonging to the group is performed for each classified group. As a dispersibility evaluation value serving as an index for evaluating dispersibility, in this example, as described above, the RMS granularity is calculated after applying the visual transfer function to the dot data.

  The dispersibility evaluation value can be considered as one form of the landing interference evaluation value for evaluating the influence of dot movement due to landing interference. The degree of impact of landing interference is quantified as a numerical value by the dispersibility evaluation value.

  After step S713 in FIG. 38, the process proceeds to step S715. Step S715 includes a determination process for determining whether or not halftone parameters can be updated, and an update process based on the determination result.

  In step S715, each group dispersibility evaluation value obtained for each group is compared with a specified reference value. Each group dispersibility evaluation value is equal to or less than the specified reference value, and FIG. When the image quality evaluation value obtained in step S503 is improved, a process for updating the halftone parameter is performed. Processing for comparing each of the dispersibility evaluation values of each group with a prescribed reference value corresponds to one form of “comparison processing”. Further, whether or not each of the dispersibility evaluation values of each group is equal to or less than a prescribed reference value is based on the “comparison result” by the comparison process.

  The prescribed reference value here is a value that defines an allowable upper limit of the influence of dot movement due to landing interference, and is determined in advance within a range that allows image quality degradation due to landing interference to be allowed. When each of the dispersibility evaluation values is equal to or less than a specified reference value, it means that the dispersibility is good or better than the dispersibility represented by the reference value for each group. In other words, when the dispersibility evaluation value for each group is less than or equal to the specified reference value, the impact of dot movement due to landing interference will be less than or equal to the impact of dot movement represented by the reference value. Means.

  In step S715, whether or not the halftone parameter can be updated is determined by combining the dispersibility evaluation value of each group and the image quality evaluation value obtained in step S503 of FIG.

  “Updating the halftone parameter” means that the halftone parameter is updated by adopting the halftone parameter temporarily set in step S501 of FIG.

  According to the processing described with reference to FIGS. 37 and 38, the halftone having a dot arrangement that falls within the allowable range represented by the specified reference value based on the comparison result of the comparison process between the dispersibility evaluation value and the specified reference value. Parameters can be generated.

  That is, according to the processing described with reference to FIGS. 37 and 38, even when dot movement due to landing interference occurs, the dispersibility of each dot group that moves by the same movement amount in the same movement direction is good, and due to landing interference. It is possible to generate a halftone processing rule with small image quality degradation, that is, resistance to landing interference.

  The “same moving direction” includes a range of moving directions classified into the same group and is described as “same moving direction”. The range of the moving direction corresponding to the “same moving direction” differs depending on the details of the classification when the group classification process is performed.

  “The same amount of movement” includes a range of movement amounts classified into the same group and is described as “the same amount of movement”. The range of the movement amount corresponding to “the same movement amount” varies depending on the classification details when the group classification process is performed.

  FIG. 41 is a principal block diagram for explaining functions of the image processing apparatus according to the fourth embodiment. 41, elements that are the same as or similar to the components described in FIG. 3 are given the same reference numerals, and descriptions thereof are omitted.

  The image processing apparatus 20 according to the fourth embodiment illustrated in FIG. 41 has a function of performing the processing described with reference to FIGS. That is, the image processing apparatus 20 shown in FIG. 41 includes a halftone image analysis unit 532, a dot movement amount calculation unit 534, a group classification processing unit 537, a reference value storage unit 538, and a dispersibility evaluation value calculation unit 539. A halftone processing generation unit 58, a halftone processing rule storage unit 60, a halftone processing unit 80, and a data output unit 66.

  The halftone image analysis unit 532 analyzes the data of the halftone image 550 and generates information on the contact direction and the contact amount of each dot in the halftone image 550 with surrounding dots that are other dots. The halftone image analysis unit 532 corresponds to one form of “analysis means”. The process of analyzing the contact state of dots by the halftone image analysis unit 532 and generating information on the contact direction and the contact amount indicating the contact state corresponds to one form of the “analysis process”. The processing function of the halftone image analysis unit 532 corresponds to one form of the “analysis function”.

  The halftone image 550 is a dot image generated in the process of determining the halftone parameter by the halftone processing generation unit 58. The dot image means an image showing a dot arrangement form. Halftone image 550 is generated in step S502 of FIG.

  The dot movement amount calculation unit 534 calculates the movement direction and movement amount of dot movement due to landing interference of each dot based on the information on the contact direction and contact amount of each dot with the surrounding dots obtained from the halftone image analysis unit 532. To do. The dot movement amount calculation unit 534 corresponds to one form of “movement amount calculation means”. The step of calculating the movement amount of the dot movement by the dot movement amount calculation unit 534 corresponds to one form of the movement amount calculation step. The processing function of the dot movement amount calculation unit 534 corresponds to one form of the movement amount calculation function.

  The group classification processing unit 537 performs group classification processing for classifying each dot into one or a plurality of groups based on the information indicating the movement direction and the movement amount calculated by the dot movement amount calculation unit 534. Since the movement direction and movement amount information obtained from the dot movement amount calculation unit 534 is generated based on the contact direction and contact amount information obtained from the halftone image analysis unit 532, the group classification processing unit 537 It can be understood that the group classification processing is performed based on the information on the contact direction and the contact amount obtained from the tone image analysis unit 532. The group classification processing unit 537 corresponds to one form of “group classification means”. A process of performing group classification processing in the group classification processing unit 537 corresponds to one form of “group classification process”.

  The dispersibility evaluation value calculation unit 539 calculates a dispersibility evaluation value for evaluating the dispersibility of the dot group for each group classified by the group classification processing unit 537. Also, the dispersibility evaluation value calculation unit 539 can be configured to have a function of generating another evaluation value based on the dispersibility evaluation value of each group. As the evaluation value generated based on the dispersibility evaluation value of each group, for example, the weighted sum of the dispersibility evaluation values of each group, the dispersibility evaluation value of each group, and the image quality evaluation generated in step S503 in FIG. There may be a weighted sum with the value. The dispersibility evaluation value calculation unit 539 corresponds to one form of “dispersion evaluation value calculation means”. The step of calculating the dispersibility evaluation value by the dispersibility evaluation value calculation unit 539 corresponds to one form of the “dispersibility evaluation value calculation step”.

