JP2007088991A - Color reproduction characteristic acquisition system, image processing system, color reproduction characteristic acquisition method, and image processing method and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a color reproduction characteristic acquisition system capable of predicting colors more adapted to a user's use state. <P>SOLUTION: Upon the receipt of an input image, an image processing apparatus 20 references a stored color appearrance frequency for the user to analyze the tendency of colors used by the user. The image processing apparatus 20 establishes a weight factor to patch data stored by a patch data storage section 216 on the basis of the color appearrance frequency associated with the user and calculates a color correction factor by means of the multiple regression analysis by using the patch data to which the weight factor is set. Moreover, the image processing apparatus 20 applies color conversion processing to the input image by using the calculated correction factor to carry out prescribed correction processing. An image forming control apparatus forms an output image after the correction processing onto recording paper. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a color reproduction characteristic acquisition system for a printer, a facsimile machine, a copying machine, or the like.

Conventionally, in a color prediction method for color calibration such as calibration in an image output device such as a copying machine or a printer, output of color patches and colorimetry are performed in order to obtain a plurality of types of color data, and device characteristics. By acquiring information, a color correction parameter is acquired. The patch data used here needs to have a sufficient number and range of patches for the characteristics of the device to appear. Therefore, the patch data is arranged almost evenly in consideration of the color reproduction range of the device. Often become a patch set.
In addition, a method for accurately predicting color by increasing patches of an area such as skin color as an important color (important color gamut) has been invented. Since the color prediction used here needs to correspond to every input image, the prediction parameter set is given so as to be suitable for a large number of users (no failure).
However, the output image from the device varies depending on the user's tendency and is not necessarily an optimal prediction parameter set.

  The present invention has been made from the above-described background, and an object of the present invention is to provide a color reproduction characteristic acquisition system capable of performing color prediction more suitable for a user's usage situation.

  In order to achieve the above object, a color reproduction characteristic acquisition system according to the present invention includes a patch data storage unit that stores patch data, a color appearance frequency storage unit that stores a color appearance frequency according to a user, and the color Based on the color appearance frequency stored by the appearance frequency storage means, the analysis means for analyzing the tendency of the color used by the user, and the patch data storage means based on the result analyzed by the analysis means. Weight coefficient setting means for setting a weight coefficient for the patch data, and color correction coefficient calculation means for calculating a color correction coefficient using the patch data for which the weight coefficient is set by the weight coefficient setting means.

Preferably, the color appearance frequency storage means further stores the result analyzed by the analysis means.
Preferably, the analysis means analyzes the frequency with which the user uses each of the partial spaces of the color space.

  An image processing system according to the present invention includes a patch data storage unit that stores patch data, a color appearance frequency storage unit that stores a color appearance frequency according to a user, a reception unit that receives an input image and user information, Based on the color appearance frequency stored by the color appearance frequency storage means, the analysis means for analyzing the tendency of the color used by the user received by the reception means, and based on the result analyzed by the analysis means A color for calculating a color correction coefficient using weight coefficient setting means for setting a weight coefficient for patch data stored in the patch data storage means and patch data for which the weight coefficient is set by the weight coefficient setting means A color for performing color conversion processing on an input image using a correction coefficient calculation unit and the color correction coefficient calculated by the color correction coefficient calculation unit And a conversion means.

  The color reproduction characteristic acquisition method according to the present invention stores patch data, stores a color appearance frequency according to a user, and analyzes a tendency of a color used by the user based on the stored color appearance frequency. Then, based on the analyzed result, a weighting coefficient is set for the stored patch data, and a color correction coefficient is calculated using the patch data for which the weighting coefficient is set.

  Further, the image processing method according to the present invention stores patch data, stores color appearance frequency according to a user, accepts an input image and user information, and based on the stored color appearance frequency, Analyzing the tendency of the color used by the accepted user, setting a weighting factor to the stored patch data based on the analyzed result, and using the patch data in which the weighting factor is set The color correction coefficient is calculated, and color conversion processing is performed on the input image using the calculated color correction coefficient.

