NL2016503B1 - Image processing apparatus, image processing method, and image simulation method - Google Patents

Abstract

An image to be printed on a print medium (P) is preferably simulated in order to estimate feathering. Printing is performed so as to suppress the feathering from being conspicuous when a plurality of types of inks corresponding to different dot sizes are used. In order to estimate the feathering, an image is simulated based on deviations of dot measurement values. Furthermore, print data corresponding to the plurality of types of inks is generated so that rates of use of the plurality of types of inks are different from one another according to an ink bleeding to the print medium (P).

Description

Title: IMAGE PROCESSING APPARATUS, IMAGE PROCESSING

METHOD, AND IMAGE SIMULATION METHOD BACKGROUND OF THE INVENTION Field of the Invention

The present invention relates to an image processing apparatus, an image processing method, and an image simulation method.

Description of the Related Art

Japanese Patent Laid-Open No. 2014-112802 discloses a method to simulate an image printed by applying ink to a print medium. Specifically, a dot pattern is printed and image information resulting from the printing is stored in a storage medium. Then, based on the stored image information, a simulation image is generated.

Ink applied to a print medium causes variously-distorted dots due to the difference in ink bleeding. Such a phenomenon is called as a feathering. The feathering is different depending on the material of fibers used for a paper as a print medium, how fibers are tangled with one another by a paper making method, or the type of processing agent used in a paper manufacturing step for example.

Japanese Patent Laid-Open No. 2014-112802 does not disclose the consideration of such feathering.

SUMMARY OF THE INVENTION

The present invention efficiently simulates an image printed on a print medium in consideration of the feathering different depending on the type of a print medium.

The present invention generates, based on the simulation result, print data so that printing is favorably performed regardless of the type of a print medium. More specifically, the present invention prints, when a plurality of types of inks having different dot sizes are applied, an image using the plurality of types of inks with a rate of use so that the feathering is not conspicuous regardless of the type of a print medium.

In the first aspect of the present invention, there is provided an image processing apparatus, comprising: an acquisition unit (31) configured to acquire image data corresponding to an image to be printed on a print medium (P); and a generation unit (36) configured to generate print data for ejecting a plurality of types of inks corresponding to different dot sizes, by quantizing the image data, wherein: the generation unit (36) generates the print data so that rates of use of the respective plurality of types of inks are different from one another depending on an ink bleeding to the print medium (P).

In the second aspect of the present invention, there is provided an image processing method, comprising: an acquisition step of acquiring image data corresponding to an image to be printed on a print medium; and a generation step of quantizing the image data to thereby generate print data for ejecting a plurality of types of inks corresponding to different dot sizes; wherein: the generation step generates the print data so that rates of use of the respective plurality of types of inks are different from one another depending on an ink bleeding to the print medium.

In the third aspect of the present invention, there is provided an image simulation method for simulating an image printed on a print medium (P) by ink dots, comprising: an acquisition step (S41, S42, S43) of acquiring measurement values regarding a plurality of dots formed in a predetermined region of the print medium (P); a calculation step (S44) of calculating deviations of the measurement values of the plurality of dots; and an output step (S45) of outputting a simulation image based on the deviations calculated in the calculation step.

According to the present invention, an image to be printed on a print medium in order to estimate the feathering can be simulated preferably. Furthermore, according to the present invention, printing can be carried out so that the feathering is not conspicuous when a plurality of types of inks having different dot sizes are used.

Further features of the present invention will become apparent from the following description of exemplary embodiments (with reference to the attached drawings).

BRIEF DESCRIPTION OF THE DRAWINGS

Fig. 1 is a schematic view illustrating the configuration of an ink jet printing apparatus in the first embodiment of the present invention;

Figs. 2A and 2B are views for explaining a print head in Fig. 1;

Figs. 3A and 3B are views for explaining a control unit in Fig. 1;

Fig. 4 is a flowchart for explaining a quantizing processing in this embodiment;

Fig. 5 is a view for explaining a mixing rate table in this embodiment;

Figs. 6A to 6C are views for explaining dither tables in this embodiment;

Figs. 7A to 7C are views for explaining a quantizing processing according to the dither tables of Figs. 6A to 6C;

Figs. 8A and 8B are flowcharts for explaining a dot mixing rate processing in this embodiment;

Fig. 9 is a view for explaining a dot mixing ratio table;

Fig. 10 is a flowchart for explaining a simulation in this embodiment;

Fig. 11 is a view for explaining an example of landing variation data in this embodiment;

Fig. 12 is a view for explaining a dot arrangement example in the simulation;

Fig. 13 is a view for explaining an example of a simulation image;

Figs. 14A and 14B are views for explaining simulation images having different dot mixing rates;

Fig. 15 is a view for explaining featherings in different print media;

Figs. 16A and 16B are views for explaining parameters and measurement patterns;

Fig. 17 is a view for explaining actual measurement data for the respective nozzles;

Figs. 18A to 18D are views for explaining the relation between fluctuation parameters and the feathering;

Fig. 19 is a view for explaining simulation results;

Fig. 20 is a view for explaining a correlation between X fluctuation and stripe evaluation values;

Fig. 21 is a view for explaining a correlation between Y fluctuation and stripe evaluation values;

Figs. 22A to 22C are views for explaining dot mixing rates optimized in different print media;

Figs. 23A to 23C are views for explaining dot mixing rates optimized in different print media;

Fig. 24 is a flowchart for explaining a simulation in the third embodiment of the present invention;

Fig. 25 is a view for explaining a simulation system for carrying out the simulation of Fig. 24;

Fig. 26 is a view for explaining actual measurement data for the respective nozzles in the fourth embodiment of the present invention;

Fig. 27 is a view for explaining a correlation between gravity center moments and stripe evaluation values; and

Fig. 28 is a view for explaining method of preparing a dither table. DESCRIPTION OF THE EMBODIMENTS

The following section will describe an embodiment of the present invention based on the drawings. (First embodiment) A printing apparatus in this embodiment is an application example as an ink jet printing apparatus in which an ink jet printing head that can eject ink as liquid is used to apply ink to a print medium to thereby print an image. <Apparatus configuration>

Fig. 1 is a perspective view illustrating the main part for explaining the configuration example of an inkjet printing apparatus (image printing apparatus) 1 of this embodiment.

The printing apparatus 1 of this example is a so-called full line-type printing apparatus that prints an image using an ink jet printing head 2 having a length corresponding to the width of a print medium P. As the print head 2, a plurality of print heads corresponding to a plurality of ink colors are provided. Specifically, a print head 2Y for ejecting yellow ink, a print head 2M for ejecting magenta ink, a print head 2C for ejecting cyan ink, and a print head 2Bk for ejecting black ink are provided. These print heads 2 (2Y, 2M, 2C, and 2Bk) extend in a direction (direction of the arrow Y) orthogonal to a direction along which the print medium P is conveyed (direction of the arrow X). The print head 2 (2Y, 2M, 2C, and 2Bk) is connected by a connection pipe 4 to the ink tank 3 (3Y, 3M, 3C, and 3Bk) for storing ink corresponding to the respective inks. The ink tanks 3Y, 3M, 3C, and 3Bk can be attached and detached in an independent manner. The print head 2 is positioned so that a conveying belt 5 is sandwiched between the print head 2 and a platen 6 provided. The print head 2 is raised or lowered by a head moving unit 10 in a direction so as to be opposed to the platen 6. The head moving unit 10 is controlled by a control unit 9.

The print head 2 includes a plurality of ejection openings for ejecting ink, a common ink chamber for receiving ink supplied from the ink tank 3, and an ink flow path for guiding the ink in this common ink chamber to the respective ejection openings. In this example, a piezo element is provided as an ejection energy generating element to eject ink through the ejection opening. The piezo element is electrically connected to the control unit 9 via a head driver 2a and is controlled to be deformed depending on an ON/OFF signal (ejection /no-ejection signal) sent from the control unit 9. The ejection energy generating element is not limited to the piezo element and also may be an electrothermal conversion element (heater), an electrostatic element, or an MEMS element for example.

