Information processing device, operation method of information processing device, and program

Abstract

To enable direct evaluation of an impression received by an observer from a surface state of a part of a face.SOLUTION: An information processing device includes: a storage unit that stores a captured image of skin of a person; and a control unit that outputs a display image of a part of interest of the captured image in which a gradation value corresponding to a change mode of brightness in a target region having a plurality of pixels in the part of interest is assigned to a representation region included in the target region.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device, an operation method for an information processing device, and a program. [Background technology]

[0002] The surface condition of parts of a person's face, such as the lips and corners of the eyes, changes depending on various factors and affects the impression made by the observer, and is therefore a matter of cosmetic concern. As techniques for evaluating roughness of facial parts, for example, methods have been proposed that measure the amount of moisture using images captured by a near-infrared camera (Patent Document 1) and measure the state of moisture diffusion by analyzing MRI images (Patent Document 2). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-171365 [Patent Document 2] Japanese Patent Publication No. 2020-096763 Summary of the Invention [Problem to be solved by the invention]

[0004] It is desired to evaluate the visual impression given to an observer by the condition of roughness of a facial part more directly, without relying on indirect evaluation of factors such as moisture content.

[0005] In view of the above, the following discloses an information processing device and the like that can more directly evaluate the impression that an observer receives from the surface condition of facial parts. [Means for solving the problem]

[0006] In order to solve the above problem, the information processing device of the present disclosure has a memory unit that stores an image of a person's skin, and a control unit that outputs a display image of the area of ​​interest in the image, in which a gradation value corresponding to the change in luminance in a target area having a plurality of pixels in the area of ​​interest in the image is assigned to a representative area included in the target area.

[0007] In addition, the method of operating an information processing device in the present disclosure includes a first step of acquiring an image of a person's skin, and a second step of outputting a display image of the area of ​​interest in the captured image, in which a gradation value corresponding to the change in luminance in a target area having a plurality of pixels in the area of ​​interest is assigned to a representative area included in the target area. [Effects of the Invention]

[0008] According to the information processing device and the like of the present disclosure, it becomes possible to more directly evaluate the impression that the observer receives from the surface condition of parts of the face. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 illustrates an example of the configuration of an information processing system. [Figure 2] FIG. 10 is a flowchart illustrating an example of an operation procedure of the server device. [Figure 3A] FIG. 10 is a diagram showing an example of a face image and a region of interest. [Figure 3B] FIG. 10 is a diagram showing an example of a target region in a site of interest. [Figure 3C] FIG. 1 is a diagram illustrating a target region and a co-occurrence matrix. [Figure 3D] FIG. 10 is a diagram illustrating shifting of a target region. [Figure 4] 10A and 10B are diagrams illustrating processing of a target region in a boundary portion. [Figure 5] FIG. 10 is a diagram showing an example of a display image. [Figure 6] FIG. 10 is a diagram illustrating the direction of pixel pairs in a modified example. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, an embodiment of the present invention will be described.

[0011] [System Configuration] FIG. 1 is a diagram illustrating an example of a configuration of an embodiment of the present invention. The information processing system 1 includes a server device 10 and a terminal device 12 connected to each other via a network 11 so as to be able to communicate with each other. In the information processing system 1, the server device 10 performs various information processing using various information sent from the terminal device 12. The terminal device 12 is, for example, one or more personal computers. The personal computer may include a tablet terminal device, a smartphone, etc. The server device 10 corresponds to the "information processing device" in this embodiment. The server device 10 is, for example, one or more server computers. When the server device 10 is a single server computer, the server device 10 may be multiple server computers that cooperate to execute the operations of this embodiment and provide a cloud service. The network 11 is, for example, a local area network (LAN), the Internet, an ad hoc network, a metropolitan area network (MAN), a mobile communication network, or other networks, or any combination thereof.

