JP2008015753A - Image data processing system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image data processing system capable of automatically executing image processing suitable for an image constitution object, depending on the type of the image constitution object. <P>SOLUTION: An image discriminating means 22 receives image data composed including color information, finds the color distribution based on the color information of the image data, and discriminates the image constitution object by referring to a color distribution storage means 25 for storing the image constitution object and the color distribution in advance based on the image constitution object. The image processing means performs image processing according to the image processing contents corresponding to the image constitution object determined by the image discriminating means, which is stored beforehand by a processing content storage means 26. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to an image data processing system that performs image processing on image data, and relates to an apparatus that performs image processing in accordance with an image configuration target such as a subject constituting an image.

  Conventionally, in the printing industry, digital data obtained by digitizing a positive film using a drum scanner or the like has been used as image data for a photographic document. In addition, image processing for optimizing color and gradation is performed on image data obtained by scanner decomposition. For example, a method of performing optimization by setting an optimal tone correction curve from the cumulative histogram of image data and converting the image data (see, for example, Patent Document 1) has been proposed. The above optimization has been performed by manually correcting the image processing software.

  On the other hand, due to the recent spread of digital cameras, higher performance and higher image quality, there is a tendency to increase the number of submissions using digital data obtained by digital cameras. This eliminates the need for the step of disassembling the positive film as in the prior art. However, images based on image data obtained with a digital camera are often not optimal images, such as gray balance being shifted, too bright, or too dark. Is necessary. Also in this case, manual correction is performed, and automation is desired.

  Further, the above-described optimization needs to be modified differently depending on the image configuration target. For example, how to apply sharpness differs depending on whether the image composition target is a metal or a motorcycle and a human being. In addition, in an image including a blue sky, blue is corrected so that the sky becomes empty, and in an image including a human skin color, the skin color is corrected. So, for example, “Food”, “Jewelry”, “White pottery”, “Standard skin”, “Bright skin”, “Dark skin”, “Night view”, “Machine”, or “Home appliance” There are some which classify images according to objects, prepare processing contents suitable for each in advance, and perform optimal processing on images by selecting from these (see, for example, Patent Document 2). ). According to this, optimal image processing can be performed according to the image composition target.

JP 2003-134341 A JP 2004-58438 A

  However, it is necessary to manually select the image composition target corresponding to the image to be processed while viewing the image, and automation of the determination of the image composition target is also desired.

  In many cases, the image data used for printing is so-called layout image data in which a plurality of images are laid out. In this case, the image composition target is determined according to each of the image data of the laid out images. This must be done and requires a lot of effort.

  Further, the classification of the image composition target and the processing contents differ depending on the user's preference and the like. Therefore, a system capable of classifying image constituents and performing image processing corresponding to the image constituents according to user preferences is desired.

  The present invention has been made in view of the above circumstances, and an object of the present invention is to provide an image data processing system capable of automatically performing image processing according to image configuration symmetry in accordance with an image configuration target. Is to provide.

  In order to solve the above-mentioned problem, the invention according to claim 1 corresponds to the image composition target and the color distribution storage means for preliminarily storing the color distribution based on the image composition target, and the image composition target and the image composition target. Processing content storage means for preliminarily storing image processing contents to be received; image data including color information is received; color distribution is obtained based on the color information of the image data; refer to the color distribution storage means Image determining means for determining an image composition target, and image processing means for performing image processing on the image data according to the image processing content corresponding to the determined image composition target stored in the processing content storage means, It is characterized by having.

  According to a second aspect of the present invention, there is provided color distribution storage means for storing in advance an image composition object and a color distribution based on the image composition object, and image processing contents corresponding to the image composition object and the image composition object. Processing content storage means for storing in advance and layout image data corresponding to a page including one or a plurality of image data including color information, and the color of the image data for each image data of the layout image data A color distribution is obtained based on the information, and an image discriminating unit that discriminates an image constituent by referring to the color distribution storage unit, and stores the processing image storage unit for each image data of the layout image data. And image processing means for performing image processing in accordance with the content of the image processing corresponding to the determined image composition target.