Fig. 2A is a bottom view illustrating the print head 2 seen in a direction of the ejection opening. The print head 2 of this example is configured so that four trapezoidal ejection opening units 20 are arranged in a longitudinal direction and each of these units 20 constitutes an actuator unit including the piezo elements (piezoelectric actuator unit). These trapezoidal units 20 have oblique sides partially overlapped to one another in the short direction of the print head 2. Fig. 2B illustrates the ejection opening array in one unit 20. In the case of this example, the ejection openings 200 close to each other in the longitudinal direction have therebetween an interval P corresponding to 600dpi. Each unit includes 2558 ejection openings 200. The print head 2 of this example can use the piezo element as an ejection energy generating element to eject a different amount of ink through one ejection opening 200 so that a large, medium, or small dot having a different size is formed.

In Fig. 1, at a position dislocated from the print head 2 by a half pitch of the arrangement interval of the print head 2, a cap 7 for carrying out the recovery processing of the print head 2 is provided. A cap moving unit 8 is controlled by the control unit 9. By moving the cap 7 to a position just below the print head 2, waste ink discharged through the ejection opening is received by the cap 7. In order to convey the print medium P, the conveying belt 5 is wound around a drive roller connected to a belt drive motor 11. The conveying belt 5 is controlled by the control unit 9 via a motor driver 12. An electrical charging device 13 provided at the upstream of the conveying belt 5 causes the conveying belt 5 to be electrical-charged to thereby cause the conveying belt 5 to contact with the print medium P. The energization of the electrical charging device 13 is turned ON or OFF by the control unit 9 via an electrical charging device driver 13a. A pair of feeding rollers 14 for supplying the print medium P onto the conveying belt 5 is driven to rotate by a feeding motor 15. The feeding motor 15 is controlled by the control unit 9 via a motor driver 16.

The printing apparatus 1 of the present invention is not limited to such a full line-type printing apparatus and may be a serial scan-type one for example. When the printing apparatus 1 is the serial scan-type one, then the printing apparatus 1 prints an image by repeating an operation to allow a print head to eject ink while moving in a main scanning direction and an operation to convey a print medium in a sub scanning direction. The printing apparatus 1 may have any configuration so long as the printing apparatus 1 is configured to print an image by the relative movement of the print head and the print medium.

Fig. 3A illustrates the configuration example of the control unit 9. The control unit 9 includes a data input unit 31, a display operation unit 32, a CPU 33, a storage unit 34, a RAM 35, an image processing unit 36, and a print head control unit 37.

The data input unit 31 inputs multivalued image data through an image input device (e.g., a digital camera, a personal computer). The RAM 35 is used as a work area during the execution of various programs by the CPU 33 and temporarily stores various calculation results or image processing results for example. The display operation unit 32 includes an operation unit (e.g., a touch panel, a button) to input an instruction from a user (e.g., a parameter setting instruction, a print start instruction) into the apparatus and a display unit (e.g., a touch panel, a display) to display various pieces of information to the user. The CPU 33 controls the operation of the entire apparatus in an integrated manner. For example, the CPU 33 controls the operations of the respective units of the apparatus based on the program stored in the storage unit 34. The storage unit 34 stores therein various pieces of data. For example, the storage unit 34 stores therein information regarding the type of a print medium, information regarding ink, information related to an environment such as a temperature or humidity, information regarding the correction of a landing position (registration adjustment information), information regarding the print head 2, various control programs, and a three-dimensional LUT (lookup table) for example.

The image processing unit 36 performs an image processing on the multivalued image data inputted from the data input unit 31. For example, the image processing unit 36 quantizes the respective pixels of the multivalued image data into N value image data to allocate a dot arrangement pattern corresponding to the gradation value "K" shown by the respective quantized pixels. More specifically, the image processing unit 36 converts the gradation values of the multivalued image data represented by 256 gradations to K values. Such a processing can use an arbitrary method such as a multivalued error diffusion method, an average density save method, or a dither matrix method. As a result, the image processing unit 36 generates print data corresponding to the respective ejection openings. During the generation of the print data, based on the registration adjustment information stored in the storage unit 34, positions at which ink lands on the print medium are adjusted. The print head control unit 37 controls the printing operation by the print head 2.

The control unit 9 is not limited to the configuration as described above. For example, another configuration also may be realized in which a part of these configurations is substituted by the use of the RAM 35 as a work region by the CPU 33 and a program stored in the storage unit 34 is executed. Alternatively, another hardware configuration such as an exclusive circuit also may be used.

Fig. 3B is a flowchart for explaining a print data generation processing by the image processing unit 36. A user can use the data input unit 31 and the display operation unit 32 to prepare image data to be printed by the printing apparatus 1. During the printing, the image data inputted from the data input unit 31 is transferred to the image processing unit 36. The image processing unit 36 executes a precedent processing Si, a subsequent processing S2, a γ correction S3, a quantizing processing S4, and a print data preparation processing S5.

In the precedent processing Si, the color gamut to be displayed on the monitor of the display operation unit 32 is converted to the color gamut of the image to be printed by the printing apparatus 1 (color gamut conversion). Specifically, for example, the three-dimensional LUT stored in the storage unit 34 is referred to thereby convert image data R,G,B represented by 8-bit to 8-bit data R, G, and B in the color gamut of the printing apparatus 1. Next, in the subsequent processing S2, a signal value is converted so that the 8-bit data R, G, and B obtained through the precedent processing Si is represented by four color inks (C, Μ, Y, and K). Specifically, the three-dimensional LUT stored in the storage unit 34 is referred to thereby convert the 8-bit data R, G, and B obtained through the precedent processing Si to 8-bit C, Μ, Y, and K data corresponding to the four inks.

Next, in the γ correction S3, the C, Μ, Y, and K data obtained through the subsequent processing S2 is subjected to a γ correction. Specifically, a primary conversion is performed so that the 8-bit data C, M, Y, and K obtained through the color separation is linearly associated with the gradation characteristic of the printing apparatus. In the next quantizing processing S4, the 8-bit data C, Μ, Y, and K subjected to the γ correction is converted to 2-bit data C, Μ, Y, and K based on a predetermined quantizing processing method.

In the print data preparation processing S5, print data is prepared by adding, to the 2-bit data of the respective ink colors generated by the quantizing processing S4, print medium information, printing quality information, and control information related to a print operation such as a paper feed method stored in the storage unit 34. The print data thus generated is supplied from the print head control unit 37 to the printing apparatus 1.

Next, the following section will describe the quantizing processing S4. The quantizing is a processing to convert the gradation values of the original image data (256 gradations in this embodiment) to gradation values that can be represented by the printing apparatus 1 for the respective pixels. In this embodiment, as described later, the gradation values are converted to four gradation values corresponding to "no dot formation", "small dot formation", "medium dot formation", and "large dot formation". However, the conversion to more gradation values also may be carried out. The quantizing method in this embodiment is a method using a dither table but an error diffusion method also may be used.

Fig. 4 is a flowchart for explaining the quantizing processing in this embodiment. In this embodiment, a 256x256 pixel-size dither table is repeatedly used in longitudinal and lateral directions to perform the quantizing processing. In order to realize a brief description, the quantizing processing in this embodiment will be described using a table having a smaller size.

First, 8-bit image data is inputted (Step Sll). The image data is the 8-bit data C, Μ, Y, and K processed in the γ correction S3 that corresponds to 256 gradations, respectively. Next, the dot ON/OFF (formation/no formation) is determined using a dither table in which threshold values are set for the respective pixels. The dither table is set with regard to the respective plurality of dots having different sizes and is stored in the storage unit 34. In the case of this example, as shown in Fig. 5, large dots, medium dots, and small dots are formed as a plurality of types of dots having different sizes and a dither table corresponding to them is set as shown in Figs. 6A, 6B and 6C.

In the dot ON/OFF determination, a large dot dither table (Fig. 6A) is firstly used to compare the gradation value LV of pixels of the input image with the threshold value LTH of the position of the large dot dither table corresponding to the pixels (Step S12). When the gradation value LV is equal to or higher than the threshold value LTH, it is determined that the large dot is ON (formation) (Step S15A). When the gradation value LV is lower than the threshold value LTH, the processing proceeds to Step S13.

In Step 13, the medium dot dither table (Fig. 6B) is used to compare the gradation value LV of the pixels of the input image with threshold value MTH of the position of the medium dot dither table corresponding to the pixels. When the gradation value LV is equal to or higher than the threshold value MTH, it is determined that the medium dot is ON (formation) (Step S15B). When the gradation value LV is lower than the threshold value MTH, the processing proceeds to Step S14. In Step 14, the small dot dither table (Fig. 6C) is used to compare the gradation value LV of the pixels of the input image with the threshold value STH of the position of the small dot dither table corresponding to the pixels. When the gradation value LV is equal to or higher than the threshold value STH, it is determined that the small dot is ON (formation) (Step S15C). When the gradation value LV is lower than the threshold value STH, no dot formation is determined (Step S15D).

