JP2010136023A - Image processor, image processing method, image processing program, and recording medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To control tone jump (gradation steps) of correction data. <P>SOLUTION: An image processor has a patch data forming part which forms patch data that includes a plurality of patches for each same color and same input density value, and a patch data processor which classifies a plurality of measured data generated by reading images of the plurality of patches that are formed on a recording medium based on the patch data for each color and input density value, calculates a plurality of average values for each color and input density value of the plurality of measured data, generates correction data for each color by arranging the plurality of average values for each color in the order of input density values and divides the range of input density values of the correction data into a plurality of areas corresponding to the content of colors, input image features or gradation processing. In addition, the image processor also has a correction data determination part which determines whether or not the correction data satisfies specified conditions based on the plurality of average values for each of the plurality of areas, and a correction data generator which corrects a density correction data table based on the determination result of the correction data determination part and the correction data. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to an image processing apparatus, an image processing method, an image processing program, and a recording medium that correct a density correction data table used for density conversion of an input image.

  In a conventional image forming apparatus, it is known that the image quality of an output image changes due to the characteristics of the image forming apparatus and changes over time. As a technique for solving this problem, for example, a technique described in Patent Document 1 below is known.

  In Patent Document 1, color patch colorimetric data obtained by measuring the color of each color patch output by an output device using patch data representing a plurality of color patches having different densities and a preset target. A calibration device that determines color correction data for converging colorimetric data of color patches output from an output device to target color data by repeating a calibration process for correcting patch data based on color data a plurality of times. Further, the color misregistration amount between the color measurement data of the color patch and the preset target color data is calculated, and is generated in the next calibration step based on the color misregistration amount calculated in the current calibration step. A calibration device for selecting a color patch of patch data to be processed is described.

  In the technique described in Patent Document 1, threshold determination is performed for color patches on a sheet, color patches that are within an allowable range with respect to the threshold are excluded from the next patch data, and color patches that are outside the allowable range are excluded from the next time. Selected again for patch data. However, in the technique disclosed in Patent Document 1, threshold determination is performed on the color patch on the patch sheet on the basis of the density, so that an actual image is not output as to whether or not there is a gradation step in the correction data. May not be confirmed.

  As a related technique, the present applicant outputs a measurement chart output unit that outputs a measurement chart including a plurality of color patches, a reference chart that includes a plurality of patches with known color densities, and a measurement chart output unit. Captured image data acquisition means for acquiring captured image data including the measured measurement chart, and patch color density holding means for holding the color density of each patch included in the reference chart in association with patch identification information for identifying each patch The color density of each patch held by the patch color density holding unit in association with each patch identification information, and the image data of the patch specified by the patch identification information among the captured image data acquired by the captured image data acquisition unit Color density calculating means for calculating the color density of each patch of the measurement chart based on the color density of Proposed an image forming apparatus such as a symptom (e.g., see Patent Document 2 below).

JP 2004-289215 A JP 2006-222552 A

  The present invention has been made in view of the above, and provides an image processing apparatus, an image processing method, an image processing program, and a recording medium that can reduce gradation skip (gradation step) of correction data. The purpose is to do.

  In order to solve the above-described problems and achieve the object, an image processing apparatus according to the present invention corrects a density correction data table used for density conversion of an input image, and has the same color and the same color. Patch data forming means for forming patch data including a plurality of patches for each input density value, and a plurality of measurements generated by reading images of a plurality of patches formed on a recording medium based on the patch data The data is classified by color and input density value, a plurality of average values for each color and input density value of the plurality of measurement data are calculated, and the plurality of average values are arranged in order of the input density value for each color. Thus, correction data is generated for each color, and the range taken by the input density value of the correction data is divided into a plurality of areas according to the color, the characteristics of the input image, or the content of the gradation processing performed after density conversion. Patch data processing means for dividing, correction data determining means for determining whether or not the correction data satisfies a predetermined condition based on the plurality of average values for each of the plurality of areas, and the correction data determining means Correction data generating means for correcting the density correction data table based on the result of the determination and the correction data.