  The reference value storage unit 538 is a storage unit that stores information on the specified reference value described in step S715 of FIG. The dispersibility evaluation value calculation unit 539 compares the calculated dispersibility evaluation value or an evaluation value generated based on the dispersibility evaluation value with a prescribed reference value, and determines the degree of influence of dot movement due to landing interference To do. The dispersibility evaluation value calculation unit 539 has a function as a landing interference influence evaluation unit that evaluates the influence of landing interference.

  The halftone processing generation unit 58 generates a halftone processing rule in cooperation with the dispersibility evaluation value calculation unit 539.

  The halftone image analysis unit 532 and the dot movement amount calculation unit 534 perform the process of step S711 in FIG. Further, the group classification processing unit 537 performs the process of step S712 in FIG. The dispersibility evaluation value calculation unit 539 performs the process of step S713 in FIG. Furthermore, the process of step S715 in FIG. 38 is performed by the dispersibility evaluation value calculation unit 539 and the halftone processing generation unit 58.

  In the case of such a configuration, the halftone processing generation unit 58 (see FIG. 41) corresponds to one form of “signal processing means”, and the halftone processing generation unit 58 generates a halftone parameter “signal processing step”. ". Further, the processing function of the halftone processing generation unit 58 corresponds to one form of a “signal processing function”.

  41 is configured to have the same configuration as the image quality evaluation processing unit 74 and the halftone selection chart generation unit 76 described in FIG. 3 in addition to the configuration specified in FIG. Can do.

<In case of error diffusion method>
The flowchart of FIG. 37 can also be applied to generation of a halftone parameter of the error diffusion method. Similar to the example described with reference to FIG. 10, the diffusion coefficient of the error diffusion matrix for each applied gradation interval is determined by repeating the flowchart of FIG. 37 for all applied gradation intervals.

  That is, for a certain gradation interval, a diffusion coefficient of an error diffusion matrix to be applied to the corresponding gradation interval is temporarily set (step S501 in FIG. 37), and an input image (single gradation) for each gradation in the gradation interval. The halftone process is performed (step S502 in FIG. 37), the image quality evaluation of the halftone image is performed (step S503), and the average value of the evaluation values for each gradation is set as the image quality evaluation value. The image quality evaluation (step S503) is performed in the same manner as in the dither method.

  In addition, the impact evaluation (step S504) and the halftone parameter update determination and update process (step S505) are performed in the same manner as in the dither method.

<When void and cluster method is applied to dither method>
FIG. 42 is a flowchart when the void-and-cluster method is used in the halftone design of the dither method. Instead of the flowchart described in FIG. 14, a flowchart shown in FIG. 42 can be employed.

  In the flowchart shown in FIG. 42, first, an initial halftone image is prepared (step S521). The method for generating the halftone initial image is the same as that in step S42 in FIG.

  Next, the process proceeds to step S522 in FIG. 42, and the filter is convoluted with respect to the halftone image. For example, a low-pass filter such as a Gaussian filter is used as the filter. In step S522, the filter may be convoluted with the halftone image itself, or the filter may be convoluted with a simulation image that takes into account characteristic parameters relating to the characteristics of the printing system. However, even when a simulation is performed in consideration of the characteristic parameters, a simulation regarding the influence of landing interference is not performed. This is because the influence of landing interference is separately evaluated in step S523 of FIG.

  Next, the impact of landing interference is evaluated (step S523). Then, the halftone image is updated based on the evaluation result of the impact effect on landing (step S524).

  More detailed processing contents of steps S523 and S524 in FIG. 42 will be described later.

  In step S525, it is determined whether or not threshold setting (that is, dot setting) has been completed for all gradations. If not completed, the process returns to step S522, and the processing from step S522 to step S524 is repeated. That is, in step S522, the filter is convoluted with the halftone image to which dots are newly added, and steps S523 and S524 are performed.

  When the processing for all the gradations is completed in step S525, the processing in FIG.

  FIG. 43 is a flowchart showing an example of further detailed processing contents of the steps S523 and S524 of FIG. In the flowchart of FIG. 43, steps that are the same as or similar to the steps of the flowchart described in FIG. 38 are assigned the same step numbers, and descriptions thereof are omitted. The flowchart in FIG. 43 includes a step S716 instead of step S715 in the flowchart described in FIG.

  Steps S711 to S713 in FIG. 43 correspond to the step S523 in FIG. 42, and step S716 in FIG. 43 corresponds to the step S524 in FIG.

  In step S716 of FIG. 43, among the pixels in which dots are not set in the halftone image, the dispersibility evaluation value of each group is equal to or less than a specified reference value, and a threshold value is set for the minimum energy pixel (that is, a void pixel). Set and set dots in the void pixels of the halftone image.

  Note that the flowchart shown in FIG. 43 is processing in a direction in which the threshold value is increased from the initial image, but the method for lowering the threshold value (that is, the gradation value) from the initial image also follows the known void and cluster method. . That is, in the energy image obtained by convolving the filter with the halftone image, among the pixels in which dots are set, the pixel having the maximum energy is regarded as a cluster pixel with dense dots, and a threshold is set, and The process of removing the dots and updating the halftone image is repeated sequentially.

<When halftone processing is performed by the direct binary search method>
FIG. 44 is a flowchart in the case of performing halftone processing by the DBS method. Instead of the flowchart described with reference to FIG. 16, a flowchart illustrated in FIG. 44 may be employed.

  In the flowchart shown in FIG. 44, first, a halftone initial image is prepared (step S531).

  The initial halftone image is generated by separately applying a dither mask that is easily generated or by a dither process according to the halftone processing rule of the dither method generated in step S14 of FIG.

  Next, a process for replacing dots in the halftone image is performed (step S532 in FIG. 44). Then, image quality evaluation is performed for each before and after dot replacement (step S533).

  As the image quality evaluation method in step S533, the same method as in step S58 in FIG. 16 can be adopted. However, in the flowchart of FIG. 16, a case has been described in which a simulation image is generated using a characteristic parameter related to the characteristics of the printing system in the image quality evaluation (step S <b> 58) (step S <b> 56 of FIG. 16).