  According to a third aspect of the present invention, the color distribution is indicated by one or a plurality of colors, and the image determination means obtains the distribution of the one or more colors of the image data, and It is characterized by discrimination.

  According to a fourth aspect of the present invention, the color distribution is represented by a color system value.

  According to a fifth aspect of the present invention, the image discriminating unit obtains a color system value from the color information using a device profile representing a relationship between the color information and the color system value. It is a feature.

  The invention according to claim 6 is characterized in that the image processing means performs one or more of color correction processing, gradation correction processing, and sharpness enhancement processing according to the contents of the image processing. Yes.

  According to a seventh aspect of the present invention, the image composition target includes a subject, and the color distribution storage unit stores in advance the subject and a color distribution based on the subject.

  Further, the invention according to claim 8 is a color distribution change for changing a color distribution based on an image configuration object stored in the color distribution storage unit in accordance with an input unit and a change input from the input unit. The image discriminating unit performs the discrimination based on the changed color distribution when the color distribution changing unit changes.

  Further, the invention according to claim 9 is an input unit and a processing content changing unit for changing the image processing content for the image composition target stored in the processing content storage unit in accordance with the input of the change from the input unit. The image processing means performs image processing according to the changed image processing content when the change is made by the processing content changing means.

  According to the image data processing system of the present invention, it is possible to automatically discriminate an image constituent using the color distribution indicated by the color information constituting the image data, and it corresponds to the discriminated image constituent. Image processing stored in advance can be automatically performed.

  A feature of the present invention is that an image composition target is automatically determined for image data, and image processing corresponding to the image composition target is automatically performed. The image composition target is an object that constitutes an image. For example, in the case of an image obtained by photographing, the subject is the subject to be photographed. The subject is like “person”, “landscape”, “machine”, and the like. Further, the subject may be further classified into “person” with “standard skin person”, “light skin person”, “dark skin person”, for example. Further, the image composition target may include, for example, computer graphics created by using a PC (Personal Computer). In addition, the “image composition target” may be referred to as a “scene”.

  First, before describing the present invention, the values of the XYZ color system and the L * a * b * color system used in the following description will be described. The value of the L * a * b * color system is one of the values of the color system representing the color, and represents the color in the three-dimensional space of the L * axis, a * axis, and b * axis. Hue and saturation are represented by the a * b * plane, and L * is a value of a color characteristic orthogonal to the a * b * plane and representing lightness. In addition, the values of the L * a * b * color system are x (λ), y (defined by the CIE (Commission Internationale de l'Eclairage)) as equivalent to the sensitivity of the human eye. λ), z (λ) (in the CIE 1931, bar (-) is attached above x, y, z) The value of the XYZ color system obtained by integrating the amount of light with the spectral characteristics. It is based on. The X, Y, and Z values of the XYZ color system values are called color tristimulus values and represent colors in the three-dimensional space of the X, Y, and Z axes, where X is red The amount of light, Y corresponds to the amount of green light, and Z corresponds to the amount of blue-violet light. Further, since the value of the XYZ color system is obtained by integrating the light amount with the spectral characteristics as described above, it may be said to be a linear value with respect to the light amount.

  Further, from the X value, Y value, and Z value of the XYZ color system value, the L * value, a * value, b * value, or L * a * b * of the L * a * b * color system value From the L * value, a * value, and b * value of the color system value, the X value, Y value, and Z value of the XYZ color system value can be obtained by a predetermined arithmetic expression.

<First Embodiment>
Hereinafter, a first embodiment of an image data processing system according to the present invention will be described in detail with reference to the drawings.

<Control configuration>
An image data processing system as an embodiment according to the present invention will be described. The image data processing system according to the present embodiment includes a so-called PC (Personal Computer). The PC includes a computer main body, a keyboard, a monitor, and the like. A predetermined program is incorporated in the computer main body, and this program is executed to perform determination of an image configuration target described later and image processing corresponding to the image configuration target.

