JP6729097B2 - Color processing device, color processing system, and color processing program - Google Patents

Description

The present invention relates to a color processing device, a color processing system, and a color processing program.

Patent Document 1 discloses an image processing apparatus that causes a reading unit to read a predetermined document and sets appropriate processing parameters, and an input unit that reads the document in advance by the reading unit and inputs the obtained image data. A determination unit that determines whether the input image data is within the input range of the reading unit, and a setting unit that sets the processing parameter using the image data within the input range based on the result of the determination. An image processing apparatus characterized by having is disclosed.

In Patent Document 2, the first color information in the first color space and the first color information is output in the second color space when input to a color-adjusting unit that performs image color adjustment. It is output when the first related information in which the first output color information as a target to be associated is associated, and the first color information and the first color information are input to the color adjustment means. Relative information acquisition unit that acquires second related information that associates the second output color information in the second color space of the image, and the first color information that is used in the second related information An output unit that outputs the second color information in the first color space, which has a reduced number, to the color-adjusting means, and the color-receiving area when the second color information is input to the color-adjusting means. An output color information acquisition unit that acquires third output color information in the second color space output by the adjusting unit, and the second relation newly applied based on the third output color information. Based on the prediction unit that predicts information by predicting the second output color information, and the second related information and the first related information that are predicted, the target in the first color space is used. There is disclosed a color processing device, comprising: a conversion relationship creating unit that creates a conversion relationship for performing color adjustment of a color adjusting unit.

In Patent Document 3, a plurality of read data on a device-dependent color space generated by reading a plurality of color patches, a plurality of reference data on a device-independent color space for the plurality of color patches, and Receiving means for receiving a plurality of specific color component data representing a specific color component for each color patch in a plurality of color patches, and a plurality of read data, the plurality of reference data and the plurality of specific color component data , Conversion information in which the presence or absence or the amount of a specific color component included in each of the color patches is reflected as information for converting the input data in the device-dependent color space into the output data in the device-independent color space. An image processing device is disclosed, which comprises: conversion information creating means for creating.

In Patent Document 4, a reading unit reads a document, a unit that stores the read value, and a unit that stores a correction target value for correcting the color conversion table applied to the reading unit. A means for preparing a correction lookup table for converting an image signal converted from a device-dependent color space into a device-independent color space according to the reading means into a device-independent color space; and the stored read value. Means for correcting the value of the device-independent color space of the correction look-up table according to the stored target value; and means for updating the color conversion table using the corrected correction look-up table. The image processing apparatus is characterized in that the original is composed of at least patches smaller than the number of grid points of the correction look-up table, and the read value and the target value are obtained according to the patch. ing.

JP-A-09-006956 JP, 2005-119422, A JP, 2005-073152, A JP, 2010-193076, A

Conventionally, for the purpose of color management of an image forming apparatus (so-called printer), a pattern image in which correction images are arranged is formed on a recording medium (for example, paper) and the color of the formed correction image is acquired. , The color of the image formed by the printer is evaluated. At this time, in order to perform the evaluation simply, an RGB value may be acquired by an image reading device (so-called scanner) instead of the colorimeter, and the evaluation may be performed by a Lab value estimated from the acquired RGB value. is there. The characteristics of the scanner may differ depending on the type of the scanner, and the relationship between the RGB value and the Lab value may differ depending on the physical characteristics of the printer such as the color material and the glossiness. Therefore, it is desirable to individually create the relationship between RGB and Lab values for each device and each image forming condition.

Here, CMYK values and RGB values correspond to C and R, M and G, and Y and B, respectively, but K does not correspond to any color. Therefore, in general, when the color to be converted does not include the K color and when it includes only the K color, the color can be accurately measured. However, when the color to be converted is a multi-order color including K color, the accuracy in measuring the color is reduced. For example, when a color composed of four colors of CMYK is read in a color composed of three colors of RGB, even if a correction image that does not include K color is read, it may be measured as a color that includes K color. .. In this case, there is a possibility that color management cannot be performed accurately.

The present invention compares the color of the first space with the color of the second space in comparison with the case where the first relationship information representing the relationship between the color of the first space and the color of the second space is not corrected based on the characteristic value of the specific color. It is an object of the present invention to provide a color processing device, a color processing system, and a color processing program capable of creating a color conversion model for converting to the above color with high accuracy.