  The first program according to the present invention includes a patch data storage step for storing patch data in a color reproduction characteristic acquisition system including a computer, and a color appearance frequency storage step for storing a color appearance frequency according to a user. An analysis step for analyzing a tendency of a color used by a user based on the stored color appearance frequency, and a weight for setting a weighting factor for the stored patch data based on the analyzed result The computer of the color reproduction characteristic acquisition system is caused to execute a coefficient setting step and a color correction coefficient calculation step of calculating a color correction coefficient using the patch data in which the weighting coefficient is set.

  Furthermore, a second program according to the present invention includes a patch data storage step for storing patch data, a color appearance frequency storage step for storing a color appearance frequency according to a user, and an input in an image processing system including a computer. An accepting step for accepting an image and user information, an analyzing step for analyzing a tendency of colors used by the accepted user based on the stored color appearance frequency, and on the basis of the analyzed result, A weighting factor setting step for setting a weighting factor in the stored patch data; a color correction factor calculating step for calculating a color correction factor using the patch data in which the weighting factor is set; and the calculated color A color conversion step of performing color conversion processing on the input image using the correction coefficient; To be executed in.

  According to the color reproduction characteristic acquisition system according to the present invention, it is possible to perform color prediction more suitable for the use situation of the user.

FIG. 1 is a diagram showing a configuration of a tandem type image forming apparatus 10 according to an embodiment of the present invention.
As shown in FIG. 1, the image forming apparatus 10 includes an image reading unit 12, an image forming unit 14, an intermediate transfer belt 16, a paper tray 17, a paper transport path 18, a fixing device 19, an image processing device 20, and an image forming control device. 21. The image forming apparatus 10 has a function as a full-color copying machine using the image reading unit 12 and a function as a facsimile in addition to a printer function for printing image data received from a personal computer (not shown). It may be a multifunction machine.

  The outline of the image forming apparatus 10 will be described. An image reading unit 12, an image processing apparatus 20, and an image forming control apparatus 21 are disposed on the upper part of the image forming apparatus 10. The image reading unit 12 reads an image displayed on the document 30 and outputs it to the image processing apparatus 20. The image processing apparatus 20 performs a color conversion process and an image data input from the image reading unit 12 or image data input from a personal computer (not shown) or the like via a network line such as a LAN. Image processing such as color correction processing is performed and output to the image formation control device 21. The image forming control device 21 controls the image forming unit 14 based on the image data subjected to image processing. Note that the image formation control device 21 may be included in the image processing device 20 as a part of the image processing device 20.

  Below the image reading unit 12, a plurality of image forming units 14 are arranged corresponding to the colors constituting the color image. In this example, the first image forming unit 14K, the second image forming unit 14Y, and the third image forming corresponding to each color of black (K), yellow (Y), magenta (M), and cyan (C). The unit 14M and the fourth image forming unit 14C are arranged horizontally along the intermediate transfer belt 16 with a certain interval. The intermediate transfer belt 16 rotates as an intermediate transfer member in the direction of an arrow A in the figure, and these four image forming units 14K, 14Y, 14M, and 14C are configured based on the image data input from the image processing apparatus 20. The toner images are sequentially formed and transferred (primary transfer) to the intermediate transfer belt 16 at a timing at which the plurality of toner images are superimposed on each other. The order of the colors of the image forming units 14K, 14Y, 14M, and 14C is not limited to the order of black (K), yellow (Y), magenta (M), and cyan (C). ), Magenta (M), cyan (C), black (K), and the like.

  The sheet conveyance path 18 is disposed below the intermediate transfer belt 16. The recording paper 32 supplied from the paper tray 17 is transported on the paper transport path 18, and the toner images of each color transferred onto the intermediate transfer belt 16 are collectively transferred (secondary transfer). The transferred toner image is fixed by the fixing device 19 and discharged to the outside along the arrow B.