  The functions of the image data processing system according to this embodiment will be described with reference to FIG. FIG. 1 is a functional block diagram for explaining a control configuration of the image data processing system according to the first embodiment.

  The accepting unit 21 accepts layout image data and sends it to the image discriminating unit 22. The accepting means 21 is means for receiving layout image data transmitted from a terminal device via a network, or a medium on which layout image data is recorded, such as a CD-ROM (compact disk-read only memory). The recording medium is detachable, and is configured by means for reading photographic original RGB data written on the loaded recording medium. Further, it may be means for acquiring layout image data created using application software that operates in the image data processing system.

  The layout image data handled in the present embodiment is configured to include image data (hereinafter referred to as photographic original RGB data) indicating pixels with R (red), G (green), and B (blue) as color information. An image based on the photographic original RGB data is arranged at a desired position.

  The photographic original RGB data indicates a pixel by the intensity of each RGB light, and indicates the intensity as a gradation value. Here, the gradation value is a value that indicates the intensity of light step by step using a numerical value from 0 to 100 or from 0 to 255. For example, black is indicated as (R0, G0, B0), and white is indicated as (R255, G255, B255) when using gradation values 0 to 255.

  FIG. 2 shows an example of the configuration of layout image data. As shown in FIG. 2, the layout image data includes layout image data identification information (file name, etc.), layout information indicating the arrangement position of an image based on photographic original RGB data, and photographic original RGB data. This is equivalent to a page. FIG. 3 shows an example of the arrangement of images indicated by the layout image data. As shown in FIG. 3, an image based on, for example, photographic original RGB data is arranged in a page according to the layout information. The layout information is indicated by, for example, the coordinate position where the reference point is arranged with the upper left corner of the photographic original RGB data as the reference point. Moreover, it is not restricted to the coordinate position of this reference point, For example, the information etc. which show an area | region may be sufficient.

  The LUT storage unit 24 indicates the relationship between RGB and XYZ color system values, and stores a device profile of an RGB display for converting RGB into XYZ color system values. The device profile of the RGB display is composed of a gradation correction curve and a coefficient (value of 3 × 3 matrix), and is used by the image discrimination means 22 described later.

  The device profile of the RGB display is, for example, displaying a plurality of colors one by one on the display and measuring the X, Y, and Z values of the XYZ color system values with a measuring instrument, It was created based on. In addition, as a plurality of colors, white (R = G = B = 255), black (R = G = B = 0), and RGB single colors 0 to 255, which are divided into 10 equal parts, 0, 26 , 51,..., 230, 255 may be used in 10 levels (other colors are 0).

  The color distribution storage unit 25 stores an image configuration target and a color distribution based on the image configuration target (hereinafter sometimes referred to as a color distribution) in association with each other. FIG. 4 shows an example of the configuration of the color distribution storage means 25. As shown in FIG. 4, a subject as an image composition target is stored in association with a characteristic color distribution indicating an image including each subject. The subject is “person”, “landscape”, “white pottery”, or the like. Further, the color distribution is indicated by the ratio of pixels included in the range of the L * a * b * coordinate space. That is, the color distribution of the image composition target is indicated by the ratio of the colors constituting the image composition target, in other words, the color composition of the image composition target. For example, as shown in FIG. 4, for a subject “person”, pixels with color distributions “L *: 40 to 60, a *: 10 to 20 and b *: 20 to 30” are 0.2% or more, and L *: 10-20, a *: 30-40, and b *: 10-20 pixels are 0.05% or more. It is stored in advance.

  Here, L *: 40-60, a *: 10-20 and b *: 20-30 indicate skin color, L *: 10-20, a *: 30-40 and b *: 10-20 are red That is, it indicates the color of the lips. If pixels of these colors are included in a predetermined ratio or more, it is considered that skin and lips are present, and it can be determined that there is a high probability that the image is a person. Therefore, the color distribution indicates “person”.