The color processing apparatus according to claim 1, the characteristic values of the K color in the first relationship information indicating the relationship between the color of the second color space of the first color space, obtained by the measurement, the first color The first relationship information in which the K color value is corrected is acquired so that the characteristic value of the K color in the second relationship information representing the relationship between the color of the space and the color of the second color space is equivalent. using an acquisition unit, acquired by the acquiring means, the first relationship information value of K-color has been corrected, the color data obtained by combining the pre-Symbol second relationship information, the first Generating means for generating a color conversion model for converting the color of the color space into the color of the second color space.

The color processing apparatus according to claim 2 is the invention of claim 1, wherein said obtaining means, the characteristic values of the K color in corresponding color included in the first related information, included in the first relationship information A characteristic of the K color in the second relationship information, which is a correction image of at least a part of the colors and is obtained by reading the correction image formed by the image forming apparatus that is the target of color processing. The first relationship information in which the K color value is corrected so as to be equivalent to the value is acquired.

According to a third aspect of the present invention, in the color processing apparatus according to the second aspect, the acquisition unit sets K in a color other than the color corresponding to the color of the correction image among the colors included in the first relationship information. a color characteristic value of the as each color characteristic values of predicted from characteristic values of K color in the correction the second relationship information image obtained by reading a becomes equal, the value of K-color The corrected first relationship information is acquired.

The color processing apparatus according to claim 4 is the invention according to any one of claims 1-3, wherein the acquisition means, the concentration of K color that represent the variation in the concentration of K color in a plurality of types of original color For the range, the first relationship information in which the K color value is not corrected is acquired.

According to a fifth aspect of the present invention, in the color processing apparatus according to the first aspect of the present invention, the obtaining unit replaces the first relationship information in which the K color value is corrected with the K color value with correction. From the plurality of unrelated first relation information, the first relation information in which the K color characteristic value is closest to the K color characteristic value in the second relation information is acquired, and the generation means The color conversion model is generated using synthetic color data obtained by synthesizing the first relationship information acquired by the acquisition unit and the second relationship information .

According to a sixth aspect of the present invention, in the color processing apparatus according to the fifth aspect of the invention, the acquisition unit is configured such that the characteristic value of the K color in the color included in the first relationship information is the color value included in the first relationship information. Of the correction images of at least some of the colors, the K color characteristic value in the second relationship information obtained by reading the correction image formed by the image forming apparatus that is the target of color processing The closest first relationship information is acquired.

The color processing apparatus according to claim 7, in the invention of claim 5 or 6, wherein said acquisition means, processing for selecting on the basis of the characteristic value of the lowest color K color density of the color K, the concentration of K color process but it is selected based on the highest K colors color characteristic value, and the process of selecting, based on the gradation characteristics of a plurality of colors of K color characteristic value including the K color, either by treatment of The selected first relationship information is acquired.

A color processing system according to claim 8 includes: the color processing device according to any one of claims 2, 3, and 6; and a reading unit that reads a correction image formed by an image forming apparatus that is a target of color processing. , Is provided.

A color processing program according to a ninth aspect is a program for causing a computer to function as each unit included in the color processing apparatus according to any one of the first to seventh aspects.

According to the inventions of claims 1, 8 and 9, as compared with the case where the first relationship information representing the relationship between the color of the first space and the color of the second space is not corrected based on the characteristic value of K color, A color conversion model that converts the color of the first space into the color of the second space can be created with high accuracy.

According to the second aspect of the invention, the first space is compared with the case where the correction image of the color not included in the first relationship information indicating the relationship between the color of the first space and the color of the second space is used. It is possible to easily create a color conversion model that converts the color of the color into the color of the second space.

According to the invention of claim 3, the color of the first space is compared with the case where only the color of the image for correction is corrected in the first relationship information representing the relationship between the color of the first space and the color of the second space. It is possible to create a color conversion model for converting the color of the color into the color of the second space with high accuracy.

According to the invention of claim 4, the value of K color in the first relationship information representing the relationship between the color of the first space and the color of the second space is compared with the case where the value is corrected in the entire range of the density of K color. As a result, it is possible to prevent the color accuracy from deteriorating due to the characteristics of each type of document.

According to the invention of claim 5, the color of the first space is compared with the color of the second space as compared with the case where the first relationship information representing the relationship between the color of the first space and the color of the second space is fixed. A color conversion model for converting to can be created with high accuracy.