  An image processing method according to the present invention is an image processing method for correcting a density correction data table used for density conversion of an input image, and includes a plurality of patches for the same color and the same input density value. A patch data forming step for forming data, and a plurality of measurement data generated by reading images of a plurality of patches formed on a recording medium based on the patch data are classified for each color and input density value, Calculating a plurality of average values for each color and input density value of the plurality of measurement data, generating correction data for each color by aligning the plurality of average values in the order of the input density value for each color, and A patch data processing step that divides the range taken by the input density value of the correction data into a plurality of areas according to the content of the gradation process performed after color, characteristics of the input image, or density conversion; For each of the plurality of regions, a correction data determination step for determining whether or not the correction data satisfies a predetermined condition based on the plurality of average values, a result of determination by the correction data determination step, and the correction data And a correction data generation step of correcting the density correction data table based on the above.

  An image processing program according to the present invention causes a computer to execute the image processing method according to any one of claims 8 to 14.

  A recording medium according to the present invention is a computer-readable recording medium storing the image processing program according to claim 15.

  According to the present invention, patch data including a plurality of patches is formed for each of the same color and the same input density value, and the patch data is used to read the images of the plurality of patches formed on the recording medium. Correction data is generated using a plurality of measured data colors and a plurality of average values for each input density value. As a result, it is possible to reduce the gradation jump (gradation level difference) of the correction data.

  Exemplary embodiments of an image processing apparatus, an image processing method, an image processing program, and a recording medium according to the present invention are explained in detail below with reference to the accompanying drawings.

(Embodiment of the present invention)
As an embodiment of the present invention, an example in which the image processing apparatus of the present invention is applied to an image forming apparatus will be described. This image forming apparatus is connected to a client PC and receives input of image data from the client PC.

  FIG. 1 is a block diagram showing a configuration of an image forming apparatus 1 and a client PC 2 according to an embodiment of the present invention. As shown in FIG. 1, the image forming apparatus 1 includes an image processing unit 10, an image forming unit 20, and an image reading unit 30.

  The image forming apparatus 1 is connected to the client PC 2, and during normal printing processing, the image processing unit 10 in the image forming apparatus 1 receives image data (RGB image data) via the printer driver 2a in the client PC 2. 2b is input. The image processing unit 10 performs color conversion processing, density conversion processing, and gradation processing on the image data 2 b input from the client PC 2 and outputs CMYK image data to the image forming unit 20. The image forming unit 20 forms an image based on CMYK image data input from the image processing unit 10 on a recording medium (for example, paper).

  The image processing unit 10 includes a color conversion processing unit 11, a density conversion processing unit 12, a density correction processing unit 13, and a gradation processing unit 14. The density correction processing unit 13 includes a patch data processing unit 13a as a patch data processing unit of the present invention, a patch data forming unit 13b as a patch data forming unit of the present invention, and correction data as a correction data generation unit of the present invention. A generation unit 13c and a correction data determination unit 13d as correction data determination means of the present invention are included.

  The color conversion processing unit 11 converts RGB image data input from the client PC 2 into CMYK image data.

  The density conversion processing unit 12 uses a density correction data table set in advance for each color of CMYK in a normal printing process in which image formation is performed based on image data input from the client PC 2. 11 converts the density of image data input from 11 for each color of CMYK. The density correction data table used by the density conversion processing unit 12 is corrected by the density correction processing unit 13 at the end of the density correction (calibration) process. During the density correction (calibration) process, the density conversion processing unit 12 converts the density of the patch data input from the density correction processing unit 13 for each color of CMYK using the density correction data table at that time.

  The gradation processing unit 14 converts the number of gradations of the CMYK image data input from the density conversion processing unit 12 into the number of gradations according to the gradation processing capability of the image forming unit 20.

  The image forming unit 20 forms an image based on the image data input from the gradation processing unit 14 on a recording medium.