By subjecting all pixels of the inputted image data to the determination processing as described above, image data is prepared that is obtained by being converted, with regard to the respective pixels, to have the four values corresponding to "large dot ON", "medium dot ON", "small dot ON", and "no dot". The 4-valued image data is 2-bit information that is used, with regard to the individual pixels corresponding to the print resolution of the printing apparatus 1, to form any of the large, medium, or small dots or not to form any of these dots. In the quantizing processing of this embodiment, instead of the 4-valued 2-bit processing as described above, a further higher bit number and quantizing processing also may be performed.

In the dither tables of Figs. 6A, 6B, and 6C, threshold values of 1 to 255 are set. Actually, the dither tables are a 16x16 size dither table. However, in order to provide a brief description, an 8x8 size matrix table is used. These dither tables are a table reflecting large dot, medium dot, and small dot mixing rates as shown in Fig. 5 as described above. The mixing rate (dot mixing rate) means a ratio of dots that are formed, in order to print a solid region having a certain gradation, within the solid region when compared to the pixels within the solid region. For example, when the image data having the gradation value 128 is inputted in an 8x8 pixel solid region, it is assumed that the mixing rate in the mixing rate table of Fig. 5 has large dots of 23%, medium dots of 34%, and small dots of 11%. The dither table reflects such a mixing rate table. Specifically, with regard to all pixels within the 8x8 pixel solid region, the threshold values of the dither tables of Figs. 6A, 6B, and 6C are consequently set so that large dots, medium dots, and small dots formed within the region occupy the region at ratios of 23%, 34%, and 11%, respectively.

In Figs. 7A, 7B, and 7C, black-painted pixels are pixels that are turned ON when the image data having the gradation value 128 is inputted to the dither tables of Figs. 6A, 6B, and 6C. A ratio at which the ON dots occupy all 8x8 of 64 pixels is a mixing rate. The print head 2 can form only dots of one size to one pixel at a certain gradation. Thus, among pixels having the same threshold value in the large dot, medium dot, and small dot dither tables, relatively-large dots are formed in a prioritized manner.

Thus, with regard to pixels in Figs. 7B and 7C that have a threshold value lower than that of the gradation value 128, dots having the sizes corresponding to their dither tables are not formed and dots having a size larger than them are formed in a prioritized manner.

In the dither-based quantizing processing for handling dots having a plurality of sizes as described above, the dot formation method is limited when gradation values are increased. Specifically, pixels for which dots having any size are ON cannot be changed unless dots having a larger size than that of the dots are turned ON. Thus, the threshold values of the dither table for relatively-small size dots are not higher than the threshold values of the dither table for relatively-large size dots. Thus, a dither table corresponding to dots having a plurality of sizes is prepared in order to satisfy such a limitation and to realize the mixing rates in the mixing rate table as shown in Fig. 5 at all gradations.

The following section will describe the preparation method of the dither table of a plurality of dots used in this embodiment with reference to Fig. 28. First, one table is prepared that describes the mixing rates of a plurality of dots determined for the respective gradations in advance and the values of matrix elements, and that is equal to a dither table used for printing. In this description, in order to provide easy-to-understand explanation, among the tables in Fig. 28, the table 1901 on a 3x3 matrix has the maximum gradation value of 7. Then, dots are arranged based on one gradation in an order from a smaller numerical value of the table 1901. An example of the arrangement is arrangement states 1903, 1904, and 1905. The arrangement state 1903 shows a case where the gradation value is 1.

The arrangement state 1904 shows a case where the gradation value is 2.

The arrangement state 1905 shows a case where the gradation value is 4.

Then, a value obtained by deducting 1 from the first gradation value at which these dots are arranged is a threshold value thereof. For example, in the case of the gradation value of 4 of the table 1902, there are 1 small dot, 4 medium dots, and 1 large dot. The large dots are arranged at a position having the smallest number in the 3x3 table after which the medium dots and small dot are arranged. In this case, since the large dots are firstly placed at the upper-left position in this gradation, the upper-left position of the dither table of the large dots has a threshold value of 3. In this manner, the threshold values of a plurality of dots are determined. The tables 1906, 1907, and 1908 are a dither table of a plurality of dots obtained based on this mixing rate and the table 1901. The threshold values are desirably arranged to form a blue noise pattern. According to this, to-be-printed dots can be arranged in a dispersed manner. This embodiment has been described, in order to provide easy-to-understand explanation, so that dots are arranged. However, it is not always required to arrange dots. Thus, a processing substituting the arrangement may be carried out by a computer program. Furthermore, the method of arranging a plurality of dots described in this embodiment is an example and the invention is not limited to this. <Processing to select a dot mixing rate>

Next, the following section will describe a method of selecting the mixing rates of dots having a plurality of sizes. In this embodiment, large, medium, and small dots of three sizes are used. Ink for forming these dots is ejected in amounts of 5pl, 7pl, and 12pl, respectively. The following description will be described based on an assumption that ink of a single color is used as an example. However, by performing a similar processing on various inks such as cyan, magenta, yellow, and black inks and a light-color ink having a low density, the mixing rate of these dots can be calculated. <Flow of the selection processing>

Fig. 8A is a flowchart for explaining a processing to select the mixing rates for all gradations.

First, from among all 256 gradations of gradations 0 to 255, gradations of a predetermined number N are set discretely (Step S21).

When the predetermined number N is high in order to set more gradations discretely, a selection processing (which will be described later) is frequently performed to thereby provide a higher quality. However, this consequently causes a proportionally-increased processing time. Thus, the number is desirably set to about 10 for a practical case. All gradations are not limited to 256 gradations.

Next, as image data corresponding to the respective N gradations, image data having a plurality of different mixing rates is generated to print or simulate images corresponding to the respective pieces of image data to determine the ranking of these images based on the image evaluation value (evaluation result) (Step S22). The processing for the respective gradations will be described later. This processing provides the ranking of the mixing rates that provides a favorable result to the granularity and stripe included in the quality evaluation (which will be described later). Next, with regard to the respective N gradations, the mixing rates are selected in an order from a higher quality evaluation value in such a manner that the mixing rates are smoothly continuous at all gradations in consideration of the gradation conditions for example (Step S23). Based on the mixing rates among N gradations, the mixing rates of other gradations are calculated based on linear interpolation to subsequently calculate mixing rates continuous in all gradations. A method of complementing the mixing rated among the N gradations is not limited to the linear interpolation and thus a spline interpolation method for example also may be used. Thereafter, the mixing rates at all gradations are stored in the storage unit 34 of Fig. 3A and is reflected on a dither table used in the quantizing processing of Fig. 3B described above (Step S4). Specifically, the dither table used in the quantizing processing of Fig. 3B (Step S4) is prepared so as to realize the mixing rate at all gradations calculated in Step S23 of Fig. 8A. As described above, the image data is converted to have 4 values based on this dither table. <Flow of the processing for the respective gradations>

Fig. 8B is a flowchart for explaining the processing of Step S22, i.e., a processing to determine an order of the mixing rates at the respective gradations based on image evaluation values.

In Step 31, for the respective N gradations, as image data corresponding to the respective gradations, image data is determined that has different mixing rates of large, medium, and small dots (Step S31). Specifically, firstly, for the respective gradations, combinations of the printing ratios of the large, medium, and small dot are set. In this embodiment, the printing ratios of the large, medium, and small dots are changed from 0% to 100% in an increment of 10%. In this embodiment, large, medium, and small dots cannot be formed in an overlapped manner. Thus, the sum of the printing ratios of the large, medium, and small dots does not exceed 100%. Therefore, when the sum of the printing ratios is 100% and a small dot printing ratio is 10% for example, the remaining 90% (100-10=90(%)) means the printing ratio of medium and small dots. As described above, the respective printing ratios of the large, medium, and small dots are changed from 0% to 100% in an increment of 10%. Then, as shown in Fig. 9, the mixing rates are set so that the respective printing ratios of the large, medium, and small dots are changed from 0%, 0%, and 0%, respectively, to 100%, 0%, and 0%, respectively. When ll(k) printing ratios of 0, 10, 20, · · ·, 90, and 100 are used, the number of the combinations of the printing ratios of the large, medium, and small dots is calculated as B((k+1) xk/2). In this embodiment, the printing ratio is changed by a variation width of 10%. However, the variation width is desirably minimized in order to provide a favorable quality. However, the reduction in the variation width causes a proportional increase of the processing time required for the simulation. Thus, the variation width is desirably set to about a few percent.