According to the invention of claim 6, as compared with the case where the correction image of the color not included in the first relationship information indicating the relationship between the color of the first space and the color of the second space is used, It is possible to easily create a color conversion model that converts the color of the color into the color of the second space.

According to the invention of claim 7, the first relationship information is compared with the case where the first relationship information representing the relationship between the color of the first space and the color of the second space is selected without using the density of K color. Can be selected appropriately.

1 is a block diagram showing an overall configuration of a color processing system according to an embodiment. It is a block diagram showing a functional composition of a color processing device concerning an embodiment. 3 is a block diagram showing an electrical configuration of the color processing device according to the embodiment. FIG. 6 is a flowchart showing a program flow of reference data set creation processing according to the embodiment. FIG. 5 is a schematic diagram for explaining a method of creating a reference data set according to the embodiment. FIG. 6 is a schematic diagram for explaining a method of creating a measurement data set according to the embodiment. It is a schematic diagram which shows the relationship between reference color data and measurement color data. A table showing an example of the relationship between Cin[%], the K density of the reference color data, and the K density of the measurement color data, and an example of the relationship between Cin[%] and Cout[%] of the K color according to the embodiment. Is. 6 is a graph showing an example of a relationship between Cin [%] of reference color data and lightness L* according to the embodiment. 6 is a graph showing an example of the relationship between Cin [%] of measured color data and lightness L* according to the embodiment. 6 is a graph in which an example of the relationship between Cin[%] of the reference color data and the lightness L* and an example of the relationship between Cin[%] of the measurement color data and the lightness L* are displayed in an overlapping manner according to the embodiment. .. 6 is a graph showing an example of a method of correcting the K color value of the reference color data according to the embodiment. 9 is a graph showing an example of a relationship between Cin[%] and Cout[%] of K color as a conversion LUT according to the embodiment. 6 is a flowchart showing a program flow of color conversion model creation processing according to the first embodiment. It is a schematic diagram for demonstrating the law enforcement method of a reference data set and a measurement data set which concerns on 1st Embodiment. FIG. 3 is a schematic diagram showing a relationship among reference color data, measurement color data, correction color data, and composite color data according to the first embodiment. 9 is a flowchart showing the flow of a program for color conversion model creation processing according to the second embodiment.

Hereinafter, the color processing system according to the present embodiment will be described with reference to the accompanying drawings.

[First Embodiment]

As shown in FIG. 1, the color processing system 1 according to the first embodiment includes a color processing device 2 described below and an image forming device 3 that forms an image on a sheet 4. Further, in the color processing system 1, the image formed on the sheet 4 by the image forming apparatus 3 (so-called scanner) 5 that is an example of a reading unit that reads the image formed on the sheet 4 by the image forming apparatus 3 and the image forming apparatus 3. It has a color measuring device 6 for measuring the color of an image. Examples of the color measuring device 6 include a spectrocolorimeter and an LED (light emitting diode) colorimeter.

As shown in FIG. 2, the color processing device 2 includes a correction image creation unit 12, a read data acquisition unit 14, a correction unit 16, a color conversion model generation unit 18, and a color processing data storage unit 22. .. The color processing data storage unit 22 also includes a reference color data storage unit 22a, a correction color data storage unit 22b, and a composite color data storage unit 22c.

As shown in FIG. 3, the color processing apparatus 2 according to this embodiment includes a CPU (Central Processing Unit) 30 that controls the entire apparatus, and each unit of the color processing apparatus 2 is realized by being controlled by the CPU 30. .. Further, the CPU 30 is connected to a ROM (Read Only Memory) 32 that stores programs and various information used for the processing of the CPU 30. Further, the CPU 30 connects a RAM (Random Access Memory) 34 that temporarily stores various data as a work area of the CPU 30 and a storage unit 36 such as a non-volatile memory that stores various information used for the processing of the CPU 30. Has been done. The color processing data storage unit 22 is provided in the storage unit 36.

Further, the CPU 30 is connected to a communication line I/F (interface) unit 38 that inputs/outputs data to/from an external device connected to the color processing device 2. Further, the CPU 30 is connected to a keyboard, a mouse, etc. for inputting data, and an operation display unit 40 having a display, etc. for displaying data.

The reference color data storage unit 22a stores reference color data that is an example of the first relationship information. The reference color data is information in which RGB values, K values, and Lab values related to a large number (for example, 1500 points) of colors are associated with each other.