  For example, the range of the skin color L * a * b * coordinate space is not limited to the above, and may be a wider range. Further, the skin color ranges are (1) L *: 40 to 60, a *: 10 to 20, b *: 20 to 30 (2) L *: 20 to 40, a *: 10 to 20, b *: 10 Two ranges such as ˜20 may be used, and the number of pixels falling in the two ranges may be summed up for determination. Moreover, you may make it discriminate | determine from a person, when either the conditions shown by (1) or the conditions shown by (2) are satisfy | filled. Furthermore, in addition to the skin color and the color of the lips, the black color distribution of the hair may be included. As a result, it is possible to discriminate even when the skin color, the color of the lips, the color of the hair, the difference in makeup, and the photographing conditions are different.

  In addition, the color distribution of “person” is shown as an example, but for other subjects as well, although not shown in detail, “landscape” is indicated by the ratio of blue and green pixels, or “white pottery” is displayed. It may be indicated by the ratio of white pixels.

  The image discriminating unit 22 discriminates the image composition target of each photographic original RGB data included in the layout image data. First, the L * a * b * color system value indicated by RGB of each pixel of the photographic original RGB data is obtained, and a function as a determination means for determining whether or not the condition of each color distribution shown in FIG. 4 is satisfied. If each color distribution is satisfied, the subject corresponding to the color distribution is discriminated as the image composition target of the photographic original RGB data.

  Here, the determination performed by the image determination unit 22 will be specifically described. First, for each pixel, an XYZ color system value is obtained from the RGB of each pixel by the following calculation procedure, and an L * a * b * color system value is calculated from the XYZ color system value.

  First, the value of R is converted to R2 by the gradation correction curve of the device profile of the RGB display stored in the LUT storage unit 24. FIG. 5 shows an example of the gradation correction curve, and the relationship between the R value of the pixel on the horizontal axis and the converted R2 on the vertical axis is shown by a curve. Similarly, G and B are converted to G2 and B2.

Next, the X value, the Y value, and the Z value of the values of the XYZ color system are obtained from R2, G2, and B2 using the following equation.
X = (0.4561 × R2 + 0.3209 × G2 + 0.1871 × B2) /0.9641×95.04
Y = (0.2446 × R2 + 0.6720 × G2 + 0.0832 × B2) /0.9998×100.0
Z = (0.0190 × R2 + 0.1069 × G2 + 0.6988 × B2) /0.8247×108.89
Here, the coefficients of 0.4561, 0.3209, 0.1871, 0.2446, 0.6720, 0.0832, 0.0190, 0.1069, and 0.6988 are RGB display as well as the gradation correction curve. The coefficients (3 × 3 matrix values) constituting the device profile are used.

Further, the L * value, a * value, and b * value of the L * a * b * color system value are obtained from the X value, Y value, and Z value of the XYZ color system value as shown below. .
When X / 95.04 is 0.008856 or less,
X2 = (X / 95.04) × 7.787 + 16/116
Otherwise,
X2 = (X / 95.04) ^ (1/3)
When Y / 100.0 is 0.008856 or less,
Y2 = (Y / 100.0) × 7.787 + 16/116
Otherwise,
Y2 = (Y / 100.0) ^ (1/3)
When Z / 108.89 is 0.008856 or less,
Z2 = (Z / 108.89) × 7.787 + 16/116
Otherwise,
Z2 = (Z / 108.89) ^ (1/3)
And X2, Y2, and Z2 are obtained,
L * = 116 × Y2-16
a * = 500 × (X2−Y2)
b * = 200 × (Y2-Z2)
Each value of L *, a *, b * is obtained by the following formula.

  Then, for example, by determining whether or not the ratio of the pixels included in the range shown in the color distribution for each subject shown in FIG. 4 satisfies the condition, the subject as the image configuration target of the image data is obtained.

