JP5957270B2 - Image processing apparatus and image processing program - Google Patents

Description

  The present invention relates to an image processing apparatus and an image processing program.

  Conventionally, a color distribution in a room or an image is closely related to a psychological state based on human color recognition, and various techniques for objectively measuring the relationship have been developed.

  For example, the color data of the imaged image is used to measure the colors distributed in the image, and plotted on a chromaticity diagram to be decomposed into a plurality of color groups and the number of colors and vividness There is a technique for calculating the visual comfort level by calculating (see Patent Document 1, etc.).

JP 2005-283184 A

  By the way, it is considered that the psychological state based on human color recognition is determined by the harmony of several colors representing the image rather than the color distribution of the entire image. However, the visual comfort level calculated based on the distribution of the entire image on the chromaticity diagram as in the prior art may not always match the psychological state based on actual human color recognition.

  SUMMARY OF THE INVENTION In view of the above-described problems of the prior art, an object of the present invention is to provide a technique capable of evaluating the color harmony of an image in consideration of human color recognition.

An aspect of the image processing apparatus illustrating the present invention includes an image dividing unit that divides an image into a plurality of image regions , coordinates in a color space of colors of the image regions , and a color tone and a color name corresponding to the coordinates. A calculation unit to be obtained, a plurality of extraction target areas among a plurality of image areas, a harmony evaluation section for evaluating color harmony in an image based on the coordinates of the extracted plurality of target areas, coordinates, color tone, and color name that having a an area coupling unit coupling the image area adjacent to the image area on the basis of.

  The harmony evaluation unit may extract a plurality of target regions based on the sizes of the plurality of image regions.

  The harmony evaluation unit may evaluate the color harmony in the image by obtaining the harmony relation of each of the combinations of the two target areas in the plurality of target areas based on the relative positional relationship of the coordinates.

Another aspect of the image processing apparatus exemplifying the present invention includes an image dividing unit that divides an image into a plurality of image regions, a calculation unit that obtains coordinates in a color space of colors of the image regions, and a plurality of image regions. Among the target areas to be evaluated, a plurality of target areas are extracted, and from the relative positional relationship of the coordinates in the combination of the two target areas in the plurality of target areas , the harmony relationship of the combination is the same with the same color between the two target areas. Harmony evaluation unit that evaluates the color harmony in the image by calculating the frequency of the same harmony, similar harmony and contrast harmony in multiple target areas, as harmony, similar harmony, or contrasting harmony And have .

  The harmony evaluation unit may calculate the frequencies Ri, Rs, and Rc of the same harmony, similar harmony, and contrast harmony using the following equations.

Note that N indicates the number of target regions, and Ni, Ns, and Nc indicate the number of combinations that are the same harmony, similar harmony, and contrast harmony in a plurality of target regions.

An aspect of the image processing program illustrating the present invention includes an input procedure for reading an image, an image division procedure for dividing an image into a plurality of image areas , coordinates in a color space of colors of the image areas, and a color tone corresponding to the coordinates. and calculation procedure for determining a color name, a plurality of extracted as the target area to be evaluated among the plurality of image regions, harmony evaluation procedure for evaluating the color harmony in the image based on the coordinates of the extracted plurality of target areas, coordinates, color And a region combining procedure for combining the image region and the adjacent image region based on the color name .
The harmony evaluation procedure may extract a plurality of target areas based on the sizes of the plurality of image areas.

  According to the present invention, it is possible to evaluate the color harmony of an image in consideration of human color recognition.

1 is a block diagram showing a configuration of a computer according to an embodiment of the present invention. The flowchart which shows the image processing by the computer which concerns on one Embodiment The figure which shows an example of a Moon-Spencer model

  FIG. 1 shows a configuration of a computer 100 that operates as an image processing apparatus according to an embodiment of the present invention.

  As shown in FIG. 1A, the computer 100 according to this embodiment includes a CPU 10, a storage unit 20, an input / output interface (input / output I / F) 30, and a bus 40. The CPU 10, the storage unit 20, and the input / output The I / F 30 is connected via the bus 40 so that information can be transmitted. The computer 100 is connected to an output device 50 for displaying the progress of image processing and processing results, and an input device 60 for receiving input from the user, via the input / output I / F 30. As the output device 50, a general liquid crystal monitor, a printer, or the like can be appropriately selected and used as the input device 60, such as a keyboard or a mouse.