  However, in the image quality evaluation (step S533) in the flowchart shown in FIG. 44, generation of a simulation image is not an essential process. That is, the image quality of the halftone image itself may be evaluated without simulation.

  Further, in the image quality evaluation in step S533, even when a simulation is performed in consideration of the characteristic parameters of the printing system as in the example of FIG. 16, the simulation regarding the influence of the landing interference described in FIG. 11 is not performed. And This is because the influence of landing interference is separately evaluated in step S534 of FIG.

  Next, impact influence on landing is evaluated (step S534). Then, based on the evaluation result of the impact impact impact and the evaluation result of the image quality evaluation obtained in step S533, it is determined whether or not the halftone image can be updated, and the halftone image is updated (step S535). More detailed processing contents of steps S534 and S535 in FIG. 44 will be described later.

  In accordance with the “pixel update count” set in advance, the dots are replaced a predetermined number of times, and the processing from step S532 to step S535 is repeated. That is, in step S536, it is determined whether or not the predetermined number of dot replacement processes have been completed. If the predetermined number of processes has not been completed, the process returns to step S532, and the processes from step S532 to step S535 are repeated. If it is determined in step S536 that the predetermined number of processes has been completed, the process in FIG. 44 is terminated.

  FIG. 45 is a flowchart showing an example of further detailed processing contents of the steps S534 and S535 of FIG. Steps S741 to S744 in FIG. 45 correspond to the step S534 in FIG. 44, and step S745 in FIG. 45 corresponds to the step S535 in FIG.

  In step S741 of FIG. 45, for each dot before and after dot replacement, the movement direction and movement amount due to landing interference are calculated for each dot based on the contact direction and contact amount with surrounding dots.

  Then, the groups are classified based on the movement direction and the movement amount before and after dot replacement (step S743). The method for calculating the amount of movement due to the landing interference of each dot and the method for group classification are the same as those in steps S711 and S712 in FIG. 38 and the example described in FIG.

  Next, the dispersibility of each group is evaluated (step S744 in FIG. 45). The dispersibility evaluation value of each group in the dot image before dot replacement and the dispersibility evaluation value of each group in the dot image after dot replacement are obtained.

  After step S744, the process proceeds to step S745. Step S745 includes a determination process for determining whether or not the halftone image can be updated, and an update process based on the determination result. That is, in step S745, each of the dispersibility evaluation values of each group in the dot image after dot replacement calculated by dot replacement is compared with a specified reference value, and each of the dispersibility evaluation values of each group is set to a specified reference. When the image quality evaluation value obtained in step S533 in FIG. 44 is less than or equal to the value and improved before and after the dot replacement, a process for updating the halftone image is performed.

  That is, in step S745 in FIG. 45, whether or not the halftone image can be updated is determined by combining the dispersibility evaluation value of each group after dot replacement and the image quality evaluation value obtained in step S533 in FIG.

  “Updating the halftone image” means updating the halftone image by adopting the dot arrangement state after the dot replacement performed in step S532 of FIG.

  44 and 45, even if dot movement due to landing interference occurs, the dispersibility of each dot group that moves by the same movement amount in the same movement direction is good, and image quality deterioration due to landing interference. Can be generated, that is, a halftone image having resistance to landing interference. “Good dispersibility” means that the dispersibility of the dot group is as good as or better than the dispersibility standard represented by the specified standard value.

  44 and 45, the dispersion evaluation value of each group is obtained for each group of dot groups in which the movement direction and movement amount of the dot movement due to landing interference are approximately the same, and the dispersion evaluation value is obtained. A halftone image having a dot arrangement that falls within the allowable range represented by the prescribed reference value can be generated based on the comparison result of the comparison process between the prescribed reference value and the prescribed reference value.

  The halftone processing described in FIGS. 44 and 45 can be performed in the halftone processing unit 80 shown in FIG. In this case, the halftone image 550 to be evaluated for impact impact assessment is a dot image generated in the course of processing by the halftone processing unit 80, and is the initial image described in step S531 of FIG. 44 or the step S532. It is an image after dot replacement or an updated halftone image updated in step S535. The halftone processing unit 80 that performs the halftone processing described with reference to FIGS. 44 and 45 (see FIG. 41) performs a halftone image update process by the DBS method in cooperation with the dispersibility evaluation value calculation unit 539.

  In such a configuration, the halftone processing unit 80 (see FIG. 41) corresponds to one form of “signal processing means”, and the process of generating a halftone image in the halftone processing unit 80 is the “signal processing process”. It corresponds to one form. Further, the processing function of the halftone processing unit 80 corresponds to one form of a “signal processing function”.

[Example of halftone design and / or halftone processing with error tolerance]
Next, a configuration example will be described in which image deterioration due to landing interference in the case where there is at least one error among the dot diameter, the dot shape, the dot formation position deviation, and the undischarge is described.

  FIG. 46 is a principal block diagram for explaining functions of the image processing apparatus according to the fifth embodiment. In FIG. 46, elements that are the same as or similar to those described in FIGS. 3 and 41 are given the same reference numerals, and descriptions thereof are omitted.

  The image processing apparatus 20 according to the fifth embodiment illustrated in FIG. 46 includes a parameter acquisition unit 544 and an error reflection processing unit 546 in addition to the configuration described in FIG.

  The parameter acquisition unit 544 is a means for acquiring a parameter representing at least one error among the dot diameter, the dot shape, the dot formation position deviation, and the discharge failure. In the example described with reference to FIG. 40, the parameters representing the dot formation position deviation direction and the dot formation position deviation amount related to the dot formation position deviation error are acquired. The parameter acquisition unit 544 may be configured with a user interface, may be configured with a data capturing terminal that captures parameter information held in an external storage medium or the apparatus, or a communication interface, and an appropriate combination thereof It may be.

  The error reflection processing unit 546 performs processing for generating a dot arrangement that reflects the error represented by the parameter obtained from the parameter acquisition unit 544. The error reflection processing unit 546 reflects the error represented by the parameter obtained from the parameter acquisition unit 544 to the data of the halftone image 550, and generates a dot image indicating the dot arrangement state after error reflection. In the case of the example described with reference to FIG. 40, the error reflection processing unit 546 generates dot arrangement data to which an error due to a dot formation position shift is added. The error reflection processing unit 546 corresponds to one form of “error reflection processing means”. The step of adding an error to the dots of the halftone image 550 and generating the dot arrangement reflecting the error by the error reflection processing unit 546 corresponds to one form of the error reflection processing step.