  The density correction processing unit 13 outputs patch data (CMYK data) to the density conversion processing unit 12 during density correction (calibration) processing. The density conversion processing unit 12 performs density conversion processing on the patch data input from the density correction processing unit 13 and outputs the patch data to the gradation processing unit 14. The gradation processing unit 14 converts the number of gradations of the CMYK image data input from the density conversion processing unit 12 into the number of gradations according to the gradation processing capability of the image forming unit 20 and outputs the converted number to the image forming unit 20. To do. The image forming unit 20 forms an image based on CMYK image data input from the density conversion processing unit 12 (hereinafter also referred to as “density correction color chart”) on a recording medium.

  The image reading unit 30 generates digital image data based on the density information of the original obtained by scanning the set original and outputs the digital image data to the image processing unit 10. During the density correction (calibration) process, the image reading unit 30 reads digital image data (hereinafter referred to as “patch measurement data”) obtained by reading the density correction color chart formed on the recording medium by the image forming unit 20. Is also output to the image processing unit 10.

  Next, the density correction process of the image forming apparatus 1 will be described in detail. 2 to 5 are flowcharts showing the procedure of density correction (calibration) processing of the image forming apparatus 1 according to the present embodiment. When receiving an instruction to start density correction (calibration), the image forming apparatus 1 starts the processes shown in FIGS.

  First, the patch data forming unit 13b determines (forms) a patch to be arranged in the density correction color chart (step S11).

  FIGS. 6A and 6B are diagrams illustrating density correction color charts C1 and C2 as examples of the density correction color chart formed by the image forming apparatus 1, respectively. The density correction color charts C1 and C2 each include 24 patches of cyan, magenta, yellow, and black. The numerical value in each patch represents the input density value of the patch (the density value input from the patch data forming unit 13b to the density conversion processing unit 12). The smaller (closer to 0), the lower the density, and the larger the value. The higher the density (closer to 11), the higher the density. The density correction color charts C1 and C2 include patches of 12 types of input density values for each of the same color materials (cyan, magenta, yellow, and black). Further, the density correction color charts C1 and C2 include a plurality of (two in this case) patches for the same color material and the same input density value. For example, when describing cyan as one color material, the input density values of the two patches P100 and P120 are the same (here, 0). Similarly, the input density values of the two patches P101 and P121 are the same (here, 1). The same applies to the patches P102 to P111 and the patches P122 to P131. The same applies to the other color materials (magenta, yellow, black).

  In general, as in the density correction color chart C1 shown in FIG. 6A, a plurality of patches of the same color material are arranged in order of density from low density to high density. For example, when describing cyan as one color material, the patches P100 to P111 are arranged in the order in which the density gradually increases from the right side in the drawing toward the left side in the drawing. In addition, the patches P120 to P131 are arranged on the lower side of the patch P100 to patch P111 in the order in which the density gradually increases from the right side in the drawing toward the left side in the drawing. Similarly, patches of other color materials (magenta, yellow, black) are also arranged in order of gradually increasing density from the right side in the drawing toward the left side in the drawing.

  Further, as in the density correction color chart C2 shown in FIG. 6B, the patches may be arranged randomly rather than in order of density. For example, a description will be given of cyan as one color material. Patches P100 to P111 are patches P100, P102, P104, P106, P108, P110, P101, P103, from the right side in the figure toward the left side in the figure. P105, P107, P109, and P111 are arranged in this order. The patches P120 to P131 are patches P121, P123, P125, P127, P129, P131, P120, and P122 on the lower side of the patch P100 to patch P111 in the drawing from the right side in the drawing toward the left side in the drawing. , P124, P126, P128, and P130. Similarly, patches of other color materials (magenta, yellow, black) are also randomly arranged. By arranging the color patches at random in this way, it is possible to absorb measurement errors caused by in-plane density unevenness.

  In order to increase the density correction accuracy, it is conceivable to increase the increment of the input density value. However, when the increment of the input density value is increased, a gradation step may occur. FIG. 7A is a diagram illustrating a graph representing the relationship between the input density value and the output density value when the increment of the input density value is increased. In FIG. 7A, a gradation step is generated. Therefore, in the present embodiment, the input density value step is reduced (12 steps from 0 to 11), a plurality of patches of the same color and the same density value are arranged, and an average value thereof is calculated and used. As a result, gradation steps can be reduced. FIG. 7-2 shows the relationship between the input density value and the output density value when the input density value is reduced, a plurality of patches having the same color and the same density are arranged, and the average value is calculated and used. It is a figure which shows the graph showing. In FIG. 7-2, the gradation level difference is reduced as compared with FIG.