[0012] In this embodiment, the server device 10 extracts a region of interest (e.g., lips, corners of the eyes, cheeks, etc.) from a captured image of a person's skin, e.g., a captured image of the face (hereinafter referred to as a facial image) and performs information processing to evaluate the condition of roughness of the region of interest. The server device 10 includes a memory unit 102 that stores the facial image, and a control unit 103 that outputs a display image of the region of interest in which a gradation value (hereinafter referred to as a representative gradation value) corresponding to the luminance variation pattern in a target region having multiple pixels in the region of interest in the facial image is assigned to a representative region included in the target region. The target region is an area of ​​any shape including any number of pixels. The representative region is one or more pixels that constitute a part of the target region. Rough skin in the region of interest can result in cracks, peeling, wrinkles, etc., resulting in a visually uneven skin surface condition. Such unevenness is manifested as sudden and frequent changes in luminance between adjacent pixels in the target region. The display image, which is composed of pixels in the representative region to which representative gradation values ​​that reflect such changes are assigned, allows the evaluator to objectively and quantitatively visually recognize the roughness of the target area, thereby enabling a more direct evaluation of the impression the observer receives.

[0013] [Configuration example of server device 10] The server device 10 includes a communication unit 101, a storage unit 102, and a control unit 103. When the server device 10 is configured with two or more server computers, these components are appropriately arranged in the two or more server computers.

[0014] The communication unit 101 includes one or more communication interfaces. The communication interface is, for example, a LAN interface. The communication unit 101 receives information used in the operation of the server device 10 and transmits information obtained by the operation of the server device 10. The server device 10 is connected to a network 11 by the communication unit 101 and communicates information with a terminal device 12 via the network 11.

[0015] The storage unit 102 includes, for example, one or more semiconductor memories, one or more magnetic memories, one or more optical memories, or a combination of at least two of these, that function as a main storage device, an auxiliary storage device, or a cache memory. The semiconductor memories are, for example, RAM (Random Access Memory) or ROM (Read Only Memory). The RAM is, for example, SRAM (Static RAM) or DRAM (Dynamic RAM). The ROM is, for example, EEPROM (Electrically Erasable Programmable ROM). The storage unit 102 stores information used in the operation of the control unit 103 and information obtained by the operation of the control unit 103.

[0016] The control unit 103 includes one or more processors, one or more dedicated circuits, or a combination thereof. The processor is, for example, a general-purpose processor such as a CPU (Central Processing Unit), or a dedicated processor such as a GPU (Graphics Processing Unit) specialized for a specific process. The dedicated circuit is, for example, an FPGA (Field-Programmable Gate Array), an ASIC (Application Specific Integrated Circuit), etc. The control unit 103 executes information processing related to the operation of the server device 10 while controlling each unit of the server device 10.

[0017] The functions of the server device 10 are realized by a processor included in the control unit 103 executing a control program. The control program is a program for causing the processor to function as the control unit 103. Alternatively, some or all of the functions of the server device 10 may be realized by a dedicated circuit included in the control unit 103. Alternatively, the control program may be stored in a non-transitory recording / storage medium readable by the control unit 103, and read by the control unit 103 from the medium.

[0018] [Configuration example of terminal device 12] The terminal device 12 includes a communication unit 121 , a storage unit 122 , a control unit 123 , an input unit 125 , and an output unit 126 .

[0019] The communication unit 121 includes a communication module compatible with wired or wireless LAN standards, a module compatible with mobile communication standards such as LTE (Long Term Evolution), 4G (4th Generation), or 5G (5th Generation), etc. The terminal device 12 is connected to the network 11 by the communication unit 121 via a nearby router device or a mobile communication base station, and performs information communication with the server device 10, etc. via the network 11.

[0020] The storage unit 122 includes one or more semiconductor memories, one or more magnetic memories, one or more optical memories, or a combination of at least two of these. The semiconductor memories are, for example, RAM or ROM. The RAM is, for example, SRAM or DRAM. The ROM is, for example, EEPROM. The storage unit 122 functions as, for example, a main storage device, an auxiliary storage device, or a cache memory. The storage unit 122 stores information used in the operation of the control unit 123 and information obtained by the operation of the control unit 123.

[0021] The control unit 123 has, for example, one or more general-purpose processors such as a CPU, an MPU (Micro Processing Unit), etc., or one or more dedicated processors such as a GPU specialized for a specific process. Alternatively, the control unit 123 may have one or more dedicated circuits such as an FPGA, an ASIC, etc. The control unit 123 performs overall control of the operation of the terminal device 12 by operating according to a control / processing program or operating according to an operating procedure implemented as a circuit. The control unit 123 then transmits and receives various information to and from the server device 10, etc. via the communication unit 121, and performs the operation according to this embodiment.