Next, each configuration of the image forming apparatus 10 will be described in detail.
As shown in FIG. 1, the image reading unit 12 includes a platen glass 124 on which a document 30 is placed, a platen cover 122 that presses the document 30 onto the platen glass 124, and a document 30 placed on the platen glass 124. And an image reading unit 130 for reading an image. The image reading unit 130 illuminates the original 30 placed on the platen glass 124 with a light source 132, and displays a reflected light image from the original 30 as a full rate mirror 134, a first half rate mirror 135, and a second half half. Scanning exposure is performed on an image reading element 138 made of a CCD or the like through a reduction optical system including a rate mirror 136 and an imaging lens 137, and the color material reflected light image of the document 30 is transferred to predetermined dots by the image reading element 138. It is configured to read at a density (for example, 16 dots / mm).

  The image processing device 20 performs predetermined image processing such as color conversion on image data read by the image reading unit 12 or image data input via a network line. The color material reflected light image of the document 30 read by the image reading unit 12 is, for example, document reflectance data of three colors of red (R), green (G), and blue (B). By the image processing by 20, the original color material gradation data of four colors of yellow (Y), magenta (M), cyan (C), and black (K) is converted.

  The image formation control device 21 generates a pulse signal according to the image data (YMCK) input from the image processing device 20 and outputs the pulse signal to the optical scanning device 140. More specifically, the image formation control device 21 performs a first optical scanning device 140K, a second optical scanning device 140Y, a third optical scanning device 140M, and a fourth optical scanning, which will be described later, based on the image data. A pulse signal is output to the device 140C to form an image.

The first image forming unit 14K, the second image forming unit 14Y, the third image forming unit 14M, and the fourth image forming unit 14C are arranged and formed in parallel at a certain interval in the horizontal direction. The configuration is almost the same except that the color of the image is different. Accordingly, the first image forming unit 14K will be described below. The configuration of each image forming unit 14 is distinguished by adding K, Y, M, or C.
The image forming unit 14K forms an electrostatic latent image by an optical scanning device 140K that scans a laser beam in accordance with image data input from the image processing device 20, and a laser beam scanned by the optical scanning device 140K. And an image forming apparatus 150K.

  The optical scanning device 140K modulates the semiconductor laser 142K according to the black (K) image data, and emits the laser light LB (K) from the semiconductor laser 142K according to the image data. The laser beam LB (K) emitted from the semiconductor laser 142K is applied to the rotary polygon mirror 146K via the first reflection mirror 143K and the second reflection mirror 144K, and is deflected and scanned by the rotation polygon mirror 146K. The light is irradiated onto the photosensitive drum 152K of the image forming apparatus 150K through the second reflecting mirror 144K, the third reflecting mirror 148K, and the fourth reflecting mirror 149K.

The image forming apparatus 150K includes a photosensitive drum 152K as an image carrier that rotates at a predetermined rotational speed in the direction of arrow A, and primary charging as a charging unit that uniformly charges the surface of the photosensitive drum 152K. And a developing device 156K for developing the electrostatic latent image formed on the photosensitive drum 154K, and a cleaning device 158K. The photosensitive drum 152K is uniformly charged by the scorotron 154K, and an electrostatic latent image is formed by the laser beam LB (K) irradiated by the optical scanning device 140K. The electrostatic latent image formed on the photosensitive drum 152K is developed with black (K) toner by the developing device 156K and transferred to the intermediate transfer belt 16. Residual toner, paper dust, and the like adhering to the photosensitive drum 152K after the toner image transfer process are removed by the cleaning device 158K.
The other image forming units 14Y, 14M, and 14C also form yellow (Y), magenta (M), and cyan (C) toner images in the same manner as described above, and intermediately transfer the formed toner images of the respective colors. Transfer to belt 16.

  The intermediate transfer belt 16 has a constant tension between the drive roll 164, the first idle roll 165, the steering roll 166, the second idle roll 167, the backup roll 168, and the third idle roll 169. The drive roll 164 is rotationally driven by a drive motor (not shown), and is circulated at a predetermined speed in the direction of arrow A. The intermediate transfer belt 16 is formed into an endless belt shape by, for example, forming a flexible synthetic resin film such as polyimide in a band shape and connecting both ends of the synthetic resin film formed in the band shape by welding or the like. It has been done.