  The processing content storage unit 26 stores the image configuration target and the image processing content corresponding to the image configuration target in association with each other. FIG. 6 shows an example of the configuration of the processing content storage unit 26. As shown in FIG. 6, image processing contents for optimizing an image including each subject are stored in association with the subject as an image configuration target. Regarding this correction, depending on the image composition target, for example, the image composition target may be different in how sharpness enhancement is applied between a person such as a metal or a motorcycle and a human, and an image including a blue sky is empty. It is determined in advance that blue is corrected so that the image looks natural, and an image including human skin color is corrected. For example, as shown in FIG. 6, for the subject “person”, contents such as “the gradation correction by the gradation correction curve (1) (not shown) and sharpness enhancement are weakened” are determined in advance. Is remembered.

  The image processing unit 23 performs image processing on each photographic original RGB data included in the layout image data according to the image processing content corresponding to the image configuration target of the determination result by the image determination unit 22 stored in the processing content storage unit 26. I do. Image processing includes, for example, color correction processing based on color conversion information such as RGB → RGB lookup table, γ correction using a tone correction curve, sharpness enhancement correction, and processing related to colors such as contrast.

  For example, when it is determined that the image composition target of one photographic original RGB data in the layout image data is “person”, RGB shown in FIG. 6 is applied to the photographic original RGB data by the gradation correction curve (1). A correction process is performed to reduce the sharpness enhancement.

  The RIP processing means 29 converts the RGB of the photographic original RGB data of the layout image data so as to indicate the gradation values of each color of CMYK, converts the layout image data into raster data (bitmap data), and for example, a printer or the like. Output to the image output device. The data converted into the raster data is called print image data. Further, the RIP processing unit 29 may be provided with a function as a halftoning processing unit that performs halftoning processing, and the halftone processing may be performed after conversion to raster data.

  Here, the gradation value of each color of CMYK is a value that indicates stepwise by setting white as 0 and solid as 100, or white as 0 and solid as 255. For example, white is indicated as (C0, M0, Y0, K0), and black is indicated as (C255, M255, Y255, K255) when the gradation values 0 to 255 are used. Also, the conversion from RGB to CMYK is performed by an RGB → CMYK lookup table indicating the conversion relationship between RGB and CMYK, or RGB → L * a indicating the relationship between RGB and L * a * b * color system values. * B * lookup table, L * a * b * → CMYK lookup table, CMYK → L * a * b * lookup table, etc. showing the relationship between CMYK and L * a * b * color system values This is done using a look-up table described in the color profile. These lookup tables used by the image processing unit 23 and the RIP processing unit 29 are stored in the LUT storage unit 24.

<Image data processing procedure>
Next, an image processing procedure in the image data processing system according to the present embodiment will be described with reference to FIGS. FIG. 7 is a flowchart showing a procedure of image processing of layout image data, FIG. 8 is a flowchart showing a procedure of determining an image composition target of photographic original RGB data, and FIG. 9 is an example of an image indicated by photographic original RGB data. .

  First, as shown in FIG. 7, the receiving means 21 receives layout image data. (Step S101. Hereinafter, step S101 is abbreviated as S101. Other steps are also abbreviated in the same manner.)

  Next, the image discriminating unit 22 discriminates an image composition target for each photographic original RGB data included in the received layout image data (S102).

  Here, the determination of the image composition target will be described with reference to FIG. Assume that the image composition target is sequentially determined for the photographic original RGB data included in the layout image data.

  First, the image discriminating unit 22 obtains an XYZ color system value of each pixel (S201). For each pixel, each value of R, G, B is converted into R2, G2, B2. This is performed using the gradation correction curve shown in FIG. Then, the value of the XYZ color system is obtained from R2, G2, and B2. Next, the value of the L * a * b * color system of each pixel is obtained from the value of the XYZ color system (S202).