[0022] The functions of the terminal device 12 are realized by a processor included in the control unit 123 executing a control program. The control program is a program for causing the processor to function as the control unit 123. Alternatively, some or all of the functions of the terminal device 12 may be realized by a dedicated circuit included in the control unit 123. Alternatively, the control program may be stored in a non-transitory recording / storage medium readable by the control unit 123, and read by the control unit 123 from the medium.

[0023] The input unit 125 includes one or more input interfaces. The input interfaces include, for example, physical keys, capacitive keys, a pointing device, and a touch screen integrated with a display. The input interfaces also include a microphone for receiving voice input and a camera for capturing captured images. The input interfaces may also include a scanner or camera for scanning image codes, and an IC card reader. The input unit 125 receives an operation for inputting information used in the operation of the control unit 123 and sends the input information to the control unit 123. The input unit 125 also sends images captured by the camera to the control unit 123.

[0024] The output unit 126 includes one or more output interfaces. The output interfaces include, for example, a display and a speaker. The display is, for example, an LCD (Liquid Crystal Display) or an organic EL (Electro-Luminescence) display. The output unit 126 outputs information obtained by the operation of the control unit 123.

[0025] [Operation procedure of server device 10] Fig. 2 is a flowchart for explaining an example of the operation of the server device 10. The procedure in Fig. 2 is executed by the control unit 103 when determining the roughness state of a target area based on a facial image. For example, a user operates the terminal device 12 to send an instruction to the server device 10 to operate the server device 10, and in response to the instruction, the control unit 103 executes the procedure in Fig. 2.

[0026] In step S20, the control unit 103 acquires a facial image. The facial image is generated by capturing an image of the face of a person who is the subject. The image of the person's face is captured by, for example, a camera of the terminal device 12 or a digital still camera. The captured image is acquired by the terminal device 12 when a user operates the terminal device 12 to capture an image using the terminal device 12 or when an image captured by the digital still camera is imported into the terminal device 12. The control unit 103 then receives the facial image of the person sent from the terminal device 12 via the communication unit 101 and stores it in the storage unit 102. Alternatively, the control unit 103 may acquire the facial image from open data.

[0027] In step S21, the control unit 103 extracts a region of interest from the face image. In this case, the region of interest is the lower lip. The control unit 103 detects the face region of the face image using any algorithm such as landmark point detection or pattern matching, or an image recognition model generated by machine learning, extracts the lip region from the face region, and further extracts the lower lip region from the lip region. For example, from the face image 30 in FIG. 3A , the control unit 103 extracts a lip image 32 including a lip region 31. The lip image 32 includes an image of the lip region 31 and its surroundings. The control unit 103 further extracts a lower lip image 34 including a lower lip region 33 as a region of interest from the lip image 32. The control unit 103 applies a low-intensity color, such as black, to the area outside the lower lip region 33 in the lower lip image 34 to define the outline of the lower lip region 33.

[0028] In step S22, the control unit 103 determines a target region in the lower lip area. The target region is a region of any shape made up of any number of pixels. Preferably, the target region is rectangular, with the length of one side set to 0.004 to 0.04 times the longitudinal length of the region of interest. Here, the representative region is one pixel included in the target region. For example, as shown in the example of FIG. 3B, the control unit 103 determines a rectangular target region 35 with one side measuring 10 pixels at any position in the lower lip area 33. The control unit 103 also determines a pixel at any position inside the target region 35 as the representative region 36. For example, in the target region 35 of 10 pixels by 10 pixels, the pixel in the 5th row and 5th column is determined as the representative region 36.

[0029] In step S23, control unit 103 generates a co-occurrence matrix corresponding to the target region. Control unit 103 converts the color of each pixel included in the target region to, for example, a 256-level grayscale. Next, control unit 103 creates pairs of gradation values ​​for pairs of adjacent pixels in the target region and generates a co-occurrence matrix in which the occurrence frequency of each pair is used as a component value. FIG. 3C partially illustrates target region 35 and co-occurrence matrix 37 corresponding to target region 35. Target region 35 has 10 rows and 10 columns of pixels, each with a gradation value ranging from 0 to 255. Co-occurrence matrix 37 is a 256 x 256 matrix corresponding to the gradation width of each pixel in target region 35. The control unit 103 sequentially generates pairs of gradation value i of a pixel in m rows by n columns (where m is a natural number less than or equal to the number of pixels on one side of the target area 35) adjacent to each other in the row direction of the target area 35, and gradation value j of a pixel in m rows by (n+1) columns. Then, for each generated pair, the control unit 103 increments the value of the corresponding element (i+1, j+1) of the co-occurrence matrix 37 by 1 to generate the co-occurrence matrix 37. The element (i+1, j+1) of the co-occurrence matrix 37 generated in this manner indicates the frequency (number of pairs) of adjacent pixels with gradation value i and gradation value j in the target area 35. This co-occurrence matrix 37 corresponds to the manner in which luminance changes in the target area 35.