  The halftone image analysis unit 532 can analyze the contact direction and the contact amount of the halftone image after the error is reflected after the error reflection processing unit 546 adds an error to the halftone image 550.

  The halftone image analysis unit 532 includes a halftone image 550 before an error is added by the error reflection processing unit 546, and a halftone after the error is reflected after the error reflection processing unit 546 adds an error to the halftone image 550. For each of the tone images, a configuration capable of analyzing the contact direction and the contact amount may be used.

  The halftone image 550 before the error is added (that is, when the error is not reflected) is a dot image when the error is not reflected.

  With the configuration shown in FIG. 46, for each dot after reflecting an error in which at least one error among the dot diameter, the dot shape, the dot formation position deviation, and the undischarge is reflected in the halftone image 550, a dot due to landing interference is used. The movement direction and movement amount of movement can be calculated, and group classification processing can be performed according to the movement direction and movement amount. A specific group classification method is as described with reference to FIG.

  The flowchart of the process by the image processing apparatus 20 according to the fifth embodiment shown in FIG. 46 is not shown, but instead of the process in step 711 of FIG. 38 or 43, the dot diameter, the dot shape, the dot formation position shift, For each dot when at least one error is reflected in the discharge failure, the movement direction and the movement amount due to the landing interference are calculated based on the contact direction and the contact amount with the surrounding dots. Thereafter, as in the flowchart of FIG. 38 or FIG. 43, group classification processing is performed based on the movement direction and movement amount when an error is reflected (step S712), and the dispersibility of each group is evaluated (step S712). Step S713).

  In addition, regarding halftone processing by the direct binary search method, instead of step S741 in FIG. 45, dot replacement is performed when at least one error among dot diameter, dot shape, dot formation position deviation, and discharge failure is reflected. For each dot before and after dot replacement, the direction and amount of movement due to landing interference are calculated for each dot based on the direction and amount of contact with surrounding dots. Thereafter, the processing is the same as that in the flowchart of FIG. 45, and group classification processing is performed based on the moving direction and the moving amount for each of the dot replacement before and after the dot replacement when the error is reflected (step S743). The dispersibility of each group is evaluated (step S744).

  According to the configuration of the fifth embodiment, the influence of dot movement due to landing interference when reflecting a predetermined error that is at least one error among the dot diameter, the dot shape, the dot formation position deviation, and the undischarge is approximately the same. By making the dispersibility of each dot group good, the image quality is good with a predetermined error added, or the image quality is small even when a predetermined error is added (that is, it has tolerance to errors) ) Halftone design and / or halftone processing is possible.

  The group classification and evaluation of the dispersibility of each group may be configured only when a predetermined error that is at least one of the dot diameter, the dot shape, the dot formation position deviation, and the non-discharge is reflected. The group classification and the evaluation of the dispersibility for each group may be performed for each of the case where the error is not reflected and the case where the predetermined error is reflected.

  The contents of the processing by the image processing apparatus 20 in the embodiment described with reference to FIGS. 37 to 46 described above can be grasped as an image processing method.

[Modification of Specific Example Described in FIGS. 37 to 46]
<Modification 1>
In the description of FIGS. 37 to 46, the example in which the movement direction and movement amount of dot movement due to landing interference is calculated based on the information indicating the contact direction and contact amount of each dot has been described. However, it is possible to perform the group classification process directly from the contact direction and the contact amount by treating the movement amount of the dot movement due to the landing interference as being approximately proportional to the contact amount of the dot.

  For example, in the case of the dot arrangement example shown in FIG. 47, when attention is paid to the center dot, the contact direction and the contact amount with the left and right dots are indicated by arrows in FIG. The direction indicated by the arrow indicates the contact direction, and the length of the arrow indicates the contact amount. The dot arrangement shown in FIG. 47 corresponds to the arrangement form of dot 1, dot 2, and dot 3 described in FIG.

  In the contact state shown in FIG. 47, the sum of the vectors indicated by the two arrows shown in the figure is “0” without intentionally calculating the moving direction and the moving amount due to landing interference, so that the landing interference moving amount is “0”. " Even if the movement vector described with reference to FIG. 39 is not calculated, group classification processing can be performed using vectors representing the contact direction and contact amount with surrounding dots.

  Therefore, a form in which the “dot movement amount calculation unit 534” described with reference to FIGS. 41 and 46 is omitted is also possible.

<Modification 2>
When image quality evaluation is performed without simulation related to landing interference in step S503 in FIG. 37, the type of image to be subjected to image quality evaluation is the same as the type of image to be evaluated for impact impact in step S504. Is preferred. That is, whether or not to reflect the dot diameter, dot shape, dot formation position deviation, dot density, and other various errors in the image to be evaluated, and if so, the type of error to be reflected It is preferable to set the same amount for each of the image that is the object of the image quality evaluation and the image that is the object of the impact evaluation of the landing interference.

  Similarly, the type of image in which the filter is convoluted without simulation regarding landing interference in step S522 in FIG. 42 is preferably the same as the type of image for which the influence of landing interference is evaluated in step S523.

  In other words, whether or not to reflect various errors such as dot diameter, dot shape, dot formation position deviation, dot density, etc., for the image where the filter is convolved without simulation related to landing interference and the image subjected to evaluation of impact impact In addition, when reflecting, it is preferable that the type and amount of error to be reflected are the same.

  Similarly, when performing image quality evaluation without simulation regarding landing interference in step S533 of FIG. 44, the types of images to be subjected to image quality evaluation and the types of images to be evaluated for landing interference effects in step S534 are as follows. Are preferably the same.

<Modification 3>
Each of the dispersibility evaluation values of each group may be an evaluation value for evaluating the influence of landing interference, or a weighted sum of the dispersibility evaluation values of each group may be used as the evaluation value. In addition, when reflecting a predetermined error that is at least one of the dot diameter, the dot shape, the dot formation position deviation, and the non-discharge, an evaluation value that does not reflect the error is obtained without reflecting the predetermined error. ”And the“ evaluation value reflecting the error ”obtained by reflecting the predetermined error, the halftone parameter and the reference for updating the halftone image may be set, or the evaluation value and the error that do not reflect the error An update criterion may be set for the weighted sum of evaluation values that reflect the above.