Next, for the respective N gradations, the combinations of the printing ratios of large, medium, and small dots for printing an image having densities corresponding to these gradations (hereinafter referred to as a "target density") are selected from Fig. 9. Specifically, in consideration of the ink volumes of the large, medium, and small dots for example, a plurality of mixing rates are selected from the mixing rates of Fig. 9 as mixing rates corresponding to the respective N gradations. Then, based on the image data corresponding to these mixing rates, images are printed or simulated. From among these images, a plurality of images are selected that have densities corresponding to the respective N gradations. Then, image data corresponding to the selected images is selected as a candidate of image data for the respective gradations. Alternatively, two images having densities corresponding to the respective N gradations may be selected to calculate, from among image data corresponding to them, candidates of image data of the respective gradations based on a complementary method.

This description has an objective of calculating the candidates of the mixing rates corresponding to the N gradations. Thus, an image printed or simulated based on image data may be a small patch so long as the density of the image can be measured. A high density (high duty) image having a high gradation level cannot be printed only by small dots. Thus, some of the mixing rates of Fig. 9 are excluded from the image data candidates to print the high density image. Thus, it is not required to print or simulate all of the mixing rates of Fig. 9. Image data corresponding to the respective N gradations can be narrowed down in advance. The number of the image data candidates corresponding to the respective N gradations is not always equal.

Then, in Step S31, the mixing rates of the large, medium, and small dots at the image data candidates are used to generate 4-valued bitmap image data to be simulated. The large, medium, and small dots may be arranged based on the error diffusion method or the dither method for example. In this embodiment, the dither method as described above was used to determine a method of arranging the large, medium, and small dots. The image data must have a size required for a quality evaluation (which will be described later). In this embodiment, the image data has a size of about lOmmxlOmm.

Next, in Step S32, an image printed based on image data generated in Step S31 is simulated by a computer. During the simulation, an image close to an actual print image is simulated by considering not only the image data but also the influence by the characteristic of the actual printing apparatus for example.

Next, in Step S33, the simulated image is evaluated. In the case of this embodiment, as will be described later, the evaluation value regarding the granular level and stripe as well as a comprehensive evaluation value for comprehensively evaluating them are used. After the evaluation of all images is completed, the processing proceeds from Step S34 to Step S35. Then, as will be described later, to-be-evaluated images are arranged in an order of a higher evaluation to output the evaluation value and the mixing rates of the large, medium, and small dots. <Method of simulating image data having different mixing rates>

As described above, in Step S32 of Fig. 8B, an image is simulated that is printed based on a plurality of pieces of image data having different mixing rates of the large, medium, and small dots. The following section will describe the processing using the flowchart of Fig. 10. The simulation system of this example can be realized by a program operating on a computer. An output image based on the simulation desirably has a resolution of about several pm. If the image has a higher resolution, dots are formed on a print medium at a high accuracy but the time required for the calculation processing will be longer. If the image has an excessively -low resolution on the other hand, the dots are formed at a lower accuracy. Furthermore, if an image is simulated using the landing variation (will be described later) as in this embodiment, the value of the landing variation is suppressed from being reflected.

First, image data, data regarding ink dots, and landing variation data are read (Steps S41, S42, and S43). These pieces of data may be read in an arbitrary order.

The image data read in Step 41 is data in order to carry out the simulation. In the case of this example, the image data is bitmap data converted to 4 values through the quantizing processing as described above. Data regarding the ink dots read in Step S42 is data related to the shapes and diameters of the large, medium, and small dots, and gradation values for configuring these dots used for the simulation. Furthermore, as will be described later, simulation considering feathering can be carried out by inputting data reflecting the dot distortion or the dot density due to the difference in the feathering form.

In the case of the simulation in this example, the pixels configuring dots have the maximum number of gradation values with regard to all of large, medium, and small dots (255 values). However, all of the pixels configuring the dots are not required to have the same gradation value. For example, gradation values corresponding to the large, medium, and small dots may be different from one another. Alternatively, an optical microscope for example may be used to measure the dot density to use the value thereof. When a processing is performed to select the mixing rates of large, medium, and small dots by an ink color having a high lightness in particular, a low gradation value is desirably used.

The landing variation data read in Step S43 is data that shows, with regard to the landing positions at which ink droplets for forming dots land on a print medium, the displacement amounts from the ideal landing position. The landing variation data also includes a landing position displacement error due to the influence by a print head characteristic or air current and an ejection amount error. The landing variation data also includes a temporarily-changing landing fluctuation (which will be described later) and an ejection amount fluctuation. Such errors can be measured by being measured from a printed matter printed by a printing apparatus in advance through an optical microscope for example. As landing variation data inputted for simulation, the measurement values of the errors regarding all ejection openings of the print head may be inputted. In this case however, the input data will be enormous. To prevent this, in this embodiment, with regard to about 100 ejection openings, the center value and the standard deviation of the error measurement values are calculated. Based on an assumption that these values are based on a normal distribution, the errors of all of the ejection openings are calculated. Fig. 11 illustrates an example of the landing variation data in this embodiment. Based on such landing variation data, as will be described later, seven parameters regarding the direction X (a direction along which a print medium is conveyed) and the direction Y intersecting with the direction X (a direction orthogonal to the direction X in the case of this example) are used to perform the simulation. Such a landing variation amount is different depending on each ink color and each dot size. Thus, seven parameters are prepared for each ink color and each dot size.

In Step S44, based on the bitmap data (image data) and the landing variation data of a to-be-simulated image, the ink landing position coordinate (xmm, ymm) is calculated. Fig. 12 illustrates an example of the input bitmap data for the large, medium, and small dots. Based on an assumption that the upper-left pixel of the inputted image data is an origin (0mm, 0mm), the coordinates of the respective dots corresponding to the resolution are calculated. In the case of this embodiment, the resolution is 600dpi. Thus, the medium dot 1601 in Fig. 12 has the ideal landing position at the coordinate of (0.0423mm, 0.1692mm). By adding the above-described landing variation data to the ideal landing position, the landing position for simulation is fixed. Here, it is assumed that the landing displacement amounts in the directions X and Y regarding ejection openings for forming the medium dot 1601 are (0.005mm, 0.012mm). In this case, the landing position for the simulation has coordinates of (0.0473(=0.0423+0.005)mm, 0.1704(=0.1692+0.012)mm). In this manner, the landing positions of all dots are fixed.

In Step S45, the simulation is carried out so that the data regarding the ink dot read in Step S42 are formed at the landing position fixed in Step S44. The simulation as described above allows, as shown in Fig. 13, image data reflecting the landing variation data to be outputted.

The image is a bitmap image having an 8-bit gray scale.

In order to evaluate the image as described above, the resolution of the image is converted. In this embodiment, the resolution required for the image evaluation is 800dpi. Thus, the image resolution by the simulation is converted from 8400dpi to 800dpi. The conversion uses a bicubic method. However, the image format, resolution, and the resolution conversion method for example are not limited to this embodiment.

Figs. 14A and 14B illustrate the result of simulating a plurality of images corresponding to the gradation value 128 in the mixing rate table of Fig. 5. The simulation image of Fig. 14A includes medium and small dots. Thus, although stripe is conspicuous, graininess is not conspicuous. The simulation image of Fig. 14B on the other hand includes many large dots. Thus, stripe is suppressed from being conspicuous but graininess is conspicuous. The simulation image having different mixing rates of large, medium, and small dots as described above is evaluated as will be described later to prepare a mixing rate table optimal for all gradations. Then, the dither table used in the quantizing processing (Step S4) of Fig. 3B is prepared so that the mixing rates of all gradations in the mixing rate table are realized. <Quality evaluation value>

As described above, in Step S33 of Fig. 8B, the simulation image is evaluated. As image evaluation values, an evaluation value showing the granular level of the image and an evaluation value showing the stripe are used.