Here, the flow of the reference color data creation process in which the color processing device 2 creates the reference color data will be described with reference to the flowchart shown in FIG.

The reference color data may be created using an image forming apparatus that is the target of color processing, or may be created using an image forming apparatus that is not the target of color processing. Further, the reference data may be created using a type of paper that is the target of color processing, or may be created using a type of paper that is not the target of color processing.

In step S101, the CPU 30 acquires the RGB data of the RGB space, which is an example of the first color space, obtained by reading the plurality of correction images formed by the image forming apparatus 3. The correction image 42 is an image for adjusting the color for each image forming apparatus or each type of paper. In the present embodiment, as shown in FIG. 5, the image forming apparatus 3 forms a pattern image 42A in which a plurality of correction images 42 having different colors are arranged in a grid pattern on the paper 4. In addition, the image reading device 5 creates the RGB data 44A of the pattern image 42A by reading the formed pattern image 42A. Further, the color processing unit 2 obtains the RGB data 44A of the pattern image 42 A from the image reading device 5.

In step S103, the CPU 30 acquires Lab data in the Lab space, which is an example of the second color space, obtained by measuring the color of the correction image formed by the image forming apparatus 3. In the present embodiment, as shown in FIG. 5, the image forming apparatus 3 forms the pattern image 42A on the paper 4. Further, the color measuring device 6 creates the Lab data 46A of the pattern image 42A by measuring the color of the formed pattern image 42A. Further, the color processing unit 2 obtains the Lab data 46A of the pattern image 42 A from a color measuring device 6.

In step S105, the CPU 30 causes the information indicating the drawing position of each correction image 42 included in the pattern image 42A, and the density (K value) of the specific color (K color in this embodiment) of each correction image 42. The specific color information 48A including the information indicating) is acquired.

In step S107, the CPU 30 selects one of the correction images 42 included in the pattern image 42A. In the present embodiment, each of the correction images 42 arranged in a grid is sequentially selected from the upper left.

In step S109, the CPU 30 determines whether or not the correction image 42 selected in step S107 includes K color based on the specific color information 48A acquired in step S105. If it is determined in step S109 that the K color is included (S109, Y), the process proceeds to step S111, and if it is determined that the K color is not included (S109, N), the process proceeds to step S113.

In step S111, the CPU 30 includes in the reference data set A information in which the RGB value of the selected correction image, the K value of the selected correction image, and the Lab value of the selected correction image are associated with each other, and The process proceeds to S115. As shown in FIG. 5, a reference data set A in which RGBK data 441A including K values in RGB data including K colors and Lab data 461A including K colors are associated with each other is generated.

In step S113, the CPU 30 includes, in the reference data set B, information in which the RGB value and the Lab value of the correction image selected in step S107 are associated with each other, and the process proceeds to step S115. As shown in FIG. 5, the reference data set B in which the RGB data 442A not including the K color and the Lab data 462A not including the K color are associated with each other is generated.

In step S115, it is determined whether or not there is an unprocessed correction image 42, that is, the correction image 42 that has not undergone the processes of steps S105 to S113. When it is determined in step S115 that there is an unprocessed correction image 42 (S115, Y), the process proceeds to step S105, the unprocessed correction image 42 is selected in step S105, and the processes of steps S107 to S113 are performed. .. If it is determined in step S115 that there is no unprocessed correction image 42 (S115, N), the process proceeds to step S117.

In step S117, the CPU 30 stores the reference data set A and the reference data set B as reference color data in the reference color data storage unit 22a, and ends the execution of the program of this reference color data creation process.

The reference color data thus created is stored in advance in the reference color data storage unit 22a. However, the method of creating the reference color data is not limited to this, and the reference color data created by another color processing device may be received from an external device.

As shown in FIG. 6, the correction image creation unit 12 includes a simple pattern image 42B in which some of the correction images 42 included in the above-described pattern image 42A are arranged in a grid pattern. To create. At this time, the correction image creation unit 12 also creates specific color information 48B including information indicating the density of the K color of each correction image 42. Further, the correction image creating unit 12 sends the image data indicating the created simple pattern image 42B to the image forming apparatus 3. The image forming apparatus 3 forms the simple pattern image 42B on the sheet 4 based on the received image data.

The read data acquisition unit 14 acquires the RGB data 44B in which the simple pattern image 42B formed on the paper 4 is read by the image reading device 5.