  Further, the intermediate transfer belt 16 includes a first primary transfer roll 162K, a second primary transfer roll 162Y, a third primary transfer roll 162M, and a position facing the image forming units 14K, 14Y, 14M, and 14C, respectively. A fourth primary transfer roll 162C is provided, and the toner images of the respective colors formed on the photosensitive drums 152K, 152Y, 152M, and 152C are transferred onto the intermediate transfer belt 16 in a multiple manner by these primary transfer rolls 162. The The residual toner adhering to the intermediate transfer belt 16 is removed by a cleaning blade or brush of a belt cleaning device 189 provided downstream of the secondary transfer position.

In the paper transport path 18, a paper feed roller 180 for taking out the recording paper 32 from the paper tray 17, a first roller pair 181, a second roller pair 182 and a third roller pair 183 for paper transport, and a recording paper A registration roll 184 is provided that conveys 32 to the secondary transfer position at a predetermined timing.
In addition, a secondary transfer roll 185 that is in pressure contact with the backup roll 168 is disposed at the secondary transfer position on the paper transport path 18, and each color toner image transferred onto the intermediate transfer belt 16 is Secondary transfer is performed on the recording paper 32 by the pressing force and electrostatic force of the secondary transfer roll 185. The recording paper 32 onto which the toner image of each color is transferred is conveyed to the fixing device 19 by the first conveyance belt 186 and the second conveyance belt 187.
The fixing device 19 melts and fixes the toner to the recording paper 32 by performing heat treatment and pressure treatment on the recording paper 32 to which the toner images of the respective colors are transferred.

FIG. 2 is a diagram for explaining the color appearance frequency distribution and the weighting coefficient in the input image from the user.
As shown in FIG. 2, the image processing apparatus 20 according to the present invention stores colors used by the user, and analyzes the tendency of the colors used by each user based on the stored color appearance frequency. The image processing apparatus 20 divides a predetermined color space into a plurality of partial spaces, and analyzes the frequency with which the user uses the partial space of the color space in each of the divided partial spaces. This color space may be an RGB color space or a YMCK color space. The color space may be a device-independent color space such as CIELAB space.

In the example of FIG. 2, the color space is divided into 16 partial spaces, and the appearance frequency is stored in each partial space. When the image is input, the image processing apparatus 20 updates the color appearance frequency based on the color used in the image.
In addition, when an image is input, the image processing apparatus 20 sets a weighting factor in the stored color calibration patch data based on the stored color appearance frequency. The curve shown in FIG. 2 shows the weighting factor. The weighting factor is calculated using a smooth bell function centered on a predetermined color in each partial space. Each pixel value of the input image is set with a weighting coefficient calculated using a bell-type function corresponding to the color appearance frequency in the partial space of the color space.

FIG. 3 is a diagram illustrating the relationship between the appearance frequency and the weighting coefficient.
As shown in FIG. 3, the weighting coefficient increases as the appearance frequency increases. For this reason, in a partial space with a high appearance frequency, a large weight coefficient is set for the patch data. In a partial space with a small appearance frequency, a small weighting factor is set for the patch data. For this reason, a prediction error becomes small in the partial space with a large appearance frequency.

Since the weighting coefficient is set based on the input image data from the user, the color correction coefficient described later is customized for each user, and color conversion, color prediction, and the like are performed in a form adapted to the usage situation of the user. For example, when the user uses a lot of flesh-colored images, the color appearance frequency increases in the partial space including the flesh-color, so the flesh-color prediction error is small.
Note that the graph shown in FIG. 3 monotonically increases, but the graph is not limited to this example.

FIG. 4 is a block diagram illustrating a functional configuration of the image processing apparatus 20.
As illustrated in FIG. 4, the image processing apparatus 20 includes a reception unit 200, a color space conversion unit 202, a correction unit 204, a data output unit 206, an analysis unit 208, a weighting coefficient setting unit 210, a correction coefficient calculation unit 212, a color appearance A frequency storage unit 214 and a patch data storage unit 216 are included.
Each of the above-described components included in the image processing apparatus 20 may be realized by software such as a CPU, a memory, and a program, or may be realized by hardware such as an ASIC. Further, the image processing apparatus 20 may be included not only in the image forming apparatus 10 but also in a personal computer, for example.