<Modification 4>
Step S715 in FIG. 38, step S716 in FIG. 43, or the reference for updating the halftone image in step S524 in FIG. 42 or the update reference in halftone image in step S535 in FIG. Not only the update criteria exemplified in step S745 of FIG. 45, but also various update criteria can be defined.

  For example, as an update criterion, “when the image quality evaluation value or energy is equal to or lower than a predetermined criterion value for determination criteria and the dispersibility evaluation value of each group is improved” or “image quality evaluation value or energy The case where the weighted sum of the dispersibility evaluation value of each group is improved may be used. Further, instead of “dispersity evaluation value of each group”, it can be set as “evaluation value generated based on the dispersion evaluation value of each group”, and “image quality evaluation value or energy is When the evaluation value is less than or equal to a predetermined criterion value for evaluation and the evaluation value generated based on the dispersibility evaluation value of each group is improved ”or“ image quality evaluation value or energy and dispersibility evaluation of each group ” The case where the weighted sum of the evaluation values generated based on the values is improved ”may be used. Here, “energy” corresponds to an image evaluation value of an energy image obtained by convolving a dot image with a filter such as a Gaussian filter.

  “When the dispersibility evaluation value is improved” means that when the dispersibility evaluation value decreases, the trend of increase / decrease in the dispersibility evaluation value itself is grasped. When the property improves, it is determined that “the dispersibility evaluation value has been improved”. When judging whether or not the dispersibility evaluation value has been improved, the dispersibility evaluation value calculated from different dot images is compared to determine whether there is an increase or decrease. Includes comparison processing. The determination result of whether or not the dispersibility evaluation value has been improved is based on the “comparison result” by the comparison process.

  “Image quality evaluation value or weighted sum of energy and dispersibility evaluation value” corresponds to one form of “evaluation value generated based on dispersibility evaluation value”. The “weighted sum of image quality evaluation value or energy and dispersibility evaluation value of each group” may be a weighted sum of image quality evaluation value and dispersibility evaluation value, or a weighted sum of energy and dispersibility evaluation value. Also good.

<Modification 5>
When a predetermined error (here, an error other than non-discharge) is reflected in the dot arrangement of the halftone image, the movement direction and the amount of movement due to the landing interference of the dot group reflecting the error are mainly errors. Therefore, the group classification process may be performed only with the dot group that reflects the error. That is, in the example shown in FIG. 40, only the dot 2 and the dot 5 that reflect the error of the dot formation position deviation may be group-classified.

  The dot group that is the target of group classification processing for evaluating the influence of dot movement due to landing interference is not limited to a mode that targets all dots included in the dot image, but only a dot group that adds a predetermined error. A part of all the dots included in the dot image can be targeted.

<Modification 6>
When the dot formation position deviation is reflected as a predetermined error, the amount of movement due to landing interference largely changes in a direction parallel to the direction in which the error is added, so the movement direction of dot movement due to landing interference adds an error. Group classification processing may be performed only for dots that are parallel to the direction. In this case, the group classification process may be performed only on dots that are in contact with a direction parallel to the direction to which the error is added, that is, only dots that include dot movement only in the movement direction parallel to the direction to which the error is added.

  In the case of the example shown in FIG. 40, a dot that touches in a direction to which an error is added, that is, a dot that includes dot movement only in a moving direction parallel to the direction to which an error is added, is dot 1, dot 2, and dot 3. That is. Therefore, in the example shown in FIG. 40, group classification processing is performed only for dot 1, dot 2, and dot 3.

<Modification 7>
When the dot formation position deviation is reflected as a predetermined error, the dispersibility evaluation value is calculated only for the group to which the dot belongs in which the moving direction of the dot movement due to the landing interference is parallel to the error adding direction. be able to.

  The modified example 7 is not limited to the case of being combined with the configuration of the modified example 6 and can be applied to the case where the group classification is performed without imposing restrictions on the group classification process as in the modified example 6. it can. The dispersibility evaluation value calculation unit 539 shown in FIG. 41 or 46 can have a function of calculating the dispersibility evaluation value for only a specific group according to the modified example 7.

<System configuration variations>
Means for acquiring characteristic parameters relating to the characteristics of the printing system, that is, a device for inputting characteristic parameters by a user, a chart output control device for outputting a characteristic parameter acquisition chart, and a characteristic parameter acquisition chart according to the control Printing device for printing, further device for reading characteristic parameter acquisition chart and acquiring characteristic parameter based on analysis result of read image, device for generating two or more types of halftone processing rules, chart for halftone selection Output control device for outputting image, device for generating simulation image from halftone processing result of halftone selection chart, reading output result of halftone selection chart, and calculating image evaluation value from the chart read image Device, user half Each device, such as a device for performing an operation for selecting a processing rule, may be configured as an integrated system, or may be a function-distributed and separated system in which a plurality of systems are combined. It may be configured.

  Similarly, the configuration of the image processing apparatus 20 described in FIG. 36, FIG. 41, and FIG. 46 may also be configured as an integrated system, or may be configured as a separated system in which a plurality of systems are combined. May be.

  [Modification 1 of System Configuration] For example, a device that performs processing for obtaining characteristic parameters and a device that performs processing for generating halftone processing rules can be configured as separate devices.

  [Modification 2 of System Configuration] Also, a device that performs processing for outputting a halftone selection chart and a device for a user to perform a halftone processing selection operation can be configured as separate devices.

  [Modification 3 of System Configuration] Also, a device that performs processing for obtaining characteristic parameters and a device that performs processing for generating a halftone processing rule while retaining priority parameters may be configured as separate devices. it can.

  [Modification 4 of System Configuration] As another configuration example, an apparatus for performing processing for outputting a characteristic parameter acquisition chart, an image reading apparatus for reading the output characteristic parameter acquisition chart, and a characteristic parameter acquisition chart The apparatus for generating and acquiring the characteristic parameter from the read image and the apparatus for generating the halftone processing rule using the acquired characteristic parameter can be configured as separate apparatuses.