  Then, the image discriminating means 22 obtains the distribution of the L * a * b * coordinate space for the photographic original RGB data (S203), and satisfies the condition of the color distribution for the image constituents indicated in the color distribution storage means 25. If the condition is satisfied (S204, Y), the image composition target of the color distribution is determined as the image composition target of the photographic original RGB data (S205). If the condition is not satisfied (S204, N), the distribution of the L * a * b * coordinate space of the color for the other subject is obtained and the determination is made in the same manner.

  Further, if there is unidentified photographic original RGB data (S206, Y), the image discrimination means 22 similarly discriminates the image composition target, and if not (S206, N), the discrimination ends.

  Here, the determination of the image composition target will be described using the photographic original RGB data constituting the image of FIG. 9 as an example. The image in FIG. 9 is a color image, and each pixel is indicated by RGB in 0 to 255 gradations (8 bits), and the size is 3072 pixels in the horizontal direction × 4096 pixels in the vertical direction.

  The values of the L * a * b * color system of each pixel of the photographic original RGB data are obtained as described above. First, the L * a * b * coordinate space of the color distribution shown in “person” shown in FIG. L *: 40 to 60, a *: 10 to 20, b *: 20 to 30% of pixels are 0.2% or more, L *: 10 to 20, a *: 30 to 40, b *: 10 It is determined whether or not 20 pixels satisfy the condition of 0.05% or more.

  From the obtained L * a * b * color system values of each pixel, the number of pixels included in the range for L *: 40 to 60, a *: 10 to 20, and b *: 20 to 30 is 226783 pixels. Therefore, the ratio [%] to the total of 3072 × 4096 pixels is 1.2%, which satisfies the condition “0.2% or more”. Further, for L *: 10 to 20, a *: 30 to 40, and b *: 10 to 20, there are 101022 pixels, and the ratio [%] to the total of 3072 × 4096 pixels is 0.8%, which is the condition “0 .05% or more ". Therefore, the image shown in FIG. 9 satisfies the color distribution condition of the “person” to be imaged. Therefore, the image composition target is determined to be “person”.

  Returning to FIG. 7, the image processing unit 23 corresponds to the image configuration target of the determination result by the image determination unit 22 stored in the processing content storage unit 26 for each photographic original RGB data included in the layout image data. Image processing is performed according to the processing content (S103).

  Further, the RIP processing means 29 converts the RGB of the photographic original RGB data of the layout image data so as to indicate the gradation values of each color of CMYK, and converts the layout image data into raster data (bitmap data), thereby printing. Image data is generated (S104). Then, the printing image data is output to an image output apparatus such as a printing machine.

  As described above, it is possible to automatically determine the image configuration target of the photographic original RGB data of the layout image data and perform image processing according to the determined image configuration target.

  In the above description, the layout image data has been described as an example. However, for example, for the image data composed of one photographic original RGB data, the above-described image configuration target is determined and the determined image configuration target is determined. The image processing to be performed can be applied.

  Further, although the color distribution is used to determine the image composition target, an RGB histogram may be used. In addition, the shooting condition may be used as a determination condition. In this case, the shooting condition at the time of shooting is attached to the photographic original RGB data and can be determined by comparing with the determination condition. Alternatively, the determination may be made based on a combination of color distribution, RGB histogram, or shooting conditions.

  In the above description, the image composition target is discriminated and image processing is performed on the photographic original RGB data having RGB as color information, but the color distribution is similarly obtained from CMYK for data having CMYK as color information. Discrimination of the image composition target and image processing can be performed.

<Second Embodiment>
Next, a second embodiment according to the present invention will be described with reference to FIG. In the following, detailed description of configurations substantially similar to those of the first embodiment will be omitted, and different points will be mainly described.

  In the present embodiment, it is possible to perform determination of an image composition target of photographic original RGB data or image processing corresponding to the image composition target according to the user's preference.

<Control configuration>
The input means 27 is for performing various inputs and operations, and outputs signals corresponding to these various inputs and operations.

  The changing unit 28 has a function as a color distribution changing unit that changes the color distribution for the image configuration object stored in the color distribution storage unit 25 in accordance with the input of the color distribution change input using the input unit 27.