The read data acquisition unit 14 is image data obtained by converting the acquired RGB data 44B into each color of RGB data using a conversion model for converting the color of the RGB space into the color of the Lab space. Convert to Lab data 46B. In the present embodiment, the correspondence relationship between each color in the RGB space and each color in the Lab space is obtained in advance using the plurality of correction images 42, and the conversion model based on this correspondence relationship is stored in the color processing data storage unit 22. ing. Then, the read data acquisition unit 14 uses the stored conversion model to create Lab data 46B in which each color of the RGB data is converted into a color in the Lab space.

The read data acquisition unit 14 also sets the measurement data set C in which the RGBK data 461B including the K value to the RGB data 441B including the K color and the Lab data 461B including the K color are associated with each other, as an example of the second relationship information. Is created as measurement color data. The read data acquisition unit 14 also creates a measurement data set D in which the RGB data 442B that does not include K color and the Lab data 462B that does not include K color are associated with each other.

The correction unit 16 determines that the K color characteristic value (for example, lightness, density, color difference, etc.) of the reference color data stored in the reference color data storage unit 22a is the same as that of the measurement color data created by the read data acquisition unit 14. The K value in the reference color data is converted so as to approach the K color characteristic value. Further, the correction unit 16 stores the reference color data obtained by converting the K value as correction color data in the correction color data storage unit 22b.

That is, as shown in FIG. 7, the K values of the colors 52A, 52B... In the reference color data and the K values of the corresponding colors 54A, 54B. In such a case, it is desirable that the K value at the time of forming an image is set based on the K value in the measurement color data obtained by the measurement. When the difference between the K value in the reference color data and the K value in the measurement color data is calculated, if the K (density Cin) of the reference color data and the K (Cin) of the measurement color data are different, the RGB value of The difference includes an error. Therefore, it is desirable to align the K value corresponding to K(Cin) of the reference color data and the K value corresponding to K(Cin) of the measurement color data.

At this time, it is desirable to directly obtain the K value of the correction image 42 included in the simple pattern image 42B and create the color conversion model in the RGBK density state. However, it is not possible to directly obtain the K value of the correction image 42. Have difficulty. Therefore, in the present embodiment, the K value corresponding to K(Cin) of the reference color data and the K value corresponding to K(Cin) of the measurement color data are aligned in single color density.

As an example, FIG. 8 shows a table 56A showing the relationship between the lightness L* of K in the reference color data for K(Cin) and the lightness L* of K in the measurement color data for K(Cin), and Cin of K color. Table 56B showing the relationship between Cout and Cout is shown. Further, FIG. 9A shows a graph showing the relationship between K(Cin) and the lightness L* of K in the reference color data. Further, FIG. 9B shows a graph showing the relationship between K(Cin) and the lightness L* of K in the measured color data. Further, FIG. 9C shows a graph in which the graph of FIG. 9A and the graph of FIG. 9B are superimposed.

According to the example shown in FIG. 9C, in a range of K(Cin) of 10% or more, as K(Cin) becomes higher, the density of K in the measurement color data becomes lower than the density of K in the reference color data. ing. In this case, for K(Cin), the K color having a higher density than originally is extracted from the reference color data.

Therefore, in the present embodiment, as shown in FIG. 10, measured color data in which K(Cin) in the reference color data corresponds to the characteristic value of K color in this K(Cin) (here, lightness L*) A color conversion model is created after conversion into K(Cin) in the above. For example, referring to FIG. 10, since the lightness L* of Cin 80% in the reference color data corresponds to Cin 89% in the measurement color data, Cin of the reference color data is converted from 80% to 89%. In this way, each Cin value in the reference color data is converted into Cout based on Cin in the measured color data.

When Cin in the measured color data, which corresponds to the lightness L* of Cin in the reference color data, exceeds 100%, Cin in the reference color data is converted to 100%.

Further, in the present embodiment, the Cin of the reference color data is converted so that the lightness L* of Cin in the reference color data and the lightness L* of Cin in the measurement color data are equivalent, but the present invention is not limited to this. Cin of the reference color data may be converted so that the lightness L* of Cin in the reference color data approaches the lightness L* of Cin in the measurement color data.