  In addition, for example, the output of the characteristic parameter acquisition chart or the halftone selection chart and the image reading process of the chart are performed by the printing machine manufacturer's factory or the printing company's individual local printing system, and the obtained reading After the images are sent to the development department or the server of another printing press manufacturer in a batch, the characteristic parameters are acquired and the halftone processing rules are generated by the development department or another company's system. A mode of operation in which halftone processing rules are sent back to the original individual local printing system is also possible.

<Other configuration examples>
With respect to the above-described embodiment, the following configuration can be employed.

  [Configuration Example 1] Each time a new print job is executed or during execution of a print job, the system error parameter is automatically acquired from the chart output and the read result of the chart, and based on the acquired parameter Halftone processing rules may be generated. Chart output and reading are performed for each print job and / or during a print job, and new halftone generation is performed only when the system error parameter changes beyond the specified standard or only at the changed position. It is good also as a structure to perform. In this case, if there is no change in the system error parameter (including the characteristic parameter), that is, if the change amount of the system error parameter is within the specified standard, the generation process of the halftone processing rule is omitted, and the time There is no typical loss.

  Further, chart output may be performed along with an image in front of the image to be halftone processed. In this case, time loss is reduced. Furthermore, the halftone processing and the halftone processing rule generation processing may be parallelized.

  [Configuration Example 2] Any one of chart contents, chart output conditions, scan conditions (synonymous with chart reading conditions), parameter acquisition method, and halftone processing rule generation contents according to user quality requirements Alternatively, a plurality of combinations may be changed. By adopting such a configuration, it is possible to reduce time loss required for processing.

  [Configuration Example 3] Analyzing dot reproduction accuracy from a dedicated chart for examining dot reproduction accuracy, and based on the analysis result, the contents of the parameter acquisition chart, chart output conditions, scanning conditions, parameter acquisition method, and halftone Any one or a plurality of combinations of the processing rule generation contents may be changed. By adopting such a configuration, it is possible to reduce time loss required for processing.

<Regarding a program for causing a computer to function as an image processing apparatus>
As an image processing apparatus described in the above-described embodiment, a program for causing a computer to function is a CD-ROM (Compact Disc Read-Only Memory), a magnetic disk, or other computer-readable medium (a non-transitory information storage medium as a tangible object). And the program can be provided through the information storage medium. Instead of providing the program by storing the program in such an information storage medium, it is also possible to provide the program signal as a download service using a communication network such as the Internet.

  By incorporating this program into the computer, the function of the image processing apparatus 20 can be realized in the computer. In addition, a mode in which a part or all of a program for realizing print control including the image processing function described in the present embodiment is incorporated in a host control device such as a host computer, or a central processing unit (CPU on the printing device 24 side). It is also possible to apply as an operation program.

<< About print media >>
The “printing medium” includes a printing medium, a printing medium, an image forming medium, an image receiving medium, a discharge medium, a recording paper, and the like that are called in various terms. In the practice of the present invention, the material and shape of the printing medium are not particularly limited, and include resin sheets such as continuous paper, cut paper, sealing paper, OHP (overhead projector) sheets, films, cloths, nonwoven fabrics, wiring patterns, and the like. Various sheet bodies can be used regardless of the printed board, rubber sheet, and other materials and shapes to be formed.

<< About image quality deterioration >>
“Image quality degradation” in the present specification mainly indicates the occurrence of streaks and unevenness, and the deterioration of graininess. The image quality deterioration can be caused by various factors such as ink aggregation unevenness, gloss unevenness, density, color or gloss, or banding of a combination of these, or bleeding.

<< About combinations of embodiments >>
It is possible to adopt a configuration in which the configurations described as the above-described embodiments, modified examples, or other configuration examples are appropriately combined. For example, regarding the configuration of the fourth embodiment or the configuration of the fifth embodiment, a configuration in which two or more of the configurations of the modified example 5, the modified example 6, and the modified example 7 are appropriately combined may be adopted. it can.

<Advantages of the embodiment>
The embodiment described above has the following advantages.

  (1) It is possible to generate a halftone parameter or a halftone image having resistance against landing interference. Deterioration in image quality due to landing interference can be suppressed, and generation of a halftone image capable of forming a high-quality image can be realized.

  (2) A halftone processing rule suitable for the printing system can be generated in consideration of a system error assuming actual printing by the printing system. As a result, it is possible to realize an appropriate halftone process for obtaining a good image quality, and it is possible to obtain a print image with a good image quality.

  (3) Various characteristic parameters relating to the characteristics of the printing system can be easily acquired from the read image of the characteristic parameter acquisition chart. As a result, it is possible to significantly reduce the user's work load related to the setting of the characteristic parameters, as compared with a configuration in which the user inputs all of the various characteristic parameters from the user interface. A halftone processing rule suitable for the printing system can be generated based on the characteristic parameter acquired from the characteristic parameter acquisition chart.

<Other aspects disclosed in this specification>
This specification discloses the following aspects [1] to [21].

  [1]: Setting means for setting parameters relating to system errors assumed when printing is performed by the printing system, simulation image generating means for generating simulation images reflecting the system errors indicated by the parameters, and simulation images Image quality evaluation means for evaluating the image quality of the image and halftone processing generation means for generating a halftone processing rule for defining the processing contents of the halftone processing used in the printing system based on the simulation image in which the evaluation falls within the target range And an image processing apparatus.

  The “simulation image reflecting the system error” means a simulation image generated under the condition to which the system error is added in the simulation condition setting when generating the simulation image.

  The “target range” is a predetermined range defined as an image quality target. The target range can be defined as an image quality target that can satisfy the required image quality. The target range can be defined as a condition for ensuring that the image quality is good at an acceptable level. Further, the target range can include that the evaluation value as an index for evaluating the image quality is the best.

  According to the aspect [1], it is possible to generate a halftone processing rule suitable for the printing system in consideration of a system error assuming actual printing by the printing system. As a result, it is possible to realize an appropriate halftone process for obtaining a good image quality, and it is possible to obtain a print image with a good image quality.

  [2]: In the image processing apparatus of [1], the image quality evaluation unit may be configured to calculate an image quality evaluation value of a simulation image.

  [3]: The image processing apparatus according to [1] or [2] may include a parameter acquisition unit that acquires a parameter related to a system error.