[0030] In step S24, control unit 103 assigns to the representative region a representative gradation value corresponding to the change in luminance of the target region. The representative gradation value is calculated based on the components in the co-occurrence matrix. For example, control unit 103 derives the representative value of the components in the co-occurrence matrix using one of the following (Equation 1) to (Equation 5) (P in each equation is the co-occurrence matrix).

number

[0031] When assigning representative gradation values ​​to the representative region 36, the control unit 103 may, for example, convert 256 gradations into a different number of gradations and assign the representative gradation values. For example, if each pixel in the target region has a dynamic range of 256 gradations, the control unit 103 performs a gradation conversion process to compress the dynamic range of the target region so that each pixel has a dynamic range of 8 gradations. The control unit 103 then generates a co-occurrence matrix corresponding to the gradation-converted target region. The control unit 103 then assigns, to the representative region, a representative gradation value corresponding to the change in luminance of the target region. By performing the gradation value conversion process, it is possible to reduce the processing load involved in generating the co-occurrence matrix and deriving the representative value, and to speed up processing due to the reduced processing load.

[0032] In step S25, control unit 103 determines whether the process of assigning representative gradation values ​​has been performed on all pixels of the lip image. If the process of assigning representative gradation values ​​has been performed on all pixels (Yes), control unit 103 proceeds to step S26. On the other hand, if the process of assigning representative gradation values ​​has not been performed on all pixels (No), control unit 103 proceeds to step S27.

[0033] In step S27, the control unit 103 shifts the target region by a predetermined pitch, and then returns to step S22. The shift pitch is a width of a predetermined arbitrary number of pixels. For example, as shown in FIG. 3D, the control unit 103 shifts the target region 35 by a pitch of one pixel in the horizontal direction of the lower lip image 34 to determine the target region 35-2. The control unit 103 then executes steps S22 to S25 for the target region 35-2. In the target region 35, a representative gradation value is assigned to pixel 36, which is the representative region, while in the target region 35-2, a representative gradation value is assigned to pixel 36-2, which is one pixel adjacent. In this way, the target region 35 before shifting and the target region 35-2 after shifting partially overlap each other, so that a representative gradation value is assigned to the pixels throughout the entire lower lip image 34. Specifically, for example, the control unit 103 positions the target region 35 at position 35-3 such that the representative region 36 is located at the pixel in the upper left corner of the lower lip image 34, and executes steps S22 to S25. Next, the control unit 103 positions the target region 35 at a position shifted by one pixel in the horizontal direction of the lower lip image 34, i.e., in the direction of arrow Ar1, and executes steps S22 to S25. The control unit 103 then sequentially shifts the target region 35 and repeats steps S22 to S25 until the target region 35 is located at position 35-4 such that the representative region 36 is located at the pixel in the upper right corner of the lower lip image 34. The control unit 103 then executes steps S22 to S25 at position 35-4, completing processing for one row across the entire horizontal area of ​​the lower lip image 34. Next, the control unit 103 positions the target region 35 at a position shifted one pixel vertically from position 35-3, i.e., in the direction of arrow Ar2, and sequentially executes steps S22 to S25. The control unit 103 then executes processing for one row across the entire horizontal area. The control unit 103 repeats the processing for each row sequentially until the target region 35 is positioned at position 35-5 where the representative region 36 is located at the pixel in the lower left corner of the lower lip image 34. After executing steps S22 to S25 at position 35-5, the control unit 103 sequentially shifts the target region 35 and executes steps S22 to S25 from position 35-5 to position 35-6 where the representative region 36 is located at the pixel in the lower right corner of the lower lip image 34, thereby completing the assignment of the representative value.In this way, the control unit 103 assigns a representative value to the pixels throughout the entire lower lip image 34, thereby assigning a representative gradation value to the pixels throughout the lower lip region 33 included in the lower lip image 34. By shifting by a pitch of one pixel, a representative gradation value is assigned to all pixels included in the lower lip region 33. Note that the shift direction, order, etc. shown here are just examples, and any shift direction and order that allows a representative value to be assigned to the pixels throughout the lower lip image 34 is possible.