  In the image processing apparatus 20, the color appearance frequency storage unit 214 stores the color appearance frequency (FIG. 2) according to the user. The color appearance frequency storage unit 214 divides the color space into a plurality of partial spaces, and stores the appearance frequency of the color in each of the divided partial spaces according to the user. The color appearance frequency storage unit 214 is realized by a recording device (not shown) such as an HDD or a memory.

  The patch data storage unit 216 stores a plurality of patch data. The patch data is a pair of color patch data obtained from the input image and colorimetric values of the color patch. The patch data storage unit 216 may store the image portion analyzed by the analysis unit 208 described later as patch data. These patch data are used with weighting factors set by a weighting factor setting unit 210 described later.

  The receiving unit 200 receives an input image from the image reading unit 12 shown in FIG. 1 or the user's personal computer, and outputs the input image to the color space conversion unit 202. The input image data is, for example, an image that is represented by 8 bits for each of RGB and belongs to the sRGB space. In addition, the reception unit 200 receives user information (user identifier) that identifies a user who is a transmission source of the image, and outputs an input image and user information to the analysis unit 208.

  The analysis unit 208 analyzes the tendency of the color used by the user based on the color appearance frequency stored in the color appearance frequency storage unit 214. Preferably, the analysis unit 208 analyzes the frequency with which the user uses each partial space of the color space. The analysis unit 208 may analyze the input image input from the reception unit 200 in the RGB color space, or may analyze after converting the input image into the YMCK color space. The analysis unit 208 outputs the analyzed color appearance frequency to the weighting coefficient setting unit 210.

  The analysis unit 208 analyzes the color used in the input image input from the reception unit 200, and updates the color appearance frequency stored in the color appearance frequency storage unit 214 according to the user. Specifically, the analysis unit 208 increases the color appearance frequency of the partial space corresponding to the color included in the input image.

  Further, the analysis unit 208 analyzes a uniform data location in the input image input from the reception unit 200. More specifically, the analysis unit 208 analyzes the input image in the frequency domain, generates a difference image between the input image and a low-frequency image obtained by removing high-frequency components from the input image, and generates a low-frequency portion (that is, The image smooth portion is specified. The analysis unit 208 acquires, as patch data, an image portion of the analyzed uniform portion of the data that is equal to or larger than a predetermined range, and stores it in the patch data storage unit 216.

  The weighting factor setting unit 210 sets a weighting factor for the patch data stored in the patch data storage unit 216 based on the result analyzed by the analysis unit 208. More specifically, the weighting factor setting unit 210 refers to the color appearance frequency (FIG. 2), and corresponds to the region so that the color used more frequently by the user is more strongly affected by the input image data. Set a weighting factor for patch data. The weighting factor setting unit 210 outputs the patch data in which the weighting factor is set to the correction factor calculation unit 212.

  The correction coefficient calculation unit 212 calculates a color correction coefficient using the patch data for which the weighting coefficient is set by the weighting coefficient setting unit 210, and outputs the color correction coefficient to the color space conversion unit 202. More specifically, the correction coefficient calculation unit 212 calculates a color correction coefficient by applying multiple regression analysis. Here, considering the relationship between the CIELAB (L *, a *, b *) color space, which is a colorimetric value, and the YMCK color space of the color system suitable for print processing, let F be a mapping of the color prediction model. The relationship between the two color spaces is expressed by the following equation.

  (L *, a *, b *) = F (Y, M, C, K) (1)

Here, F is a set of correction coefficients.
The correction coefficient calculation unit 212 performs color prediction for the CIELAB color space using the patch data to which the weight coefficient is set, and the square sum of the distance between the predicted value and the stored patch data value is obtained. The correction coefficient is calculated so as to be minimized.
The color space is not limited to these two color spaces. For example, the CIEXYZ color space may be used as a device-independent color space, and the RGB color space is used as a device-dependent color space. May be.

