Information processing apparatus, information processing method, and program

Abstract

An information processing apparatus (100) evaluates a hair growth suppression effect obtained by an optical hair removal apparatus (10), the information processing apparatus (100) including: an acquisition unit (111) that acquires a skin image obtained by photographing a subject part of a subject; a counting unit (112) that counts a number of body hairs based on the skin image (200); and an evaluation unit (113) that evaluates the hair growth suppression effect based on a comparison result of a first count result counted for a first skin image photographed at a first time and a hair amount prediction value at the first time based on a second count result, the second count result being a result counted for a second skin image photographed at a second time, the second time being earlier than the first time by a first period.

Description

Technical Field

[0001] This disclosure relates to information processing apparatus, information processing methods, and procedures. Background Technology

[0002] Patent document 1 discloses a measurement system for counting body hairs and evaluating hair removal or hair growth.

[0003] (Existing patent literature) (Patent Documents) Patent Document 1: Japanese Patent Application Publication No. 2021-56708 Summary of the Invention

[0004] The problem that the invention aims to solve This disclosure provides an information processing device, etc., capable of appropriately evaluating the hair growth inhibition effect obtained by an optical hair removal device.

[0005] Methods for solving problems One aspect of this disclosure relates to an information processing apparatus for evaluating the hair growth inhibition effect obtained by an optical hair removal device. It comprises: an acquisition unit for acquiring a skin image obtained by photographing a target area of ​​a subject; a counting unit for counting the number of body hairs based on the skin image; and an evaluation unit for evaluating the hair growth inhibition effect based on a comparison between a first counting result obtained from a first skin image captured at a first time and a predicted hair volume value at the first time based on a second counting result, wherein the second counting result is obtained from a second skin image captured at a second time, the second time being a first period earlier than the first time.

[0006] Furthermore, one aspect of this disclosure relates to an information processing method executed by an information processing device having one or more processors and evaluating the hair growth inhibition effect obtained by an optical hair removal device. The one or more processors acquire skin images obtained by photographing a target area of ​​a subject, count the number of body hairs based on the skin images, and evaluate the hair growth inhibition effect by comparing the result of the counting performed on a first skin image taken at a first time moment (i.e., a first counting result) with a predicted hair volume value at the first time moment based on a second counting result. The second counting result is the result of the counting performed on a second skin image taken at a second time moment, which is a first period earlier than the first time moment.

[0007] Furthermore, these general or specific methods can be implemented by non-transitory recording media such as devices, integrated circuits, computer programs, or computer-readable CD-ROMs, or by any combination of devices, integrated circuits, computer programs, and non-transitory recording media.

[0008] The effects of the invention The information processing apparatus and the like disclosed herein can appropriately evaluate the hair growth inhibition effect obtained by the optical hair removal device. Attached Figure Description

[0009] Figure 1 This is a diagram used to illustrate the outline of the information processing apparatus involved in the implementation method.

[0010] Figure 2 This is a hardware configuration diagram of the information processing device in the implementation method.

[0011] Figure 3 This is a block diagram illustrating an example of the functional configuration of the information processing apparatus in the embodiment.

[0012] Figure 4 This diagram illustrates the process of defining the region of a countable object in a skin image.

[0013] Figure 5 This is a diagram illustrating the process of calculating the constants used to determine the threshold in the binarization of a skin image.

[0014] Figure 6 This is a diagram used to illustrate the brightness values ​​used in the binarization of skin images.

[0015] Figure 7 It is a graph used to determine which pixels are candidates for body hair in the binarization of a skin image.

[0016] Figure 8 It is a graph used to determine candidate pixels other than body hair in the binarization of skin images.

[0017] Figure 9 This is a graph showing the relationship between the second average brightness and the threshold used to determine which pixels are candidates for becoming body hair.

[0018] Figure 10 This is a diagram showing an example of a binarized image.

[0019] Figure 11 This is a diagram illustrating an example of a method for detecting pixel groups.

[0020] Figure 12 This is a diagram showing an example of a group of pixels that can be considered as a candidate block of body hair in a binarized image.