  Referring back to FIG. 2, the density conversion processing unit 12 performs density conversion processing on the patch data input from the density correction processing unit 13 and outputs the patch data to the gradation processing unit 14. The gradation processing unit 14 performs gradation processing for converting the CMYK image data (patch data) input from the density conversion processing unit 12 into the number of gradations according to the gradation processing capability of the image forming unit 20. The image is output to the image forming unit 20. The image forming unit 20 forms on the recording medium a density correction color chart based on the CMYK image data (patch data) input from the density conversion processing unit 12 (step S12).

  Next, the image reading unit 30 acquires patch measurement data (digital image data) by reading the density correction color chart formed on the recording medium by the image forming unit 20 and outputs the patch measurement data (digital image data) to the image processing unit 10 ( Step S13).

  Next, the patch data processing unit 13a classifies the plurality of measurement data corresponding to the plurality of patches in the patch measurement data for each color and input density value, and a plurality of the plurality of measurement data for each color and input density value. An average value is calculated (step S14). Referring to FIGS. 6A and 6B again, for example, cyan as one color material will be described. The patch data processing unit 13a includes the measurement data of the part corresponding to the patch P100 and the part corresponding to the patch P120. The average value with the measured data is calculated. The patch data processing unit 13a similarly calculates the average value for each input density value for the patches P101 to P111 and P121 to P131. The patch data processing unit 13a similarly calculates the average value for each color and input density value for other colors (magenta, yellow, black).

  Referring to FIG. 2 again, the patch data processing unit 13a generates temporary correction data for each color by arranging (sorting) the calculated plurality of average values in the order of input density values for each color (step) S15). Further, the patch data processing unit 13a divides the range taken by the input density value of the temporary correction data for each color into a plurality of areas, and distributes the data for each divided area (step S16). The number of areas to be divided and the width of each divided area differ depending on various conditions.

  For example, when the range taken by the input density value of the temporary correction data is divided into a plurality of regions according to the characteristics of the color material, the patch data processing unit 13a performs the process shown in FIG.

  First, the patch data processing unit 13a divides the range taken by the input density value of temporary correction data into three (step S31). FIG. 8A is a diagram illustrating a graph obtained by dividing the range taken by the input density value of temporary correction data into three.

  Next, when the color material is black (black) (step S32: Yes), the patch data processing unit 13a narrows the division width on the low density side (step S33). FIG. 8-2 is a diagram illustrating a graph in which the division width on the low density side is narrowed. When the color material is black, compared to other colors, it is easy to notice density fluctuations at places where the amount of adhesion is low, such as on the low density side. can do.

  On the other hand, when the color material is not black (black) (step S32: No), the patch data processing unit 13a ends the process without reducing the division width.

  For example, in the case of a photographic image, the patch data processing unit 13a performs the process shown in FIG.

  First, the patch data processing unit 13a divides the range taken by the input density value of the temporary correction data into three (step S41).

  Next, when the input data is a photograph (step S42: Yes), the patch data processing unit 13a changes the number of area divisions from 3 to 4 (step S43). FIG. 9B is a diagram illustrating a graph in which the number of divided areas is changed from 3 to 4. Further, the patch data processing unit 13a narrows the division width of the two regions on the medium density side (region 2 and region 3 shown in FIG. 9-2) (step S44). In the case of photographs, since many colors of medium density are used, the number of divisions can be changed from 3 to 4, and the division width of the two areas on the medium density side can be narrowed to increase the accuracy.

  On the other hand, when the input data is not a photograph (step S42: No), the patch data processing unit 13a ends the process without changing the number of divisions or reducing the division width.

  Further, for example, when the division is performed according to the characteristics of the gradation processing performed in the subsequent stage of the density conversion processing, the patch data processing unit 13a performs the processing illustrated in FIG.