  The color space conversion unit 202 performs color conversion processing on the input image using the correction coefficient input from the correction coefficient calculation unit 212 and outputs the input image to the correction unit 204. The color space conversion unit 202 converts, for example, an input image (RGB) into a CIELAB (L *, a *, b *) color space (or CIEXYZ) that is a colorimetric value using the input correction coefficient, The converted image data in the CIELAB color space is converted into image data in a color system YMCK color space suitable for printing processing.

The correction unit 204 corrects the input image data to a gradation suitable for the printing process, and outputs it to the data output unit 206. Note that the correction unit 204 may perform color correction processing using the patch data stored in the patch data storage unit 216.
The data output unit 206 outputs the image data in the YMCK color space input from the correction unit 204 to the image formation control device 21. The data output unit 206 may output the input image data to a memory for storing image data.

FIG. 5 is a flowchart showing the operation (S10) of the image processing apparatus 20.
As shown in FIG. 5, in step 100 (S 100), the user makes a print request via the personal computer or the image reading unit 12. When the input image data is input, the receiving unit 200 acquires the input image data via the network or the image reading unit 12, and receives the received image data (for example, 8 bits for each of RGB) as a color space conversion unit 202. Output for. The receiving unit 200 outputs the input image and user information (user identifier) included in the input image data or user information received together with the input image data to the analyzing unit 208.

  In step 102 (S102), the analysis unit 208 refers to the color appearance frequency of the user stored in the color appearance frequency storage unit 214 and analyzes the tendency of colors used by the user. The analysis unit 208 outputs the color appearance frequency of each partial space of the color space to the weighting coefficient setting unit 210. The analysis unit 208 accumulates and updates the color appearance frequency related to the user stored in the color appearance frequency storage unit 214 based on the color used in the input image input this time. Note that the analysis unit 208 may acquire an image portion that can be used as patch data from the input image and newly store it in the patch data storage unit 216.

In step 104 (S104), the weighting factor setting unit 210 sets a weighting factor for the patch data stored in the patch data storage unit 216 based on the color appearance frequency related to the user input from the analysis unit 208, and These patch data are output to the correction coefficient calculation unit 212.
In step 106 (S106), the correction coefficient calculation unit 212 calculates a color correction coefficient by multiple regression analysis using the patch data after setting the weighting coefficient input from the weighting coefficient setting unit 210. The correction coefficient calculation unit 212 outputs the calculated correction coefficient to the color space conversion unit 202.

In step 108 (S108), the color space conversion unit 202 performs color conversion processing on the input image using the correction coefficient input from the correction coefficient calculation unit 212, and outputs the result to the correction unit 204.
In step 110 (S110), the correction unit 204 performs predetermined color correction processing and outputs output image data to the data output unit 206.
In step 112 (S112), the data output unit 206 outputs the output image data input from the correction unit 204 to the image formation control device 21, and the image formation control device 21 controls the image formation unit 14. Thus, an image is formed on the recording paper 32.

  As described above, the image processing apparatus 20 (color restriction characteristic acquisition system) according to the present invention stores patch data, stores the appearance frequency of the color according to the user, and the user's appearance based on the color appearance frequency. Analyzing the tendency of the color to be used, setting the weighting factor for the stored patch data based on the analysis result, and calculating the color correction coefficient using the patch data for which the weighting factor is set. The color prediction suitable for the use situation of can be performed.

  Since the image processing apparatus 20 analyzes the frequency with which the user uses each of the subspaces of the color space, a larger weighting factor is set for the important color range used by the user, and the color corresponding to the user is set. Prediction processing can be performed. Further, since the image processing apparatus 20 further stores the analysis result of the color usage frequency, the tendency of the color used by the user can be efficiently reflected.

  Accordingly, the image processing apparatus 20 according to the present invention, for example, has a large solid density usage range for users who often use CG, and thus can use a larger weighting coefficient in this range. In addition, for example, in the case of a user who often uses photographic images, the image processing apparatus 20 can perform color prediction processing with emphasis on halftone color prediction.