Further, in the area of the paper 4 on the paper white (original color) side (area where the K density is low), the K value is low and the K value greatly varies depending on the characteristics of each type of paper. Therefore, within the range from the lowest value (0%) of Cin of the reference color data to the predetermined control point (the range representing the variation for each color type of the document), Cin is directly converted to Cout without conversion. To do. It should be noted that the control point mentioned here represents the maximum value of Cin of the colors of a plurality of types of originals that may be used in the image forming apparatus 3, and in the present embodiment, the control point is Cin=30%. As a result, by correcting the K color, it is possible to prevent the color accuracy from decreasing due to the characteristics of each type of the paper 4.

FIG. 11 shows, as a conversion LUT, a graph showing a relationship between Cin and Cout obtained by converting each Cin value in the reference color data based on Cin in the measurement color data. The correction unit 16 stores the reference color data obtained by converting the K value (Cin) of the reference color data into the K'value (Cout) based on the conversion LUT in the correction color data storage unit 22b as the correction color data.

The color conversion model generation unit 18 generates a color conversion model based on the measured color data created by the read data acquisition unit 14 and the corrected color data stored in the corrected color data storage unit 22b.

Next, a flow in which the color processing device 2 according to the present embodiment performs the color conversion model generation processing will be described with reference to the flowchart shown in FIG.

In the present embodiment, the program for the color conversion model generation processing is stored in the storage unit 36 in advance, but the present invention is not limited to this. For example, the program of the color conversion model generation process may be received from an external device via the communication line I/F unit 38 and executed. Further, the color conversion model generation process may be executed by reading the program of the color conversion model generation process recorded in a recording medium such as a CD-ROM by a CD-ROM drive or the like.

In the present embodiment, the color conversion model generation processing program is executed when an execution instruction is input by the user operating the operation display unit 40. However, the execution timing is not limited to this, and may be executed at the timing when the image forming apparatus 3 is activated, for example.

In step S201, the correction image creating unit 12 transmits the simple pattern image 42B including the plurality of correction images 42 to the image forming apparatus 3 and causes the paper 4 to form the simple pattern image 42B.

In step S203, the read data acquisition unit 14 creates a measurement data set C and a measurement data set D as measurement color data.

In step S205, the correction unit 16 selects either the reference data set A or the reference data set B as the reference color data.

In step S207, the correction unit 16 determines whether or not the reference data set A is selected. If it is determined that the reference data set A is selected in step S207 (S207, Y), the process proceeds to step S209, and if it is determined that the reference data set B is selected (S207, N), the process proceeds to step S213.

In step S209, the correction unit 16 converts the K value in the reference color data so that the characteristic value of the K color in the reference color data approaches the characteristic value of the K value in the measured color data. It is stored in the storage unit 22b.

In step S211, the color conversion model generation unit 18 combines the reference data set A stored in the corrected color data storage unit 22b and the measurement data set C. In this step, the K value in the reference data set A is the K'value corrected in step S209.

A method in which the color conversion model generation unit 18 synthesizes the reference data set A and the measurement data set C will be described with reference to FIG. 13.

First, the color conversion model generation unit 18 uses the reference data set A and the specific color information 48C obtained by converting the K value to the K′ value, and uses the RGBK-Lab of the color corresponding to the color included in the measurement data set C. The value is extracted as comparative color data. If the reference data set A does not have a color corresponding to the color included in the measurement data set C, the RGBK-Lab values of the other colors in the reference data set A are used to determine the RGBK-Lab values of the corresponding colors. May be predicted.

Further, the color conversion model generation unit 18 calculates, for each corresponding color, a measurement data set difference (RGBK-Lab) that is a difference between the color included in the measurement data set C and the color included in the comparative color data. To do.

In addition, the color conversion model generation unit 18 extends the measurement data set difference to the reference data set. For example, the difference between the colors included in the reference data set A is predicted from the difference between the colors included in the measurement data set C to obtain the reference data set difference (RGBK-Lab).

In addition, the color conversion model generation unit 18 adds the reference data set difference of the corresponding color to each color included in the reference data set A to combine the reference data set A and the measurement data set C into a combined image. Generate color data.

In step S213, the color conversion model generation unit 18 combines the reference data set B stored in the corrected color data storage unit 22b and the measurement data set D. In this case, the reference data set B and the measurement data set D do not include K color. In this case as well, the same method as in step S211 is used to generate combined color data in which the reference data set B and the measurement data set D are combined.