  First, the patch data processing unit 13a divides the range taken by the input density value of temporary correction data into three (step S51).

  Next, the patch data processing unit 13a determines the number of divisions of the area when the gradation processing is gradation processing that is used for, for example, a character (a non-periodic dot arrangement) (step S52: Yes). Is changed from 3 to 2 (step S53). FIG. 9A is a diagram illustrating a graph in which the number of divided areas is changed from 3 to 2. This is because it is not necessary to emphasize the overall gradation in the character use compared to the photographic use.

  On the other hand, the patch data processing unit 13a changes the number of divisions when the gradation processing is not gradation processing (for example, a non-periodic dot arrangement) used for, for example, characters (step S52: No). The process is finished without.

  Referring to FIG. 2 again, the patch data processing unit 13a uses the average value of the measurement data for each divided region, and generates correction data for generating a density correction data table (step S17).

  Next, the correction data determination unit 13d determines whether or not correction data correction processing is necessary by determining whether or not the correction data satisfies a predetermined condition for each of a plurality of regions. Specifically, the correction data determination unit 13d calculates the variation (difference) of individual measurement data with respect to the average value with respect to the measurement data (patch) of the same input density value for each of a plurality of areas, and outputs a single (1 If the number of input density values whose variation is larger than a predetermined value in the region (2) is equal to or smaller than the threshold value (within the allowable range) (step S18: Yes), the correction data satisfies the predetermined condition and the correction data is corrected. It is determined that processing is unnecessary. In this case, the correction data generation unit 13c treats the correction data calculated in step S17 as a corrected density correction data table and reflects (outputs) it to the density conversion processing unit 12 (step S19). FIG. 10A is a diagram illustrating a graph of correction data when the number of input density values whose variation is larger than a predetermined value within a single region is equal to or less than a threshold value (within an allowable range).

  On the other hand, the correction data determination unit 13d determines that the correction data is predetermined when the number of input density values whose variation is larger than a predetermined value in a single region is not less than or equal to the threshold value (within an allowable range) (step S18: No). It is determined that correction data correction processing is necessary without satisfying the above condition, and an approximate expression is calculated within a single region (step S20). In this case, the correction data generation unit 13c modifies (calculates) the correction data using the approximate expression (step S21). FIG. 10B is a graph of correction data corrected using an approximate expression when the number of input density values whose variation is larger than a predetermined value in a single region is not less than or equal to a threshold value (within an allowable range). FIG. As an approximate expression, when the determination target region is a low density portion, the amount of change in density value is small compared to other density portions, and therefore an approximate expression of the second order or less is used. Further, when the determination target region is a medium density portion or a high density portion, an approximate expression of the fourth order or lower is used.

  Then, the correction data generation unit 13c connects the correction data for each of the plurality of areas modified in step S21. At this time, the correction data generation unit 13c may correct a gradation step on the correction data of the connection portion because a gradation step may occur in the connection portion between the regions. The gradation step can be corrected by confirming data in the vicinity of the connected portion (for example, ± 5% as a density value) and correcting the data of the connected portion by weighted averaging. Thereafter, the correction data generation unit 13c reflects (outputs) the connected correction data to the density conversion processing unit 12 as a density correction data table (step S19).

  Through the above processing, the density correction data table of the density conversion processing unit 12 is corrected, and thereafter, the density conversion processing unit 12 performs density conversion processing using the corrected density correction data table.

  According to the present embodiment, patch data including a plurality of patches is formed for the same color and the same input density value, and images of the plurality of patches formed on the recording medium are read using the patch data. Correction data is generated using a plurality of generated measurement data colors and a plurality of average values for each input density value. As a result, factors on the engine (image forming unit 20) side (in-plane density unevenness and fluctuation over time) and factors on the image processing unit 10 side (problems in processing when generating correction data) are absorbed and corrected. It is possible to reduce the gradation jump (gradation level difference) of data.