1 is a diagram illustrating a configuration of a tandem-type image forming apparatus 10 according to an embodiment of the present invention. It is a figure explaining the color appearance frequency distribution and the weighting coefficient in the input image from a user. It is a figure which shows the relationship between appearance frequency and a weighting coefficient. 3 is a block diagram illustrating a functional configuration of the image processing apparatus 20. FIG. It is a flowchart which shows operation | movement (S10) of the image processing apparatus 20. FIG.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Image forming apparatus 12 Image reading unit 14 Image forming unit 20 Image processing apparatus 21 Image formation control apparatus 32 Recording paper 200 Reception part 202 Color space conversion part 204 Color correction part 204 Correction part 206 Data output part 208 Analysis part 210 Weight coefficient setting Unit 212 correction coefficient calculation unit 214 color appearance frequency storage unit 216 patch data storage unit

Claims (8)

Patch data storage means for storing patch data;
Color appearance frequency storage means for storing the appearance frequency of the color according to the user;
Analysis means for analyzing the tendency of the color used by the user based on the color appearance frequency stored by the color appearance frequency storage means;
A weighting factor setting unit that sets a weighting factor for the patch data stored in the patch data storage unit, based on the result analyzed by the analyzing unit;
A color reproduction characteristic acquisition system comprising: color correction coefficient calculation means for calculating a color correction coefficient using patch data for which a weight coefficient is set by the weight coefficient setting means. The color reproduction characteristic acquisition system according to claim 1, wherein the color appearance frequency storage unit further stores a result analyzed by the analysis unit. The color reproduction characteristic acquisition system according to claim 1, wherein the analysis unit analyzes a frequency with which a user uses each of the partial spaces of the color space. Patch data storage means for storing patch data;
Color appearance frequency storage means for storing the appearance frequency of the color according to the user;
Receiving means for receiving an input image and user information;
Based on the color appearance frequency stored by the color appearance frequency storage means, an analysis means for analyzing the tendency of the color used by the user received by the reception means;
A weighting factor setting unit that sets a weighting factor for the patch data stored in the patch data storage unit, based on the result analyzed by the analyzing unit;
A color correction coefficient calculating means for calculating a color correction coefficient using the patch data for which the weight coefficient is set by the weight coefficient setting means;
An image processing system comprising: color conversion means for performing color conversion processing on an input image using the color correction coefficient calculated by the color correction coefficient calculation means. Store patch data,
Store the frequency of color appearance according to the user,
Based on the stored color appearance frequency, analyze the tendency of the color used by the user,
Based on the analyzed result, a weighting factor is set for the stored patch data,
A color reproduction characteristic acquisition method for calculating a color correction coefficient using patch data in which the weight coefficient is set. Store patch data,
Store the frequency of color appearance according to the user,
Accept input image and user information,
Based on the stored color appearance frequency, analyze the tendency of the color used by the accepted user,
Based on the analyzed result, a weighting factor is set for the stored patch data,
Using the patch data set with the weight coefficient, a color correction coefficient is calculated,
An image processing method for performing color conversion processing on an input image using the calculated color correction coefficient. In a color reproduction characteristic acquisition system including a computer,
A patch data storage step for storing patch data;
A color appearance frequency storage step for storing a color appearance frequency according to a user;
Based on the stored color appearance frequency, an analysis step of analyzing a color tendency used by the user;
A weighting factor setting step for setting a weighting factor in the stored patch data based on the analyzed result;
A program that causes a computer of the color reproduction characteristic acquisition system to execute a color correction coefficient calculation step of calculating a color correction coefficient using patch data in which the weighting coefficient is set. In an image processing system including a computer,
A patch data storage step for storing patch data;
A color appearance frequency storage step for storing a color appearance frequency according to a user;
A reception step for receiving an input image and user information;
Based on the stored color appearance frequency, an analysis step of analyzing a tendency of a color used by the received user;
A weighting factor setting step for setting a weighting factor in the stored patch data based on the analyzed result;
A color correction coefficient calculating step of calculating a color correction coefficient using the patch data in which the weighting coefficient is set;
A program that causes a computer of the image processing system to execute a color conversion step of performing a color conversion process on an input image using the calculated color correction coefficient.

Images