First, the following section will describe the evaluation value showing the granular level of the image. The lightness data I(x,y) of the evaluation range is subjected to the Fourier conversion to calculate the space frequency characteristic Fi(u,v). This space frequency characteristic Fi(u,v) is multiplied with the visual characteristic VTF2D(u,v) to thereby calculate the Wiener spectrum WSVTF(u,v).

[Formula 1]

M: The number of longitudinal and lateral pixels in the evaluation range DPI: Scanning resolution R: Observation distance in Dooley VTF formula

Then, the integral value of this Wiener spectrum WSVTF(u,v) is used as the granular level evaluation value G. This shows that, the higher the value G is, the higher the granular level is.

[Formula 2]

Next, the following section will describe the evaluation value regarding the stripe of the image.

With regard to the image within the evaluation range, the average lightness of the pixel line (direction x) is calculated. When assuming that the lightness at the image position (x,y) is I(x,y), the line average lightness L*lD(y) is calculated by the following formula.

[Formula 3]

M: The number of lateral pixels within the evaluation range

Next, the average lightness of each line is subjected to the Fourier conversion to calculate the space frequency characteristic F(v). This space frequency characteristic F(v) is multiplied with the visual characteristic VTFlD(v) to calculate the Wiener spectrum WSVTF(v).

[Formula 4]

N: The number of longitudinal pixels within the evaluation range DPI: Scanning resolution R: Observation distance in the Dooley VTF formula

Then, the following formula is used to calculate the integral value of Wiener spectrum WSVTF(v) as the stripe evaluation value B. This shows that, the higher the value B is, the higher the stripe is.

[Formula 5]

The evaluation values regarding these granular level and stripe are an example and the invention is not limited to them. For example, a granularity evaluation value may be based on an RMS granular level or ISO-TS24790. <Comprehensive evaluation value>

The granular level evaluation value G and the stripe evaluation value B calculated as described above are used to calculate the comprehensive evaluation value T based on the following formula.

[Formula 6]

G: Granular level evaluation value B: Stripe evaluation value a: Stripe visual limit threshold value 6: Weighting parameter

Images are evaluated using this comprehensive evaluation value T and are arranged in an order of a higher evaluation. In the case of this example, images are arranged in an order of a lower evaluation value.

The following section will in detail this comprehensive evaluation value.

According to our observation, substantially no stripe is visually confirmed until the comprehensive evaluation value T exceeds a fixed value but much more stripes are suddenly visually confirmed when the comprehensive evaluation value T exceeds the fixed value. On the other hand, the granularity is more visually confirmed continuously in accordance with the continuous increase of the comprehensive evaluation value T.

Thus, by using the threshold value Tth of the comprehensive evaluation value T at which the using stripe is visually confirmed as a boundary, an image having the comprehensive evaluation value T equal to or lower than the threshold value Tth is evaluated based on the evaluation value G regarding granularity while an image having the comprehensive evaluation value T higher than the threshold value Tth is evaluated based on the comprehensive evaluation value T regarding granularity and stripe. Specifically, with regard to an image for which no stripe is visually confirmed, only granularity is suppressed without considering the balance between granularity and stripe. With regard to an image for which stripe is visually confirmed on the other hand, the balance between granularity and stripe is considered.

Generally, these evaluation values change depending on the gradation of the image. Although there is some difference depending on the print medium, ink, or half tone for example, an image having a low gradation value generally tends to have a smaller stripe while an image having a high gradation value tends to have a large stripe. Thus, by evaluating the image at each gradation, it is possible to suppress the granularity in the range having a low gradation value and to suppress the granularity and stripe with an increase of the gradation value. Specifically, such an evaluation can be provided that is useful to print a favorable image at all gradations.

In this embodiment, the threshold value Tth at which a stripe is visually confirmed is set to 0.3. However, the threshold value Tth is different depending on a print medium, ink, and a half tone. The weighting parameters to the respective evaluation values can be changed by a user depending on a print medium, a printing apparatus, an elapsed time, or a required quality. When the comprehensive evaluation value T is equal to or lower than the threshold value Tth, the evaluation may be performed not only considering the granularity only but also considering the evaluation value of the stripe. <Method of inputting information regarding the feathering (1)>

Dot distortion data as information regarding feathering can be inputted in Step S42 of Fig. 10. The distortion data is one of pieces of the information regarding the ink dot. Fig. 15 illustrates a specific example of the dot distortion data. This distortion data is based on the result of observing the ink dot bleeding formed on different print media A, B, C, and D by an optical microscope. In this example, in order to improve the simulation calculation speed, the distortion data of ink dots of a single color such as black (Bk) was used. However, RGB data having gray or color information also may be used as distortion data. Dot bleeding due to feathering is a phenomenon randomly occurring in any direction. Thus, in the simulation reflecting distortion data, the dot distortion is randomly rotated around the dot gravity center as a center. <Method of inputting information regarding the feathering (2)>

Information regarding the feathering also can be inputted as the landing variation data for each print medium in Step 43 of Fig. 10. The feathering for each print medium can be reflected on the landing variation data of each print medium to thereby reproduce these featherings. <Dot measurement

In the simulation considering the feathering, seven parameters as shown in Fig. 16A are inputted. In order to calculate these parameters, dots are measured in the manner as described below. A to-be-measured print image is obtained by printing a measurement pattern on an actually-used print medium by a printing apparatus. As shown in Fig. 16B, an ink droplet is ejected through the ejection opening 200 of the print head 2 provided in the printing apparatus to form the dot D on the print medium to thereby print the measurement pattern. Fig. 16B schematically shows that one of nozzles corresponding to the ejection openings 200 is used to form m dots D corresponding to the event number m. In the drawing, the dot D is shown by a substantially-true circle. However, the dot D actually formed on the print medium includes featherings having various shapes depending on the type of a print medium as shown in Fig. 15.

As shown in Fig. 16B, the respective n nozzles are used to form the m dots corresponding to the event number m. Based on the print result of the measurement pattern as described above, an amount by which the position at which the dot D is formed is displaced from the ideal dot landing position in the direction X (direction along which the print medium is conveyed) (hereinafter referred to as "X deflection") is measured. Similarly, an amount by which the position at which the dot D is formed is displaced from the ideal dot landing position in the direction Y (a direction along which the nozzles are arranged) (hereinafter referred to as "Y deflection") is measured. In this manner, the dot displacement amount in the X axis direction at the coordinate (X,Y) on the print medium (X deflection) as well as the dot displacement amount in the Y axis direction (Y deflection) are measured. Furthermore, the diameters of the respective dots D (hereinafter referred to as "dot diameter") are measured. These X deflection, Y deflection, and dot diameter can be measured using various image processing methods. In this example, the image reading data on which dots are formed is binarized to set the displacement amounts of the gravity center position coordinate of the dot D in the binary image and the ideal gravity center position coordinate of the dot D as the X deflection and the Y deflection. The shape of the dot D in the binary image is converted to a true circle to set the diameter of the true circle as a dot diameter.

As described above, in the m events from the event 1 to the event m, the n nozzles from the first nozzle to the nth nozzle are used to form (nxm) dots. Fig. 17 illustrates a table showing the summary of the measurement result of the X deflection, Y deflection, and dot diameter of the dots thus formed. Specifically, the data corresponding to n(nozzle(s)) x m(event(s)) is measured. In order to achieve the measurement, an area scanner or a line scanner such as CCD camera is provided in the printing apparatus to read the print result of the measurement pattern as shown in Fig. 16B. Then, the read image can be subjected to an image processing to calculate the displacement from the ideal dot landing position (X deflection, Y deflection) and the dot diameter. The print region corresponding to n (nozzles) x m (events) is a predetermined region in which dots corresponding to n (nozzles) are formed. The variation of the measurement value regarding the dots within this predetermined region shows the fluctuation of the dots corresponding to the n (nozzles). With regard to dots corresponding to one nozzle, a region to calculate the variation of the measurement value of the dots is a region corresponding to the m (events). <Parameter calculation method>

In the simulation considering the feathering, the seven parameters as shown in Fig. 16A (X deflection, Y deflection, X fluctuation, Y fluctuation, an average dot diameter, a dot diameter fluctuation, and a nozzle variation) are used. These parameters are calculated based on the above-described X deflection, Y deflection, and dot diameter measurement result. In this example, the respective parameters are defined based on the "average value" and "standard deviation" calculated from a general statistics processing such as the following formula 7.