In step S215, the color conversion model generation unit 18 generates a color conversion model using the color data combined in step S211 or step S213, and the execution of the program of this color conversion model generation processing ends.

As described above, in the present embodiment, the reference color data corrected such that the characteristic value of the specific color in the reference color data approaches the characteristic value of the specific color in the measurement color data is acquired. Further, a color conversion model for converting a color in the RGB space into a color in the Lab space is generated from the acquired reference color data and the measured color data. More specifically, as shown in FIG. 14, the correction color data obtained by converting the K value is obtained using the reference color data and the measurement color data. In addition, synthetic color data is generated by synthesizing the obtained corrected color data and measured color data. As a result, even when the data amount of the reference color data is small, the K color can be appropriately corrected, and the color accuracy of the image formed on the paper 4 can be improved.

[Second Embodiment]

Next, the color processing system 1 according to the second embodiment will be described.

In the first embodiment, the case where the measurement color data is used to correct the K color in the reference color data and the color conversion model is generated using the corrected color data obtained by correcting the K color has been described. On the other hand, in the second embodiment, a case will be described in which one reference color data set is selected from a plurality of reference color data sets based on measured color data sets, and a color conversion model is generated using the selected reference color data sets.

As shown in FIGS. 1 and 2, the configuration of the color processing system 1 according to the second embodiment is the same as that of the color processing system 1 according to the first embodiment. Therefore, the description of each component is omitted here.

In the present embodiment, the reference color data storage unit 22a stores a plurality of reference data sets A acquired using a plurality of image forming apparatuses or a plurality of types of paper.

Next, a flow in which the color processing device 2 according to the present embodiment performs the color conversion model generation process will be described with reference to the flowchart shown in FIG.

In the present embodiment, the program for the color conversion model generation processing is stored in the storage unit 36 in advance, but the present invention is not limited to this. For example, the program of the color conversion model generation process may be received from an external device via the communication line I/F unit 38 and executed. Further, the color conversion model generation process may be executed by reading the program of the color conversion model generation process recorded in a recording medium such as a CD-ROM by a CD-ROM drive or the like.

In the present embodiment, the color conversion model generation processing program is executed when an execution instruction is input by the user operating the operation display unit 40. However, the execution timing is not limited to this, and may be executed at the timing when the image forming apparatus 3 is activated, for example.

In step S301, the correction image creating unit 12 transmits the simple pattern image 42B including the plurality of correction images 42 to the image forming apparatus 3, and causes the paper 4 to form the simple pattern image 42B.

In step S303, the read data acquisition unit 14 creates a measurement data set C and a measurement data set D as measurement color data.

In step S305, the correction unit 16 selects either the reference data set A or the reference data set B as the reference color data.

In step S307, the correction unit 16 determines whether the reference data set A is selected. If it is determined that the reference data set A is selected in step S307 (S307, Y), the process proceeds to step S309, and if it is determined that the reference data set B is selected (S307, N), the process proceeds to step S313.

In step S309, the color conversion model generation unit 18 causes the reference data set A whose K color characteristic value is closest to the measured data set C from the plurality of reference data sets A stored in the corrected color data storage unit 22b. Select. Examples of the selection method include the following (E) to (G).

(E) A paper white color having the lowest density of K color and having the closest characteristic value of K color is selected. That is, from the plurality of reference data sets A, the reference data set A having the characteristic value of Cin=0% (in this embodiment, the lightness L*) closest to the characteristic value of Cin=0% of the measurement data set C is selected. ..

(F) A color having the highest density of the K color and having the closest characteristic value of the K color is selected. That is, from the plurality of reference data sets A, the reference data set A having the characteristic value of Cin=100% (in the present embodiment, the lightness L*) closest to the characteristic value of Cin=100% of the measurement data set C is selected. ..

(G) Select the one having the closest gradation of a plurality of colors having different densities of K color. That is, from the plurality of reference data sets A, the reference having the tone characteristics of the plurality of Cin characteristic values (in the present embodiment, the lightness L*) closest to the tone characteristics of the corresponding Cin characteristic values of the measurement data set C. Select data set A.

In step S311, the color conversion model generation unit 18 generates combined color data in which the reference data set A and the measurement data set C are combined by the same method as in step S211.

In step S313, the color conversion model generation unit 18 combines the reference data set B stored in the corrected color data storage unit 22b and the measurement data set D by the same method as in step S211. In this case, the reference data set B and the measurement data set D do not include K color.