  The CPU 10 is a microprocessor that executes a control program stored in the storage unit 20 and controls each unit of the computer 100. Further, the CPU 10 executes the image processing program stored in the storage unit 20 on the basis of the instruction from the user received via the input device 60, thereby dividing the image as shown in FIG. The unit 11, the calculation unit 12, the region combination unit 13, and the harmony evaluation unit 14 operate. The CPU 10 displays the image processing result on the output device 50. The operations of the image dividing unit 11, the calculating unit 12, the region combining unit 13, and the harmony evaluation unit 14 will be described later.

  The storage unit 20 stores an image to be processed and data relating to Japanese Industrial Standard (JIS) color, which will be described later, together with the control program and the image processing program. Programs and various data stored in the storage unit 20 can be referred to as appropriate from the CPU 10 via the bus 40. A storage device such as a general hard disk device or magneto-optical disk device can be selected and used for the storage unit 20.

  Next, image processing by the computer 100 will be described with reference to the flowchart of FIG. It is assumed that the image to be processed by the computer 100 is stored in the storage unit 20 in advance. The processing target image may be a still image or a moving image frame.

  A user inputs an image processing program command using the input device 60 or double-clicks an icon of the program to issue a program start command. The CPU 10 receives the command through the input / output I / F 30 and executes the image processing program stored in the storage unit 20. CPU10 starts the process from step S101.

  Step S101: The CPU 10 reads an image to be processed stored in the storage unit 20.

  Step S102: The image dividing unit 11 of the CPU 10 divides the read image into a plurality of image areas using a known method. In this embodiment, as a known method, a split and merge (Split & Marge) method and a watershed method are used in combination, and the image dividing unit 11 divides an image based on feature amounts such as image edge and saturation. It shall be. The CPU 10 outputs and displays the division result by the image dividing unit 11 on the output device 50.

  Step S103: The calculation unit 12 of the CPU 10 obtains a color value that is the coordinates of the Munsell color system for each image region divided by the image division unit 11. For this purpose, the calculation unit 12 obtains and acquires the average value of the pixel values in each image region for each of the RGB color components. For example, the calculation unit 12 converts the average value of RGB into tristimulus values of the XYZ color system using the following equation (1).

Then, the calculation unit 12 further converts these XYZ color system tristimulus values to the following equation (2) to convert them into the xyY color system, and stores the JISZ 8721 “color display method” stored in the storage unit 20. The Munsell color system color values (hue H, lightness C, and saturation V) in each image area are acquired based on the data in Appendices 1 and 2 of “Display with three attributes”.
x = X / (X + Y + Z) (2)
y = Y / (X + Y + Z)
Step S104: Based on the color values of the Munsell color system and the data of FIGS. 1 to 25 of JISZ 8102 “Color name of object color” stored in the storage unit 20, the calculation unit 12 sets the system of each image region. Get the color name.

  Step S105: The region combining unit 13 of the CPU 10 combines the image regions divided by the image dividing unit 11 based on the color value and the system color name. In other words, even if the subject is a single color, the color slightly changes depending on the shape of the subject itself and the condition of the light. Are determined to be different colors and divided into a plurality of image areas. For this purpose, the region combination unit 13 recombines the segmented image regions in order to match human color recognition.

  Therefore, how the region combining unit 13 combines image regions based on the color value and the system color name will be briefly described. The system color name includes a modifier that describes hue H, lightness C, and saturation V (hereinafter referred to as “tone”) and a basic color name. For example, when the color is shrimp tea (Munsell value is 8R3 / 4.5), the system color name is represented as dk-yR (dark yellow red), dk is the color tone, and yR is the basic color name. Then, the area combination unit 13 according to the present embodiment determines the degree of combination indicating the degree of color similarity between adjacent image areas based on the color value, the color tone, and the basic color name. That is, when the color tone T and basic color name N between the adjacent image area i and image area j are Ti = Tj and Ni = Nj (however, only Ti = Tj in the case of an achromatic color), the area combination unit 13 Since the system color names of the image area i and the image area j are the same, it is determined that the image area i has the “strong coupling degree”. Ti, Ni, Tj, and Nj indicate the color tone and basic color name of the image area i and the image area j.

On the other hand, when the system color name in the image area i and the image area j is a chromatic color, Ni = Nj, and the color value satisfies the condition of the following expression (3), the area combination unit 13 performs image area i and image area j. Is determined to have “medium degree of coupling”.
Vi-dV <Vj <Vi + dV and Ci-dC <Cj <Ci + dC (3)
Alternatively, when the system color name in the image area i and the image area j is a chromatic color, Ti = Tj, and the color value satisfies the condition of the following expression (4), the area combination unit 13 performs image area i and image area j. Is determined to have “medium degree of coupling”.
Hi-dH <Hj <Hi-dH (4)
In this embodiment, dV, dC, and dH are set to 0.5, 0.5, and 5.0, respectively, but are preferably set as appropriate according to the color distribution of the subject. .