  [4]: In the image processing apparatus of [3], the parameter acquisition unit may include an information input unit for a user to input a parameter.

  [5]: Configuration in which the image processing apparatus according to [3] or [4] includes an image analysis unit that acquires a parameter by analyzing a read image of a parameter acquisition chart printed by a printing system as a parameter acquisition unit. It can be.

  [6]: In the image processing apparatus according to any one of [1] to [5], the system error may be a characteristic error that is expected to be reproducible as a characteristic of the printing system.

  “Reproducibility is expected” includes reproducibility, and that reproducibility is expected with a reasonably high probability from a statistical probability distribution. For example, the average value or median value of the distribution of measured values of system errors can be set as the “characteristic error”.

  [7]: In the image processing apparatus according to any one of [1] to [5], the system error includes a characteristic error that is expected to be reproducible as a characteristic of the printing system, and a random error that varies irregularly. The system error may be included.

  “Randomly changing” includes changing over time or depending on location. The irregularly changing error is an error having low reproducibility compared with the characteristic error, and can be grasped as a “scattering” component with respect to the characteristic error from a statistical probability distribution. It is understood that the random system error is a fluctuation component added to the characteristic error. The random system error as a variation component added to the characteristic error can have both a positive value and a negative value.

  [8]: In the image processing apparatus according to [7], a plurality of levels are determined with respect to the value of the random system error, and a simulation for each level reflecting the random system error corresponding to each of the plurality of levels by the simulation image generating means An image can be generated.

  [9]: In the image processing apparatus according to [8], the plurality of levels may be determined according to a system error distribution of the printing system.

  [10]: In the image processing apparatus according to [8] or [9], the image quality evaluation means evaluates the image quality for each simulation image for each level, and integrates the image quality evaluation for the simulation image for each level. Can be configured to calculate.

  [11]: In the image processing apparatus according to any one of [8] to [10], the image quality evaluation unit is configured to add a weighting factor to the sum of the evaluation values of the simulation image for each level or the evaluation value of the simulation image for each level. The weighting coefficient can be determined according to the system error distribution of the printing system.

  [12]: In the image processing apparatus according to any one of [1] to [11], the image processing apparatus includes a storage unit that accumulates data of parameters acquired in the past, and halftone processing based on the accumulated data A configuration may be employed in which rules are generated.

  [13]: In the image processing apparatus according to [12], the system error distribution information of the printing system may be updated based on the accumulated data.

  [14]: Printing is performed on a print medium based on the image processing apparatus according to any one of [1] to [13] and a halftone image generated through the halftone processing defined by the halftone processing rule. And a printing system.

  [15]: Setting means for setting parameters related to system errors assumed when printing is performed by the printing system, simulation image generating means for generating simulation images reflecting the system errors indicated by the parameters, and simulation images Image quality evaluation means for evaluating the image quality of the image and halftone processing generation means for generating a halftone processing rule for defining the processing contents of the halftone processing used in the printing system based on the simulation image in which the evaluation falls within the target range And a printing apparatus that prints on a print medium based on a halftone image generated through a halftone process defined by a halftone process rule.

  [16]: a setting step for setting parameters related to system errors assumed when printing is performed by the printing system, a simulation image generation step for generating simulation images reflecting the system errors indicated by the parameters, and simulation images Image quality evaluation step for evaluating the image quality of the image and a halftone processing generation step for generating a halftone processing rule for defining the processing content of the halftone processing used in the printing system based on a simulation image in which the evaluation falls within a target range And a method of generating a halftone processing rule.

  For aspect [16], the same matters as those specified in [2] to [13] can be combined as appropriate. In this case, the means responsible for the process and function specified in the image processing apparatus can be grasped as an element of the “process (step)” of the corresponding process and operation. Moreover, the generation method of the halftone processing rule according to the aspect [16] can be grasped as an invention of a method for producing a halftone processing rule. The halftone processing rule is information used for halftone processing, and can be understood as conforming to a program. Therefore, the aspect [16] can be interpreted as a production method of a halftone processing rule.

  [17]: A halftone processing rule generated by performing the halftone processing rule generation method of [16].

  According to the halftone processing rule of [17], it is possible to generate a target image with good image quality.

  [18] An image processing method for generating a halftone image by performing halftone processing defined by the halftone processing rule generated by executing the halftone processing rule generation method of [16].

  The image processing method according to the aspect [18] can be grasped as an invention of a method for producing a halftone image. The “halftone image” may be in the form of image data as information provided for print control processing, or may be in the form of a printed image printed according to the image data. Aspect [18] can be interpreted as a halftone image production method.

  [19]: A halftone image generated by performing halftone processing defined by the halftone processing rule generated by performing the method of generating a halftone processing rule of [16].

  [20]: Print on the print medium based on the halftone image generated through the halftone processing defined by the halftone processing rule generated by performing the halftone processing rule generation method of [16]. A method for producing a printed material by performing the printed material.

  According to the aspect [20], it is possible to produce a good printed matter that falls within the target image quality range.

  [21]: Setting means for setting a parameter related to a system error assumed when the computer performs printing by the printing system, and a simulation image generating means for generating a simulation image reflecting the system error indicated by the parameter; Halftone that generates halftone processing rules that define the processing content of the halftone processing used in the printing system based on the image quality evaluation means for evaluating the image quality of the simulation image and the simulation image within which the evaluation falls within the target range A program for functioning as a process generation unit.

  For the program [21], the same matters as those specified in [2] to [13] can be combined as appropriate. In this case, the means responsible for the process and function specified in the image processing apparatus can be grasped as an element of the program that realizes the corresponding process and operation means.

  According to the aspects shown in [1] to [21], an appropriate halftone processing rule is generated based on a simulation image reflecting a system error assuming actual printing. As a result, an image with good image quality can be obtained.

  The aspects shown in [1] to [21] can be appropriately combined with the first to twelfth aspects already described.

  In the embodiment of the present invention described above, the configuration requirements can be appropriately changed, added, and deleted without departing from the spirit of the present invention. The present invention is not limited to the embodiments described above, and many modifications are possible by those having ordinary knowledge in the field within the technical idea of the present invention.