  FIG. 11 is a block diagram illustrating an example of a hardware configuration when the image processing apparatus according to the present embodiment is applied to a multifunction machine. As shown in the figure, this multifunction machine has a configuration in which a controller 110 and an engine unit (Engine) 160 are connected by a PCI (Peripheral Component Interconnect) bus. The controller 110 is a controller that controls the entire MFP, drawing, communication, and input from an operation unit (not shown). The engine unit 160 is a printer engine that can be connected to a PCI bus, and is, for example, a monochrome plotter, a 1-drum color plotter, a 4-drum color plotter, a scanner, or a fax unit. The engine unit 160 includes an image processing unit such as error diffusion and gamma conversion in addition to a so-called engine unit such as a plotter.

  The controller 110 includes a CPU 111, a north bridge (NB) 113, a system memory (MEM-P) 112, a south bridge (SB) 114, a local memory (MEM-C) 117, and an application specific integrated circuit (ASIC). 116 and a hard disk drive (HDD) 118, and the north bridge (NB) 113 and the ASIC 116 are connected by an AGP (Accelerated Graphics Port) bus 115. The MEM-P 112 further includes a ROM (Read Only Memory) 112a and a RAM (Random Access Memory) 112b.

  The CPU 111 performs overall control of the multifunction peripheral, and has a chip set including the NB 113, the MEM-P 112, and the SB 114, and is connected to other devices via the chip set.

  The NB 113 is a bridge for connecting the CPU 111 to the MEM-P 112, SB 114, and AGP 115, and includes a memory controller that controls reading and writing to the MEM-P 112, a PCI master, and an AGP target.

  The MEM-P 112 is a system memory used as a memory for storing programs and data, a memory for developing programs and data, a printer drawing memory, and the like, and includes a ROM 112a and a RAM 112b. The ROM 112a is a read-only memory used as a memory for storing programs and data, and the RAM 112b is a writable and readable memory used as a program and data development memory, a printer drawing memory, and the like.

  The SB 114 is a bridge for connecting the NB 113 to a PCI device and peripheral devices. The SB 114 is connected to the NB 113 via a PCI bus, and a network interface (I / F) unit and the like are also connected to the PCI bus.

  The ASIC 116 is an IC (Integrated Circuit) for image processing having hardware elements for image processing, and has a role of a bridge for connecting the AGP 115, the PCI bus, the HDD 118, and the MEM-C 117. The ASIC 116 includes a PCI target and an AGP master, an arbiter (ARB) that forms the core of the ASIC 116, a memory controller that controls the MEM-C 117, and a plurality of DMACs (Direct Memory) that rotate image data using hardware logic. Access Controller) and a PCI unit that performs data transfer between the engine unit 160 via the PCI bus. An FCU (Fax Control Unit) 130, a USB (Universal Serial Bus) 140, and an IEEE 1394 (the Institute of Electrical and Electronics Engineers 1394) interface 150 are connected to the ASIC 116 via a PCI bus. The operation display unit 120 is directly connected to the ASIC 116.

  The MEM-C 117 is a local memory used as a copy image buffer and a code buffer, and an HDD (Hard Disk Drive) 118 is a storage for storing image data, programs, font data, and forms. It is.

  The AGP 115 is a bus interface for a graphics accelerator card proposed for speeding up graphics processing. The AGP 115 speeds up the graphics accelerator card by directly accessing the MEM-P 112 with high throughput. .

  Note that the image processing program executed by the image processing apparatus of the present embodiment is provided by being incorporated in advance in a ROM or the like.

  The image processing program executed by the image processing apparatus of the present embodiment is a file in an installable or executable format, such as a CD-ROM, a flexible disk (FD), a CD-R, a DVD (Digital Versatile Disk), or the like. You may comprise so that it may record and provide on a computer-readable recording medium.

  Furthermore, the image processing program executed by the image processing apparatus of the present embodiment may be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network. The image processing program executed by the image processing apparatus according to the present embodiment may be provided or distributed via a network such as the Internet.