[Formula 7]

Ave: Average value o: Standard deviation N: Sampling number (measured nozzle number)

Next, the following section will describe the respective calculating formulae for the seven parameters (X deflection, Y deflection, X fluctuation, Y fluctuation, an average dot diameter, a dot diameter fluctuation, and a nozzle variation). The simulation result obtained by using such parameters will be subjected to the quality evaluation as described above. <Method of calculating the X deflection>

The following formula 8 shows a formula of calculating the X deflection.

[Formula 8]

n: Measured nozzle number m: Measurement event number

The X deflection of the nxm actual measurement of Fig. 17 is subjected to the formula 12 to calculate the average value Ave-xall to finally calculate the X deflection as a standard deviation value. <Method of calculating Y deflection>

As in the X deflection, the following formula 9 is used to calculate the Y deflection as a standard deviation value. The term Ynzi,event corresponds to the Y deflection of the actual measurement in Fig. 17. [Formula 9]

<Method of calculating X fluctuation>

The following formula 10 is a formula of calculating the X fluctuation. The term Xevent corresponds to the m X deflections regarding the respective nozzles in Fig. 17.

[Formula 10]

The X fluctuation is obtained by representing the variation of the X deflection in the m events of the respective nozzles (standard deviation) as an average value of the n nozzles. Specifically, the average value Avenzi of the X deflection in the m events for the respective nozzles is firstly calculated. Next, the X deflection variation in the m events for the respective nozzles (standard deviation) onzi is calculated. Finally, the average value of σηζι corresponding to the n nozzles is calculated and is used as the X fluctuation. <Method of calculating Y fluctuation

The following formula 11 is a formula of calculating the Y fluctuation and is calculated in the same way as in the X fluctuation. The term Yevent corresponds to the m Y deflections of the respective nozzles in Fig. 17.

[Formula 11]

<Method of calculating average dot diameter>

The following formula 12 is a formula of calculating the average dot diameter (Dot Diameter). This average dot diameter is the average value of the measurement data of the nxm dot diameters.

[Formula 12]

Dot nzl,event corresponds to the dot diameter in Fig. 17. <Method of calculating dot fluctuation>

The following formula 13 is a formula of calculating the dot diameter fluctuation. The term "dotevent" corresponds to the m dot diameters of the respective nozzles in Fig. 17.

[Formula 13]

The average value Avenzi is calculated based on the data of the dot diameter of the m events of one nozzle. Then, the variation of the dot diameter within the m events (standard deviation) onzi is calculated. Finally, the average value is calculated based on the onzi corresponding to the n nozzles to set the average value as a dot diameter fluctuation. <Method of calculating a nozzle variation>

The following formula 14 is a formula of calculating the nozzle variation.

[Formula 14]

The nozzle variation means a variation (standard deviation) of the average dot diameter of the actually-measured n nozzles. <Relation between a parameter and the feathering>

So long as ink droplets are ejected through the same nozzle of the print head, the ejection direction and the ejection amount are in principle determined based on the electrical or mechanical characteristic of the nozzle. Such a relation does not originally depend on the type of a print medium to be used. When dots are formed by ink on an exclusive paper for the inkjet printing for example, the dots has a substantially-true circle shape and thus the values of the X deflection, the Y deflection, and the dot diameter are stable in the m events. However, these values are unstable in a plain paper causing a significant feathering. In this embodiment, a difference in the feathering generation level is represented by the parameter fluctuation (X fluctuation, Y fluctuation, and a dot diameter fluctuation) <Relation between a parameter and the simulation>

The X deflection and Y deflection parameters excluding the average dot diameter are inputted to the simulation system as a standard deviation. A simulation program is used to use an inputted standard deviation to thereby calculate the X deflection and the Y deflection for the respective nozzles.

For example, a case is assumed in which an image printed based on a 600dpi resolution with 256 nozzles is simulated. In this case, based on the X deflection and the Y deflection given as a standard deviation value, the random function of Excel® as calculation software is used to prepare the normal distribution data corresponding to the 256 nozzles of the X deflection and the Y deflection so that the given standard deviation is obtained. This data is used as the X deflection and the Y deflection for the respective nozzles. With regard to the fluctuation for each event, the standard deviation values of the similarly-given X fluctuation and Y fluctuation are used to cause the fluctuation for each event. Then, the fluctuation value is added to the previously-calculated X deflection and Y deflection values for each nozzle to thereby calculate the final dot landing position.

The dot diameters of the respective nozzles are dispersed by firstly giving an average dot diameter value to all of the 256 nozzles used in the simulation so that the nozzles have the inputted nozzle variation value as a standard deviation. The average value maintained in the inputted average dot diameter. With regard to the dot diameter fluctuation for each nozzle, as in the X fluctuation and the Y fluctuation, fluctuation is given for each event to change the dot diameter.

In this example, the X deflection, the Y deflection, and the dot diameter of each nozzle are calculated by using the random function of the calculation software Excel® for each nozzle. The other X fluctuation, Y fluctuation, and dot diameter fluctuation are calculated by using a simulation program to execute the calculation using a function. However, these calculation methods are not limited and all calculations also may be performed by a program. <"Fluctuation" parameter>

Next, the following section will describe a "fluctuation" parameter. Figs. 18A to 18D are image diagrams illustrating the output images (simulation images) as simulation results in which the dots have a substantially-true circle shape. In Fig. 18A, the dots corresponding to the respective nozzles have substantially the same diameter. Specifically, the nozzle variation is zero. When the respective dots have no X deflection or Y deflection and are formed at an ideal position, the simulation image shows no stripe for example as shown in Fig. 18A.

When a certain nozzle includes the Y deflection on the other hand, in a print medium having small feathering such as a plain paper, a displaced dot is formed at the position corresponding to the Y deflection as shown in Fig. 18B to cause a stripe to be conspicuous. Specifically, since feathering is small and the values of X fluctuation and Y fluctuation are small, the parts Pa and Pb show a conspicuous stripe due to the influence by the Y deflection. In the case of a print medium having a high feathering such as a paper on the other hand, the X fluctuation and the Y fluctuation are high. Thus, the landing positions of the dots formed by the same nozzle as shown in Fig. 18C change depending on each event, thus consequently suppressing the stripes at the parts Pa and Pb from being conspicuous. Furthermore, by considering the fluctuation of the dot diameter in Fig. 18C, the diameter of the dot corresponding to each nozzle changes depending on each event as shown in Fig. 18D. This consequently further suppresses the strips at the parts Pa and Pb from being conspicuous.

The appearance of the stripe caused by the degree of the feathering in the simulation image as described above is the same as the appearance of the stripe obtained when an image is actually printed on a print medium having the feathering having a different degree. Specifically, when an image is actually printed on a different type of a print medium, the appearance of the stripe is different depending on the print medium. Thus, the stripe is less conspicuous when a paper having a high feathering i.e., a paper in which ink tends to bleed. <Specific example of the simulation>

The present inventors formed dots by the nozzle number n of 40 and the event number m of about 30 and calculated the above-described seven parameters based on the actual measurement values of these dots to use these values in the simulation using 256 nozzles, the result of which is shown in Fig. 19. More specifically, the above-described 7 parameters were acquired for the respective plain papers having different 13 types of feathering (plain papers A to M). Then, these parameters were inputted to simulate the situation in which images of three types of different densities are printed on the respective plain papers to subject the stripe in the simulated image to a quantitative evaluation. On the other hand, the images of the three types of different densities were actually printed on the respective plain papers and the strip in the actual print image was subjected to a quantitative evaluation. The former and latter quantitative evaluations show the values having a relation as shown in Fig. 19. In Fig. 19, the total of 39 points are plotted, showing that the former and latter quantitative evaluations have values having a high correlation to each other. This means that the actual measurement data is not required to acquire for all 256 nozzles to be simulated and thus an accurate simulation can be achieved by calculating parameters based on the actual measurement data for about 40 representative nozzles. (Second embodiment)

In this embodiment, a print medium is divided to a plurality of groups depending on the shape of the feathering. Then, tables having different high, medium, and low print duties are allocated to the respective groups. A method of digitizing the grouping process includes the first, second and third methods as shown below. <First method (gravity center moment)>