In step S315, the color conversion model generation unit 18 generates a color conversion model using the color data combined in step S311 or step S313, and the execution of the program of this color conversion model generation processing ends.

As described above, the color processing device 2 acquires the reference color data having the closest K color characteristic value from the plurality of reference color data, and uses the acquired reference color data and the measurement color data to perform the color conversion model. To generate. As a result, the K color is easily corrected by simply selecting the reference color data. For example, when an image is formed on three types of paper such as plain paper, coated paper, and matte paper, it is sufficient to prepare three types of reference color data. K color is corrected.

In the present embodiment, the case where the color processing device 2, the image forming device 3, the image reading device 5, and the color measuring device 6 are separately provided has been described, but the present invention is not limited to this. For example, the present invention is also applied to a color processing system in which the color processing device 2, the image forming device 3, the image reading device 5, and the color measuring device 6 are integrally formed. The present invention is also applied to a color processing system in which the color processing device 2, the image forming device 3, and the image reading device 5 are integrally formed, and the color measuring device 6 is connected to the color processing device 2. It

1 color processing system 2 color processing device 3 image forming device 4 paper 5 image reading device 6 color measuring device 12 correction image creation unit 14 read data acquisition unit 16 correction unit 18 conversion model creation unit 22 color processing data storage unit 22a reference color Data storage unit 22b Corrected color data storage unit 22c Composite color data storage unit 30 CPU
32 ROM
34 RAM
36 storage unit 38 communication line I/F unit 40 operation display unit

Claims (9)

The characteristic values of the K color in the first relationship information indicating the relationship between the color of the second color space of the first color space, obtained by the measurement, the color of the first color space of the second color space as is the characteristic value of the K color in the second relationship information indicating the relationship between the color becomes equivalent, and acquisition means for acquiring the first relationship information value of K-color has been corrected,
The acquired by acquisition means, by using said first relationship information value of K-color has been corrected, the color data obtained by combining the pre-Symbol second relationship information, the color of the first color space Generating means for generating a color conversion model for converting the color into a color of the second color space;
Color processing device equipped with. The acquisition means is a correction value image of the K color characteristic value of the color included in the first relationship information and at least a part of the colors included in the first relationship information, as the characteristic value of the K color in the second relation information obtained by reading the correction image formed by the image forming apparatus of interest and is equivalent, the first value of K-color has been corrected The color processing apparatus according to claim 1, wherein the color processing apparatus acquires related information. The acquisition unit comprises: a characteristic value of the K color in the color other than the color corresponding to the image for correction color among colors included in the first related information, wherein said obtained by scanning the image for correction The color processing according to claim 2, wherein the first relationship information in which the K color value is corrected is acquired so that the characteristic value of each color predicted from the characteristic value of the K color in the 2 relationship information becomes equivalent. apparatus. It said acquisition means, for a range of concentrations of K color that represent the variation in the concentration of K color in a plurality of types of the original color, claim to obtain the first relation information value of K-color is not corrected 1 3. The color processing device according to any one of 3 above. Instead of acquiring the first relationship information in which the K color value has been corrected , the acquisition unit uses the plurality of first relationship information in which the K color value has not been corrected in the second relationship information. The first relationship information in which the characteristic value of K color is the closest to the characteristic value of K color is acquired ,
The generation unit generates the color conversion model using combined color data obtained by combining the first relationship information acquired by the acquisition unit and the second relationship information . Color processing device. The acquisition unit is configured such that the characteristic value of K in the color included in the first relationship information is a correction image of at least a part of the colors included in the first relationship information, The color processing apparatus according to claim 5, wherein the first relationship information closest to the characteristic value of the K color in the second relationship information obtained by reading the correction image formed by the target image forming apparatus is acquired. .. Said acquisition means, processing for selecting on the basis of the characteristic value of the lowest color K color density of the color K, the process of selecting based on the characteristic value of K-color highest color density of the color K, and, K The color processing according to claim 5 or 6, wherein the first relationship information selected by any one of the processes of selecting based on the gradation characteristics of the characteristic values of a plurality of K colors including the color is acquired. apparatus. A color processing device according to any one of claims 2, 3, and 6,
A reading unit that reads a correction image formed by the image forming apparatus that is the target of color processing;
Color processing system with. A color processing program for causing a computer to function as each unit of the color processing apparatus according to claim 1.