  DESCRIPTION OF SYMBOLS 10 ... Printing system, 20 ... Image processing apparatus, 24 ... Printing apparatus, 26 ... Image reading apparatus, 32 ... Display apparatus, 34 ... Input device, 52 ... Characteristic parameter acquisition part, 53 ... System error parameter acquisition part, 54 ... Characteristic Parameter storage unit 55 ... System error parameter storage unit 56 ... Priority parameter holding unit 58 ... Halftone process generation unit 58A ... Previous halftone process generation unit 58B ... Halftone automatic selection unit 59 ... Judgment evaluation Value calculation unit, 60 ... halftone processing rule storage unit, 62 ... Characteristic parameter acquisition chart generation unit, 64 ... Image analysis unit, 67 ... System error setting unit, 70 ... Evaluation value calculation unit, 74 ... Image quality evaluation processing unit, 76: Halftone selection chart generation unit, 100: Chart for characteristic parameter acquisition, 101: Print medium, 102C, 102M 102Y, 102K ... single dot pattern, 104C, 104M, 104Y, 104K ... first continuous dot pattern, 106C, 106M, 106Y, 106K ... second continuous dot pattern, 150 ... halftone selection chart, 151, 152 ... primary color patch, 200 ... chart for characteristic parameter acquisition, 201 ... print medium, 202C, 202M, 202Y, 202K ... single dot pattern, 204C, 204M, 204Y, 204K ... first continuous dot pattern, 206C, 206M , 206Y, 206K, second continuous dot pattern, 532, halftone image analysis unit, 534, dot movement amount calculation unit, 537, group classification processing unit, 538, reference value storage unit, 539, dispersion evaluation value calculation unit. 546 ... Error reflection processing unit

Claims (12)

Analyzing means for analyzing the contact state with other dots for each dot of a plurality of pixels recorded by the inkjet printing system,
Group classification means for performing group classification processing for classifying the dots into a plurality of groups based on the information indicating the contact state obtained by the analysis means;
A dispersibility evaluation value calculating means for calculating a dispersibility evaluation value for evaluating the dispersibility of the dot group for each of the classified groups;
Using the dispersibility evaluation value calculated by the dispersibility evaluation value calculating means, or using the evaluation value generated based on the dispersibility evaluation value calculated by the dispersibility evaluation value calculating means, half Signal processing means for performing at least one of a process for generating a halftone parameter of a tone processing rule and a process for generating a halftone image;
An image processing apparatus comprising:   The signal processing means is the half having resistance to dot movement due to landing interference based on the dispersion evaluation value or a result of comparison processing using the evaluation value generated based on the dispersion evaluation value. The image processing apparatus according to claim 1, wherein at least one of a tone parameter and the halftone image is generated. The comparison process includes a process of comparing the dispersibility evaluation value and a specified reference value, or a process of comparing the evaluation value generated based on the dispersibility evaluation value and a specified reference value,
The signal processing means is configured to generate the halftone parameter having a dot arrangement that falls within an allowable range represented by the specified reference value based on the comparison result of the comparison process, and the specified reference value. The image processing apparatus according to claim 2, wherein at least one of the processes for generating the halftone image having a dot arrangement that falls within an allowable range is generated.   The signal processing means compares the dispersibility evaluation value with a prescribed reference value, thereby improving the dot group dispersibility to be equal to or better than the dispersibility standard represented by the reference value. The image processing apparatus according to claim 2, wherein at least one of a tone parameter and the halftone image is generated. Based on the information indicating the contact state obtained by the analyzing means, the moving amount calculating means for calculating the moving direction and the moving amount of the dot movement due to landing interference,
5. The image processing apparatus according to claim 1, wherein the group classification unit performs the group classification process based on information indicating the movement direction and the movement amount obtained by the movement amount calculation unit. 6. . An error reflection processing means for generating the dot arrangement reflecting at least one error among the dot diameter, the dot shape, the dot formation position deviation, and the undischarge, which are error elements in the inkjet printing system;
The image processing apparatus according to claim 1, wherein the group classification unit performs the group classification processing based on information indicating the contact state of the dots reflecting the error.   The image processing apparatus according to claim 6, wherein the group classification unit performs the group classification process using only a dot group that reflects the error.   When the dot formation position deviation is reflected as the error, the group classification unit performs the group classification process only for dots in which the movement direction of dot movement due to landing interference is parallel to the direction in which the error is added. The image processing apparatus according to claim 6 or 7, which is performed.   In the case where the dot formation position deviation is reflected as the error, the dispersibility evaluation value calculating means only applies the group to which the dot to which the moving direction of dot movement due to landing interference belongs is parallel to the direction in which the error is added. The image processing apparatus according to claim 6, wherein the dispersibility evaluation value is calculated for. An image processing device according to any one of claims 1 to 9,
An inkjet printing apparatus that performs printing on a print medium based on a halftone image generated through halftone processing defined by the halftone processing rule, or a halftone image generated by the signal processing unit;
An inkjet printing system comprising: For each dot of a plurality of pixels to be recorded by the inkjet printing system, an analysis process for analyzing the contact state with other dots,
Based on the information indicating the contact state obtained by the analysis step, a group classification step for performing group classification processing to classify the dots into a plurality of groups,
A dispersibility evaluation value calculating step for calculating a dispersibility evaluation value for evaluating the dispersibility of the dot group for each of the classified groups;
Using the dispersibility evaluation value calculated by the dispersibility evaluation value calculation step, or using the evaluation value generated based on the dispersibility evaluation value calculated by the dispersibility evaluation value calculation step, the half A signal processing step for performing at least one of a process for generating a halftone parameter of a tone processing rule and a process for generating a halftone image;
An image processing method including: Computer
Analyzing means for analyzing the contact state with other dots for each dot of a plurality of pixels recorded by the inkjet printing system,
Group classification means for performing group classification processing for classifying the dots into a plurality of groups based on the information indicating the contact state obtained by the analysis means;
A dispersibility evaluation value calculating means for calculating a dispersibility evaluation value for evaluating the dispersibility of the dot group for each of the classified groups;
Using the dispersibility evaluation value calculated by the dispersibility evaluation value calculating means, or using the evaluation value generated based on the dispersibility evaluation value calculated by the dispersibility evaluation value calculating means, half A program that functions as a signal processing unit that performs at least one of processing for generating a halftone parameter of a tone processing rule and processing for generating a halftone image.