As shown by Fig. 15, feathering can be represented by the dot distortion and the distortion can be digitized by a gravity center moment. The gravity center moment is obtained by calculating, with regard to dots as shown in Fig. 15, the distance between the gravity center position calculated based on the densities of the respective pixels constituting the dots and the ideal positions at which the dots should land to multiply the distance with the total value of the densities of the respective images. It can be considered that, the higher this value is, the higher the influence by the feathering is. The result is shown in Fig. 27. It can be seen that the gravity center moment and the stripe have therebetween a high correlation therebetween. <Second method (X fluctuation, Y fluctuation)>

As has been described using Figs. 18A to 18D, the X fluctuation and the Y fluctuation are highly correlated to the feathering. Fig. 20 illustrates an example of the correlation thereof. In Fig. 20, the horizontal axis shows the X fluctuation (pm) while the vertical axis shows a stripe evaluation value (the higher the value is, the stripe is more conspicuous, the lower the value is, the stripe is less conspicuous) and the former and the latter have a high correlation therebetween. Specifically, in the case of a print medium having a high X fluctuation, i.e., a print medium highly influenced by the feathering, the stripe is not conspicuous. In the case of a print medium having a low X fluctuation, i.e., a print medium less influenced by the feathering on the contrary, the stripe is conspicuous. Fig. 21 shows an example of the correlation between the Y fluctuation and the stripe evaluation value. The Y fluctuation and the stripe evaluation value also have therebetween a high correlation. Thus, the X fluctuation and the Y fluctuation can be used to digitize the feathering to divide a print medium to a plurality of groups. Specifically, the measurement values of images printed on a plurality of types of print media can be evaluated to divide, based on the measurement value evaluation result, these print media to groups. <Third method (simulation)>

In the above-described first embodiment, the mixing rates of large, medium, and small dots are optimized with regard to different print media to divide, based on the profiles of these mixing rates, the print media to a plurality of groups depending on the feathering level. Figs. 22A to 22C and Figs. 23A to 23C illustrate mixing rates optimized for six different print media in the first embodiment. Figs. 22A, 22B, and 22C as well as Figs. 23A, 23B, and 23C are shown in an ascending order of feathering. In these drawings, the horizontal axis shows the density while the vertical axis shows the mixing rates of the large, medium, and small dots, respectively. As can be seen from these drawings, the print medium in Fig. 22A has a low feathering level but the print media in Figs. 22B and 22C having a similar profile can be grouped as the one having a medium feathering level. The print media having a similar profile in Figs. 23A, 23B, and 23C can be classified as the one group having a high feathering level.

As is clear from the description of the second and third methods, a print medium having a high feathering level is suppressed from having a stripe, thus consequently allowing smaller dots to be used. A print medium having a low feathering level on the other hand tends to cause a stripe to appear, thus consequently allowing larger dots to be used to thereby suppress the stripe from being conspicuous. (Third embodiment)

In the above-described first and second embodiments, when an image is printed by dots of different sizes, the simulation considering feathering is used to select a mixing rate optimal for the dots to prepare a dither table for realizing the mixing rate. However, dots forming the image are not always required to have different sizes.

This embodiment is an application in which the simulation considering the feathering is performed regardless of the dot size to generate a simulation image reflecting the influence by the feathering. This embodiment of course includes a case where an image is printed by dot having the same size and includes any case regardless of the objective of the use of a simulation image reflecting the influence by the feathering.

Fig. 24 is a flowchart for explaining the simulation in this embodiment. The simulation in this embodiment is carried out as in above-described embodiment.

First, based on the print image of the measurement pattern, the measurement values (X deflection, Y deflection, and dot diameter) required for the calculation of the above-described seven parameter are acquired (Step S51). Next, as in the above-described embodiment, based on these measurement values and the formulae 8 to 14, the seven parameters, i.e., the X deflection, the Y deflection, the X fluctuation, the Y fluctuation, the average dot diameter, the dot diameter fluctuation, and the nozzle variation are calculated (Step S52). Next, as in the above-described embodiment, these parameters are used to perform the simulation considering the feathering (Step S53).

Fig. 25 illustrates the simulation system in this embodiment.

In this embodiment, an external measuring instrument 908 of the printing apparatus is used to measure the X deflection, Y deflection, and dot diameter in the print image of the measurement pattern to calculate the above-described seven parameters based on these measurement values. The former measurement function and the latter calculation function may be owned by the printing apparatus. The calculated parameters are inputted by an operator to the simulation system through the user interface 903. The original image 901 as a simulation target is similarly inputted through the user interface 903 and is converted by an image data converter 905 to data required for printing such as nozzle information, landing data, dot diameter data, or an ejection order and is subsequently stored. The parameters inputted by the operator are stored in the input parameter storage unit 907.

Thereafter, the simulation as in the above-described embodiment is performed. First, an ink landing data converter/output image data converter 906 uses the parameters stored in the storage unit 907 to calculate the X deflection, the Y deflection, the dot diameter, and the fluctuation (the X fluctuation, the Y fluctuation, the dot diameter fluctuation) given to each nozzle. Specifically, the X deflection, the Y deflection, the dot diameter, and the fluctuation (the X fluctuation, the Y fluctuation, the dot diameter fluctuation) for each nozzle is reflected upon the data of the original image 901 stored in the image data converter 905. Based on the information, the simulation image 902 in which the respective dots are arranged is outputted. (Fourth embodiment)

In the above-described third embodiment, based on the nxm measurement data subjected to the actual measurement in Step 52 of Fig. 24, the average dot diameter and the fluctuation as an input parameter are calculated to thereby perform the simulation about print media having different feathering states (e.g., plain paper). By the simulation as described above, as in the above-described first embodiment, the actual measurement values for about 40 nozzles could be used as a typical value in the simulation of the respective 256 nozzles to thereby obtain a favorable simulation result. Specifically, the X deflection, the Y deflection and each fluctuation are given by a standard deviation to use a function such as the external calculation software Excel® or a simulation program to prepare data for the simulation of each nozzle.

Although this embodiment requires a measurement time, data regarding all to-be-simulated nozzles (e.g., 256 nozzles) is actually measured based on a print image to calculate, based on these values, seven parameters for each nozzle to directly use them for the simulation. The following section will describe the method.

Fig. 26 is a table of the summary of the result of measuring, with regard to all of the 256 nozzles, the X deflection, the Y deflection, and the dot diameter for 30 events based on the dot pattern as shown in Fig. 4 in the above-described embodiment. Based on these pieces of measurement data, the following procedure is used to calculate the seven parameters given to each nozzle.

First, the X deflection and the Y deflection have an average value for 30 events with regard to each nozzle.

[Formula 15]

The term Xevent represents the X deflection in the respective 30 events for each nozzle in Fig. 26 and the average value of 30 events is the X deflection nzl of the nozzles.

The X fluctuation nzl for each nozzle is calculated by the following formula 16.

[Formula 16]

The term X fluctuation nzl shows the amount of the variation in the X deflection (standard deviation) owned by each nozzle in 30 events.

Similarly, the Y deflection nzl and the Y fluctuation nzl of each nozzle are calculated by the following formulae 17 and 18.

[Formula 17]

The term Yevent shows the Y deflection in each of 30 events of each nozzle in Fig. 26. The average value of 30 events shows the Y deflection of the nozzle.

[Formula 18]

Next, the dot diameter of each nozzle is calculated by the following formula 19 as the average value of the measurement value of the dot diameter for 30 events.

[Formula 19]

The term dotevent represents a dot diameter at each of 30 events of each nozzle in Fig. 26. The average value of 30 events is an average dot diameter of the nozzles.

The term dot diameter fluctuation nzl shows the variation in the dot diameter data of 30 events measured for the respective nozzles and is calculated by the following formula 20.

[Formula 20]

The nozzle variation is the variation of the average dot diameter of the measured 256 nozzles and thus is calculated by the following formula 21.

[Formula 21]

As described above, the formulae 15 to 21 are used to determine, with regard to the respective 256 nozzles, the seven input parameters (nozzle variation is not represented for each nozzle). In the above-described third embodiment, based on the standard deviation given by the external measuring instrument or simulation program of the printing apparatus, the X deflection, the Y deflection, the dot diameter, and the fluctuation (the X fluctuation, the Y fluctuation, the dot diameter fluctuation) of each nozzle was determined. On the other hand, in this embodiment, the standard deviation value of each nozzle obtained by the calculation is directly used.