[0034] FIG. 4 is a diagram illustrating exception processing around the contour of the lower lip region 33. When shifting the target region across the entire lower lip region 33, the target region may extend beyond the contour of the lower lip region 33 and extend into the outer black region. This figure shows target region 35-3, which includes the entire lower lip region 33, and target region 35-4, which extends across the lower lip region 33 and the outer black region 40. For target region 35-3, the control unit 103 generates a co-occurrence matrix based on the gradation values ​​of all pixels within target region 35-3. Meanwhile, for target region 35-4, there is a risk of an abnormally large difference in gradation values, i.e., brightness, between range 35-5, which overlaps with the lower lip region 33, and range 35-6, which overlaps with the black region 40. Therefore, for target region 35-4, which includes the black region 40, the control unit 103 omits processing subsequent to co-occurrence matrix generation. By not using the values ​​of some pixels near the contour of the lower lip area 33, the control unit 103 can reduce the risk of assigning abnormal values ​​to pixels near the contour of the lower lip area 33.

[0035] Returning to FIG. 2, in step S26, the control unit 103 generates and displays a display image of the region of interest. The control unit 103 generates a display image in which all pixels of the lower lip region 33 are represented by the representative gradation values ​​assigned to them. At this time, the control unit 103 generates a display image near the contour of the lower lip region 33 without using a representative region corresponding to a target region in which processing subsequent to the generation of the co-occurrence matrix has been omitted. The control unit 103 may generate a display image by changing the gradation value of each pixel to a gradation value in an arbitrary color space. The control unit 103 sends the display image to the terminal device 12 and causes it to be displayed on the terminal device 12. The control unit 103 then ends the procedure of FIG. 2.

[0036] FIG. 5 shows an example of a display image. It shows lower lip images 34-1, 34-2, 34-3, and 34-4 acquired from multiple different subjects, display images 50-1, 50-2, 50-3, and 50-4 obtained from each of the images, and the average representative gradation values ​​of pixels in the representative regions included in each display image. In FIG. 5, the degree of roughness increases in the order of lower lip images 34-4, 34-3, 34-2, and 34-1. The display images 50-1, 50-2, 50-3, and 50-4 are expressed with a more non-uniform pattern as the degree of roughness increases. Furthermore, the average representative gradation value increases as the degree of roughness increases, i.e., the value corresponds to the non-uniformity. The control unit 103 controls the terminal device 12 to display such display images alone or together with the lower lip images and the average representative gradation values, allowing the evaluator to objectively and quantitatively visually recognize the roughness of the area of ​​interest. This allows for a more direct evaluation of the impression the observer receives.

[0037] FIG. 6 is a diagram illustrating the generation of a co-occurrence matrix in a modified example. FIG. 3C illustrates an example in which pairs of gradation values ​​are generated for pairs of adjacent pixels in the row direction, i.e., the horizontal direction of the drawing, in the target region 35. In a modified example, as shown in FIG. 6, the control unit 103 may generate pairs of gradation values ​​for adjacent pixel pairs in the vertical direction 63 or diagonal directions 62 or 64, in addition to the horizontal direction 61, for a single pixel 60 in the target region 35. Furthermore, the control unit 103 may execute steps S22 to S23 of FIG. 2 for each of multiple directions and assign the average of the representative gradation values ​​obtained in each direction to the representative region. For example, if there are many vertical cracks and wrinkles in the lower lip region 33, the luminance difference between pixel pairs in the horizontal direction is likely to be greater than the luminance difference between pixel pairs in the vertical direction. In such a case, by generating luminance pairs for pixel pairs in multiple directions and averaging the representative gradation values ​​for each case, a more uniform display image can be obtained.

[0038] In the above description, the representative region may be a region consisting of multiple pixels, for example, a rectangular region consisting of four pixels, with each side being two pixels. In this case, the pitch by which the target region is shifted in step S27 can be set to be equal to or greater than the length of one side of the representative region. This allows the control unit 103 to process the entire region of interest with fewer steps, thereby reducing the processing load on the server device 10.