  The image processing program executed by the image processing apparatus according to the present embodiment has a module configuration including the above-described units (patch data processing unit, patch data forming unit, correction data generation unit, correction data determination unit). As actual hardware, a CPU (processor) reads out and executes an image processing program from the ROM, so that the respective units are loaded onto the main storage device, and a patch data processing unit, a patch data forming unit, a correction data generating unit, A correction data determination unit is generated on the main storage device.

  In the above embodiment, the image processing apparatus according to the present invention will be described with reference to an example in which the image processing apparatus is applied to a multifunction machine having at least two functions among a copy function, a printer function, a scanner function, and a facsimile function. The present invention can be applied to any image processing apparatus such as a printer, a scanner apparatus, and a facsimile apparatus.

  As described above, the image processing apparatus, the image processing method, the image processing program, and the recording medium according to the present invention are useful for a technique for correcting a density correction data table used for density conversion of an input image.

1 is a block diagram illustrating a configuration of an image forming apparatus according to an exemplary embodiment. 6 is a flowchart illustrating a procedure of density correction (calibration) processing in the image forming apparatus according to the present embodiment. 6 is a flowchart illustrating a procedure of density correction (calibration) processing in the image forming apparatus according to the present embodiment. 6 is a flowchart illustrating a procedure of density correction (calibration) processing in the image forming apparatus according to the present embodiment. 6 is a flowchart illustrating a procedure of density correction (calibration) processing in the image forming apparatus according to the present embodiment. It is a figure which shows the example of the color chart for density correction formed with the image forming apparatus which concerns on this Embodiment. It is a figure which shows the example of the color chart for density correction formed with the image forming apparatus which concerns on this Embodiment. It is a figure which shows the graph showing the relationship between the input density value of a color chart for density correction, and an output density value. It is a figure which shows the graph showing the relationship between the input density value of a color chart for density correction, and an output density value. FIG. 6 is a graph showing a relationship between an input density value and an output density value of a density correction color chart formed by the image forming apparatus according to the present embodiment. FIG. 6 is a graph showing a relationship between an input density value and an output density value of a density correction color chart formed by the image forming apparatus according to the present embodiment. FIG. 6 is a graph showing a relationship between an input density value and an output density value of a density correction color chart formed by the image forming apparatus according to the present embodiment. FIG. 6 is a graph showing a relationship between an input density value and an output density value of a density correction color chart formed by the image forming apparatus according to the present embodiment. It is a figure which shows the graph showing the one part area | region of the correction data calculated by the image forming apparatus which concerns on this Embodiment. It is a figure which shows the graph showing the one part area | region of the correction data calculated by the image forming apparatus which concerns on this Embodiment. FIG. 3 is a block diagram illustrating an example of a hardware configuration when the image processing apparatus according to the present embodiment is applied to a multifunction peripheral.

Explanation of symbols

1 Image forming apparatus 2 Client PC
3, C1, C2 Density correction color chart 10 Image processing unit 11 Color conversion processing unit 12 Density conversion processing unit 13 Density correction processing unit 13a Patch data processing unit 13b Patch data forming unit 13c Correction data generation unit 13d Correction data determination unit 14 Gradation processing unit 20 Image forming unit 30 Image reading unit 110 Controller 111 Central processing unit 112 Memory unit 113 North bridge 114 South bridge 115 AGP
116 ASIC
117 Local memory 118 HDD
120 Operation display unit 130 FCU
140 USB
150 IEEE1394
160 Engine part

Claims (16)