  When the image area i and the image area j do not correspond to either “strong coupling degree” or “medium coupling degree”, the area coupling unit 13 has different colors between the image area i and the image area j. As “weak coupling degree”.

  The region combining unit 13 according to the present embodiment determines any of “strong coupling degree”, “medium coupling degree”, and “weak coupling degree” with adjacent image areas for all image areas. The region combining unit 13 of the present embodiment combines image regions determined as “strong coupling degree” or “medium coupling degree”. Thereby, image areas of similar colors can be collected.

  Step S106: The harmony evaluation unit 14 of the CPU 10 extracts the top three image areas having a large area as image areas having a representative color among the plurality of image areas (target areas to be evaluated). The harmony evaluation unit 14 sets the color value of the image area having the largest area among the image areas combined in step S105 as the extracted color value of each target area. However, the harmony evaluation unit 14 may recalculate the color value of each target area using the pixel value of the target area, similarly to step S103.

  Step S107: The harmony evaluation unit 14 applies a known color harmony evaluation method for each combination of two target areas among the extracted three target areas to obtain a harmony relationship, and performs color harmony of the image to be processed. evaluate.

  Specifically, the harmony evaluation unit 14 applies the difference (relative positional relationship) between the color values in the two target regions of each combination to a known color harmony evaluation method, for example, the Moon-Spencer model. Thus, the color harmony relationship between the two target areas is obtained. FIG. 3 shows an example of the color harmony relationship in the Moon-Spencer model. FIG. 3A shows the range of the same harmony, first unclearness, similar harmony, second unclearness and contrast harmony according to the hue difference when one color of two target regions is used as a reference. The distribution of. FIG. 3B shows the distribution of the same harmony, first unclearness, similar harmony, second unclearness and contrast harmony according to the color saturation difference and lightness difference of the two target regions. The same harmony indicates that two colors are the same and harmonize, the similar harmony indicates that the two colors are similar and harmonized, and the contrast harmony indicates that the two colors are contrasted and harmonized. On the other hand, the first ambiguity and the second ambiguity indicate that they are not in harmony.

  The harmony evaluation unit 14 of the present embodiment uses the case where the harmony relationship of each combination in the three target regions is based on the hue difference of FIG. 3A and the case of the saturation difference and brightness difference of FIG. Ask for each. The harmony evaluation unit 14 sets Ni, Ns, and Nc as the number of times the same harmony, similar harmony, or contrast harmony is obtained, and uses the following equation (5) to determine the frequencies Ri, Rs, Rc of the same harmony, similar harmony, and contrast harmony. Is calculated.

Here, N indicates the number of target regions, and N = 3 in the present embodiment.

  Then, the harmony evaluation unit 14 evaluates the color harmony of the image based on the values of the frequencies Ri, Rs, and Rc, for example, based on the highest frequency or the harmony of 50% or more. As an example, since the harmony evaluation unit 14 is in harmony with similar colors in the case of similar harmony, it is evaluated that “the image is natural harmony”, or in the case of contrast harmony, the harmony with the contrasting colors is not Because it is rare in nature, it is evaluated that “images are artificially harmonized”. Thereafter, the CPU 10 ends a series of processes.

  As described above, in this embodiment, after an image is divided into a plurality of image areas, an image area having a color representing the image is extracted as a target area to be evaluated based on the size of the image area, and extracted. By obtaining the frequency related to the color harmony relationship in the target area, it is possible to evaluate the color harmony of the image while considering human color recognition.

In addition, by recombining the divided image regions in accordance with human color recognition, it is possible to evaluate the color harmony of the image closer to human color recognition.
<< Additional items of embodiment >>
In the above embodiment, the image to be processed is stored in the storage unit 20 in advance, but the present invention is not limited to this, and for example, the computer 100 and the digital camera or digital video camera via the input / output I / F 30 Or the like may be connected via a USB (Universal Serial Bus) cable or the like to directly read still images or moving images.

  In the above embodiment, the computer 100 is operated as an image processing apparatus. However, the present invention is not limited to this, and for example, a digital camera or the like is operated as an image processing apparatus to evaluate an image while evaluating the color harmony of a subject. You may image.