[0039] The terminal device 12 of this embodiment can be installed in, for example, a cosmetics store, and the terminal device 12 can be linked to a server device 10 on the cloud to determine the condition of rough skin on the face of a customer visiting the store. By capturing an image of the customer using the terminal device 12 and displaying an output image showing the rough skin condition on the terminal device 12, the customer and the salesperson can recognize the rough skin condition (e.g., blemishes, wrinkles, etc.) on the customer's face and select an appropriate product. Alternatively, this embodiment can be applied to objectively evaluating changes over time in the rough skin condition (e.g., uneven skin tone, uniformity of cosmetic film, etc.) of an area to which the cosmetic product is applied during the development process of the cosmetic product.

[0040] In the above description, the server device 10 corresponds to the "information processing device." However, the server device 10 and the terminal device 12 may cooperate to configure the "information processing device," or the terminal device 12 may correspond to the "information processing device."

[0041] In the above-described embodiment, the processing / control program that defines the operation of the terminal device 12 may be stored in the memory unit 102 of the server device 10 or in the memory unit of another server device, and may be downloaded to the terminal device 12 via the network 11, or may be stored in a computer-readable non-transitory recording / storage medium and read by the terminal device 12 from the medium.

[0042] Although the embodiments have been described above based on the drawings and examples, it should be noted that those skilled in the art can easily make various modifications and alterations based on the present disclosure. Therefore, it should be noted that these modifications and alterations are included in the scope of the present disclosure. For example, the functions included in each means, step, etc. can be rearranged so as not to be logically inconsistent, and multiple means, steps, etc. can be combined or divided into one. [Explanation of symbols]

[0043] 10: Server device 11: Network 12: Terminal device 101, 121: Communications Department 102, 122: Storage section 103, 123: control unit 125: Input section 126: Output section

Claims

1. a storage unit for storing captured images of a person's skin; a control unit that outputs a display image of the target region of the captured image in which a gradation value corresponding to a change in luminance in a target region having a plurality of pixels in the target region of the captured image is assigned to a representative region included in the target region; An information processing device having the above.

2. In claim 1, the variation is a co-occurrence matrix whose components are the frequency of occurrence of pairs of luminance values ​​of adjacent pixel pairs in the target region, and the gradation value corresponds to a representative value of the components of the co-occurrence matrix; Information processing device

3. In claim 2, the control unit generates the co-occurrence matrix for pixel pairs adjacent to each other in a plurality of directions in the target region. Information processing device.

4. In claim 1, The plurality of target regions overlap with one another. Information processing device.

5. In claim 1, the control unit forms the display image by omitting the representative region corresponding to the target region including an image outside the site of interest. Information processing device.

6. In claim 1, The representative region is one or more pixels. Information processing device.

7. In claim 1, The target region is a rectangle with a side length of 0.004 to 0.04 times the longitudinal length of the region of interest. Information processing device.

8. a first step of acquiring an image of a person's skin; a second step of outputting a display image of the region of interest in the captured image, in which a gradation value corresponding to a change in luminance in a target region having a plurality of pixels in the region of interest is assigned to a representative region included in the target region; An operating method of an information processing device including:

9. In claim 8, the variation is a co-occurrence matrix whose components are the frequency of occurrence of pairs of luminance values ​​of adjacent pixel pairs in the target region, and the gradation value corresponds to a representative value of the components of the co-occurrence matrix; A method for operating an information processing device.

10. In claim 9, In the second step, the co-occurrence matrices are generated for pairs of pixels adjacent to each other in a plurality of directions in the target region. A method for operating an information processing device.

11. In claim 8, The plurality of target regions overlap with one another. A method for operating an information processing device.

12. In claim 8, In the second step, the display image is formed by omitting the representative region corresponding to the target region including an image outside the target region. A method for operating an information processing device.

13. In claim 8, The representative region is one or more pixels. A method for operating an information processing device.

14. In claim 8, The target region is a rectangle with a side length of 0.004 to 0.04 times the longitudinal length of the region of interest. A method for operating an information processing device.

15. A program for an information processing device, which, when executed by an information processing device, causes the information processing device to perform any one of the operating methods of claims 8 to 14.

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