An image processing apparatus for correcting a density correction data table used for density conversion of an input image,
Patch data forming means for forming patch data including a plurality of patches for the same color and the same input density value;
A plurality of measurement data generated by reading images of a plurality of patches formed on a recording medium based on the patch data is classified for each color and input density value, and the color and input density of the plurality of measurement data A plurality of average values for each value are calculated, correction data is generated for each color by arranging the plurality of average values in the order of input density values for each color, and a range that the input density value of the correction data takes is determined. Patch data processing means for dividing into a plurality of regions according to the content of gradation processing performed after color, input image characteristics or density conversion;
Correction data determination means for determining whether the correction data satisfies a predetermined condition based on the plurality of average values for each of the plurality of regions;
Correction data generation means for correcting the density correction data table based on the result of determination by the correction data determination means and the correction data;
An image processing apparatus comprising: When the correction data determination unit divides the range taken by the input density value of the correction data into the plurality of regions, the number of divisions and the division of the range taken by the input density value of the correction data according to the characteristics of the color material The image processing apparatus according to claim 1, wherein the width is changed. When the correction data determination means divides the range taken by the input density value of the correction data into the plurality of areas, the number of divisions and the division of the range taken by the input density value of the correction data according to the characteristics of the input image The image processing apparatus according to claim 1, wherein the width is changed. The correction data determination means determines the input density of the correction data according to the content of gradation processing performed after density conversion when dividing the range taken by the input density value of the correction data into the plurality of areas. The image processing apparatus according to claim 1, wherein the number of divisions and the division width of a range that the value takes are changed. The predetermined condition is that the number of pieces of measurement data in which a difference from the plurality of average values among the plurality of measurement data is larger than a predetermined value is equal to or less than a predetermined threshold value. The image processing apparatus according to one. When the correction data determination unit determines that a certain area among the plurality of areas of the correction data satisfies the predetermined condition, the correction data generation unit converts the correction data of the area into the area. The image processing apparatus according to claim 1, wherein the image processing apparatus is treated as the corrected density correction data table. The correction data generation means, when the correction data determination means determines that a certain area among the plurality of areas of the correction data does not satisfy the predetermined condition, the plurality of average values of the area The image processing apparatus according to claim 1, wherein an approximate expression is calculated from the image data, and the density correction data table of the region is generated based on a curve obtained from the approximate expression. An image processing method for correcting a density correction data table used for density conversion of an input image,
A patch data forming step for forming patch data including a plurality of patches for the same color and the same input density value;
A plurality of measurement data generated by reading images of a plurality of patches formed on a recording medium based on the patch data is classified for each color and input density value, and the color and input density of the plurality of measurement data A plurality of average values for each value are calculated, correction data is generated for each color by arranging the plurality of average values in the order of input density values for each color, and a range that the input density value of the correction data takes is determined. Patch data processing step for dividing into a plurality of regions according to the content of gradation processing performed after color, input image characteristics or density conversion;
A correction data determination step for determining whether the correction data satisfies a predetermined condition based on the plurality of average values for each of the plurality of regions;
A correction data generation step for correcting the density correction data table based on the result of determination by the correction data determination step and the correction data;
An image processing method comprising: In the correction data determination step, when the range taken by the input density value of the correction data is divided into the plurality of regions, the number of divisions and the division of the range taken by the input density value of the correction data according to the characteristics of the color material The image processing method according to claim 8, wherein the width is changed. In the correction data determining step, when the range taken by the input density value of the correction data is divided into the plurality of regions, the number of divisions and the division of the range taken by the input density value of the correction data according to the characteristics of the input image The image processing method according to claim 8, wherein the width is changed. In the correction data determination step, when the range of the input density value of the correction data is divided into the plurality of areas, the input density of the correction data is determined according to the content of gradation processing performed after density conversion. The image processing method according to claim 8, wherein the number of divisions and the division width of the range that the value takes are changed. The predetermined condition is that the number of pieces of measurement data in which a difference from the plurality of average values among the plurality of measurement data is greater than a predetermined value is equal to or less than a predetermined threshold value. The image processing method as described in one. In the correction data generation step, when the correction data determination step determines that a certain area among the plurality of areas of the correction data satisfies the predetermined condition, the correction data generation step converts the correction data of the area into the area. The image processing method according to claim 8, wherein the image processing method is treated as the corrected density correction data table. In the correction data generation step, when the correction data determination step determines that a certain area among the plurality of areas of the correction data does not satisfy the predetermined condition, the plurality of average values of the area 14. The image processing method according to claim 8, wherein an approximate expression is calculated from the image, and the density correction data table of the region is generated based on a curve obtained from the approximate expression.   An image processing program for causing a computer to execute the image processing method according to any one of claims 8 to 14.   A computer-readable recording medium storing the image processing program according to claim 15.

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