  In the above embodiment, the image dividing unit 11 performs image division by combining the division / integration method and the watershed method. However, the present invention is not limited to this, and the image may be divided using other methods. Good.

  In the above embodiment, the calculation unit 12 uses JIS standard data to obtain the color value and the system color name of each image area. However, the present invention is not limited to this, and other data may be used. Good.

  In the above embodiment, the degree of coupling between adjacent image regions is determined to be “strong coupling degree”, “medium coupling degree”, and “weak coupling degree”, but the present invention is not limited to this. Not. For example, “strong bond” corresponds to the case where the values of dV, dC, and dH are 0 in the expressions (3) and (4), which are the conditions for “medium bond,” The “strong coupling degree” and the “medium coupling degree” may be treated as one coupling degree.

  In the above embodiment, the top three image areas having the largest size are extracted as target areas. However, the present invention is not limited to this, and four or more image areas may be extracted as target areas.

  In addition, when the colors of at least two target areas among the extracted target areas are the same, it is preferable to combine them as one target area so that the colors of the extracted target areas are different from each other.

  In the above embodiment, the harmony evaluation unit 14 applied the Moon-Spencer model to evaluate the color harmony in the target area, but the present invention is not limited to this, and other known color harmony evaluation methods are used. It may be used.

  From the above detailed description, features and advantages of the embodiments will become apparent. It is intended that the scope of the claims extend to the features and advantages of the embodiments as described above without departing from the spirit and scope of the right. Further, any person having ordinary knowledge in the technical field should be able to easily come up with any improvements and modifications, and there is no intention to limit the scope of the embodiments having the invention to those described above. It is also possible to use appropriate improvements and equivalents within the scope disclosed in.

DESCRIPTION OF SYMBOLS 10 ... CPU, 20 ... Memory | storage part, 30 ... Input-output I / F, 40 ... Bus, 50 ... Output device, 60 ... Input device, 100 ... Computer

Claims (7)

An image dividing unit for dividing the image into a plurality of image regions;
A calculation unit for obtaining coordinates on the color space of the color of the image area, and a color tone and a color name corresponding to the coordinates ;
A harmony evaluation unit that extracts a plurality of target areas to be evaluated from the plurality of image areas, and evaluates color harmony in the image based on the coordinates of the extracted plurality of target areas;
The coordinates, the image processing apparatus to have a an area coupling unit for coupling the tone and image area adjacent to the image area on the basis of the color name. The image processing apparatus according to claim 1.
The harmonic evaluation unit, based on a size of the plurality of image areas, the image processing apparatus that to extract the plurality of target regions. The image processing apparatus according to claim 1 or 2,
Before SL harmony evaluation unit is determined based on the harmonic relationships of the combination each of the two of the target region in the plurality of target regions on the relative positional relationship of the coordinates, the image processing apparatus for evaluating color harmony in the image. An image dividing unit for dividing the image into a plurality of image regions ;
A calculation unit for obtaining coordinates on a color space of the color of the image area;
A plurality of the target regions to be evaluated are extracted from the plurality of image regions, and the harmonic relationship of the combination is determined from the relative positional relationship of the coordinates in the combination of the two target regions in the plurality of target regions. Obtaining the same harmony, similar similarity, or contrasting contrast in which the colors between the two target areas are the same, and calculating the same harmony, the similar harmony, and the contrasting harmony in the plurality of target areas, respectively. calculating a frequency, an image processing apparatus that have a harmony evaluation unit for evaluating the color harmony in the image. The image processing apparatus according to claim 4.
The said harmony evaluation part is an image processing apparatus which calculates the frequency Ri, Rs, and Rc of the said same harmony, the said similar harmony, and the said contrast harmony using a following formula.

Note that N indicates the number of the target areas, and Ni, Ns, and Nc indicate the number of the combinations that are the same harmony, the similar harmony, and the contrast harmony in the plurality of target areas. Input procedure for loading images ,
An image division procedure for dividing the image into a plurality of image regions;
A calculation procedure for obtaining coordinates on a color space of the color of the image area, and a color tone and a color name corresponding to the coordinates;
A harmony evaluation procedure for extracting a plurality of target areas to be evaluated from the plurality of image areas, and evaluating color harmony in the image based on the coordinates of the extracted plurality of target areas,
A region combining procedure for combining the image region and an adjacent image region based on the coordinates, the color tone, and the color name;
An image processing program for causing a computer to execute . The image processing program according to claim 6 ,
The harmony evaluation procedure is an image processing program that extracts the plurality of target regions based on the sizes of the plurality of image regions .

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