In this embodiment, as in the above-described embodiment, a favorable result could be obtained for a simulator for reproducing an actual image. (Other embodiments)

The present invention can be widely applied to various printing apparatuses for applying ink to a print medium. Such printing apparatuses may be the full line-type one as shown in Fig. 1 for example or the so-called serial scanning type one for example. A method of applying ink is not limited to a method using an ink jet printing head.

The image processing apparatus of the present invention also can be configured as a host apparatus or may be combined with a printing apparatus that can print an image including a simulation image.

Embodiment(s) of the present invention can also be realized by a computer of a system or apparatus that reads out and executes computer executable instructions (e.g., one or more programs) recorded on a storage medium (which may also be referred to more fully as a 'non-transitory computer-readable storage medium') to perform the functions of one or more of the above-described embodiment(s) and/or that includes one or more circuits (e.g., application specific integrated circuit (ASIC)) for performing the functions of one or more of the above-described embodiment(s), and by a method performed by the computer of the system or apparatus by, for example, reading out and executing the computer executable instructions from the storage medium to perform the functions of one or more of the above-described embodiment(s) and/or controlling the one or more circuits to perform the functions of one or more of the above-described embodiment(s). The computer may comprise one or more processors (e.g., central processing unit (CPU), micro processing unit (MPU)) and may include a network of separate computers or separate processors to read out and execute the computer executable instructions. The computer executable instructions may be provided to the computer, for example, from a network or the storage medium. The storage medium may include, for example, one or more of a hard disk, a random-access memory (RAM), a read only memory (ROM), a storage of distributed computing systems, an optical disk (such as a compact disc (CD), digital versatile disc (DVD), or Blu-ray Disc (BD)™), a flash memory device, a memory card, and the like.

While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. The scope of the following claims is to be accorded the broadest interpretation so as to encompass all such modifications and equivalent structures and functions.

Claims (13)

An image processing apparatus comprising: an acquisition unit (31) configured to acquire image data corresponding to an image for printing on a print medium (P); and a generation unit (36) configured to generate print data for ejecting a plurality of ink types corresponding to different dot sizes, by quantizing the image data, wherein: the generation unit (36) generates the print data such that the respective usage rates of the plurality of ink types differ depending on a gradation value of the image data, the plurality of ink types comprises at least one ink corresponding to a first dot size, ink corresponding to a second dot size greater than the first dot size, and ink that corresponds to a third dot size that is greater than the first and second dot sizes; the image processing apparatus further comprises a memory (34) for storing first, second and third dither patterns corresponding to ink corresponding to the first, second and third dot sizes, respectively, and having threshold values for determining ink ejection or no ink ejection to respective pixels; outputs (i) the generation unit (36) to the respective pixels, when a gradation value (LV) of the image data is equal to or higher than a threshold value (LTH) determined for the third dither pattern, from print data which determine ejection of ink corresponding to the third dot size (ii) generate, when the gradation value (LV) of the image data is lower than the threshold value (LTH) determined for the third dither pattern and is equal to or higher than a threshold value (MTH) determined for the second dither pattern, from print data determining the ejection of ink corresponding to the second dot size, (iii) generating, when the gradation value (LV) of the image data is lower than the threshold value (MTH) determined for the second dither pattern and equal is at or greater than a threshold value (STH) determined for the first dither pattern, of print data determining the ejection of ink corresponding to the first dot size, and (iv) generate, when the gradation value (LV) of the image data is lower than the threshold value (STH) determined for the first dither pattern, generate print data that does not eject the respective plurality of types of ink. The image processing apparatus according to claim 1, wherein: the generation unit (36) generates the print data such that as the level of an ink leak to the print medium (P) is higher, the usage amount of ink corresponding to a larger dot size among the plurality of types of ink is lower. The image processing apparatus according to claim 1 or 2, wherein: the generation unit (36) generates the print data such that as the level of an ink leak to the print medium (P) is higher, the usage amount of ink corresponding to a smaller dot size below the many types of ink is higher. The image processing apparatus according to any of the preceding claims, wherein: in the respective first, second and third dither patterns, the threshold values for the respective pixels are determined according to the ink leak estimated from an analysis result, the analysis result being obtained by analyzing a simulation image performed based on deviations of measured values concerning a plurality of dots formed in a predetermined area of the print medium (P). An image processing method, comprising: an acquisition step of acquiring image data corresponding to an image for printing on a print medium; and a generation step of quantizing the image data to thereby generate print data for ejecting a plurality of types of ink corresponding to different dot sizes; wherein: the generation unit generates the print data such that the respective usage rates of the plurality of ink types differ depending on a gradation value of the image data, the plurality of ink types comprises at least one ink corresponding to a first dot size, ink corresponding to a second dot size greater than the first dot size, and ink corresponding to a third dot size greater than the first and second dot sizes; the image processing method further includes a preparation step of preparing first, second and third dither patterns that correspond to ink corresponding to the first, second and third dot sizes, respectively, and that have threshold values for determining ink ejection or no ink ejection to respective pixels; outputs (i) the generation step (36) to the respective pixels, when a gradation value (LV) of the image data is equal to or higher than a threshold value (LTH) determined for the third dither pattern, of print data which determine ejection of ink corresponding to the third dot size (ii) generate, when the gradation value (LV) of the image data is lower than the threshold value (LTH) determined for the third dither pattern and is equal to or higher than a threshold value (MTH) determined for the second dither pattern, from print data determining the ejection of ink corresponding to the second dot size, (iii) generating, when the gradation value (LV) of the image data is lower than the threshold value (MTH) determined for the second dither pattern and equal is determined on or greater than a threshold value (STH) for the first dither pattern, of print data determining the ejection of ink corresponding to the first dot size, and (iv) g and, when the gradation value (LV) of the image data is lower than the threshold value (STH) determined for the first dither pattern, to determine print data that does not eject the respective quantity of ink types. An image simulation method for simulating an image printed on a print medium (P) by ink dots, comprising: a first acquisition step of acquisition of image data (S41); a second acquisition step (S41, S42, S43) of acquiring first values regarding any of size, diameter, and gradation value from a plurality of dots formed in a predetermined area of the print medium (P); a third acquisition step of obtaining second values regarding landing variation of the dots (S43); a simulation step (S45) of simulating an image based on the image data, the first values and the second values; and an evaluation step (S33, S34) of evaluating the image simulated in the simulation step (S45). The image simulation method according to claim 6, further comprising a determining step of determining respective printing ratios of a plurality of types of dots. The image simulation method according to claim 6 or 7, wherein: the first values comprise at least one of an amount of displacement of a mass center dot position of the dot and a diameter obtained by conversion of the dot to a true circle. The image simulation method according to claim 8, wherein: the amount of displacement of the mass center dot position of the dot includes a dot displacement amount in one direction on the print medium. The image simulation method according to any one of claims 6 to 9, wherein: the second value contains a deviation represented by a standard deviation of the measured values in the predetermined area. The image simulation method according to any of claims 6 to 10, wherein: the image simulated in the simulation step (S45) represents the dot as a circle. The image simulation method according to any of claims 6 to 11, wherein: the first values comprise measurement values regarding the plurality of dots formed on different print media (P). An image processing apparatus comprising an acquisition unit (31) configured to acquire image data corresponding to an image for printing on a print medium (P); and a generation unit (36) configured to generate print data for ejecting a plurality of types of ink corresponding to a first dot size and ink corresponding to a second dot size greater than the first dot size, by quantizing the image data, a memory for the storing first and second dither patterns corresponding to ink corresponding to the first and second dot sizes, respectively, and having threshold values for determining ink ejection or no ink ejection to respective pixels; wherein the generation unit (36) outputs (i) outputs to the respective pixels, when a gradation where the (LV) of the image data is equal to or higher than a threshold value (MTH) determined for the second dither pattern, of generate print data determining the ejection of ink corresponding to the second dot size (ii) when the gradation value (LV) of the image data is lower than the threshold value (MTH) determined for the second dither pattern and is equal to or higher than a threshold value ( STH) determined for the first dither pattern, of print data determining the ejection of ink corresponding to the first dot size, (iii) generating, when the gradation value (LV) of the image data is lower than the threshold value (STH) determined for the first dither pattern, of print data that does not determine ejection of ink of the respective plurality of types of ink.