  For example, the change of the color distribution for the image composition target includes a change of the range of the L * a * b * coordinate space of the color distribution, an addition of a range of another L * a * b * coordinate space, and the like. Further, it includes addition of discrimination conditions based on RGB histograms, addition of discrimination conditions based on shooting conditions, and the like.

  The changing unit 28 is a processing content changing unit that changes the image processing content for the image configuration object stored in the processing content storage unit 26 in accordance with the input of the image processing content change input using the input unit 27. It has a function.

  When the color distribution for the image composition target is changed, the image determination unit 22 determines the image configuration target based on the changed color distribution.

  When the image processing content for the image composition target is changed, the image processing unit 23 performs image processing based on the changed image processing content.

It is a functional block diagram showing the control structure of the image data processing system which concerns on 1st Embodiment. It is a figure which shows the structure of layout image data. It is a figure which shows an example of the image based on layout image data. It is a figure which shows an example of a structure of a color distribution storage means. It is a graph which shows an example of a gradation correction curve. It is a figure which shows an example of a structure of a process content storage means. It is a flowchart shown about the procedure of the image process of layout image data. It is a flowchart which shows the procedure of discrimination | determination of the image composition object of photographic original RGB data. It is a figure which shows an example of the image which photograph original RGB data shows. It is a functional block diagram showing the control structure of the image data processing system which concerns on 2nd Embodiment.

Explanation of symbols

21 receiving means 22 image discriminating means 23 image processing means 24 LUT storage means 25 color distribution storage means 26 processing content storage means 27 input means 28 changing means 29 RIP processing means

Claims (9)

Color distribution storage means for preliminarily storing an image composition object and a color distribution based on the image composition object;
Processing content storage means for storing in advance the image composition target and image processing content corresponding to the image composition target;
Image determination means for receiving image data including color information, obtaining a color distribution based on the color information of the image data, and determining an image configuration target with reference to the color distribution storage means;
An image data processing system comprising: image processing means for performing image processing on the image data in accordance with image processing contents corresponding to the determined image configuration object stored in the processing content storage means. Color distribution storage means for preliminarily storing an image composition object and a color distribution based on the image composition object;
Processing content storage means for storing in advance the image composition target and image processing content corresponding to the image composition target;
Receiving layout image data corresponding to a page including one or more image data including color information, and obtaining a color distribution for each image data of the layout image data based on the color information of the image data Image discrimination means for discriminating an image composition object with reference to the color distribution storage means;
Image processing means for performing image processing on each image data of the layout image data in accordance with the image processing content corresponding to the determined image composition object stored in the processing content storage means. Image data processing system. The color distribution is indicated by one or more colors;
The image data processing system according to claim 1, wherein the image determination unit determines the distribution by obtaining the distribution of the one or more colors of the image data.   The image data processing system according to claim 1, wherein the color distribution is represented by a color system value.   The image data processing system according to claim 4, wherein the image determination unit obtains a color system value from the color information using a device profile that represents a relationship between the color information and the color system value.   The image data according to any one of claims 1 to 5, wherein the image processing means performs one or more of color correction processing, gradation correction processing, and sharpness enhancement processing according to the content of the image processing. Processing system. The image composition target includes a subject,
The image data processing system according to claim 1, wherein the color distribution storage unit stores in advance a subject and a color distribution based on the subject. Input means;
Color distribution changing means for changing the color distribution based on the image composition object stored in the color distribution storage means according to the input of the change from the input means,
8. The image data processing according to claim 1, wherein the image determination unit performs the determination based on the changed color distribution when the color distribution change unit changes. system. Input means;
Processing content change means for changing the image processing content for the image composition object stored in the processing content storage means according to the input of the change from the input means,
The image data processing system according to any one of claims 1 to 8, wherein the image processing unit performs image processing according to the changed image processing content when the processing content changing unit changes.

Images