[0021] Figure 13 This is a diagram showing an example of a rectangle surrounding a group of pixels.

[0022] Figure 14 This is a diagram used to illustrate the process of determining the length of body hair.

[0023] Figure 15 This is a graph showing an example of heatmap data.

[0024] Figure 16 This is a diagram showing an example of displayed information.

[0025] Figure 17 This is a diagram illustrating an example of a process that captures a skin image and detects hair volume at a second moment (e.g., the first time).

[0026] Figure 18 This is a flowchart showing the details of the counting process.

[0027] Figure 19 This is a diagram illustrating an example of a process that captures skin images and detects hair volume at a first moment (e.g., after the second moment). Detailed Implementation

[0028] (The knowledge that forms the basis of this disclosure) Human body hair grows in a cyclical pattern known as the hair cycle. The hair cycle includes the anagen (growth) phase, catagen (transitional) phase, and telogen (resting) phase, which body hair repeatedly goes through. During the anagen phase, body hair grows, then degenerates during the catagen phase and transitions to the telogen phase. When new body hair is generated within the same hair follicle, the hair in the telogen phase falls out. Because the hair cycle includes periods of hair growth and periods of non-growth, it is difficult to distinguish whether the lack of hair growth is due to a hair growth inhibition effect or simply because the hair is in the telogen phase. Therefore, to evaluate the hair growth inhibition effect of optical hair removal devices, it is necessary to wait for a period based on the hair cycle after light treatment with the device.

[0029] Furthermore, the effectiveness of hair growth inhibition varies from person to person and from area to area treated with light. Therefore, the changes resulting from hair growth inhibition are sometimes not so significant as to be visually apparent, but rather appear gradually. Thus, it is necessary to inform users whether the hair growth inhibition effect achieved by the optical hair removal device has already become apparent.

[0030] In the technology of Patent Document 1, hair removal or hair growth is quantitatively evaluated by measuring the number of body hairs.

[0031] However, in the technology of Patent Document 1, since it is impossible to know whether the hair growth inhibition effect obtained by the optical hair removal device is properly achieved, it is difficult for the user to determine whether to continue the light treatment without adjusting the output of the optical hair removal device, or to adjust the output before light treatment. In other words, in the prior art, because it is difficult to properly set the output of the optical hair removal device, the following problems exist: for the user, an excessively high output may cause unnecessary damage to the skin; or, an excessively low output may not achieve a proper hair growth inhibition effect.

[0032] In order to solve these problems, the inventors of the present invention have discovered an information processing device or the like that can properly evaluate the hair growth inhibition effect obtained by an optical hair removal device.

[0033] The first aspect of this disclosure relates to an information processing apparatus for evaluating the hair growth inhibition effect obtained by an optical hair removal device. It comprises: an acquisition unit for acquiring a skin image obtained by photographing a target area of ​​a subject; a counting unit for counting the number of body hairs based on the skin image; and an evaluation unit for evaluating the hair growth inhibition effect based on a comparison between a first counting result obtained from a first skin image captured at a first time and a predicted hair volume value at the first time based on a second counting result, wherein the second counting result is obtained from a second skin image captured at a second time, the second time being a first period earlier than the first time.

[0034] Accordingly, by comparing the first count result of the first skin image at the first time point with the predicted hair volume based on the hair growth suppression effect obtained by the light treatment of the optical hair removal device at the time corresponding to the second time point, it is possible to determine whether the predicted hair growth suppression effect has been achieved. Thus, the hair growth suppression effect obtained by the optical hair removal device can be appropriately evaluated.

[0035] The information processing apparatus involved in the second aspect of this disclosure is an information processing apparatus based on the first aspect. The first moment is the moment after the second period has elapsed following the light treatment performed by the optical hair removal device, and the second moment is the moment after the second period has elapsed following the light treatment performed by the optical hair removal device.

[0036] Therefore, since both the first and second moments can be taken as the moments after the second period following the corresponding light treatment, the hair growth inhibition effect can be evaluated in a way that reduces the error caused by the amount of body hair growth.

[0037] The information processing apparatus involved in the third aspect of this disclosure is an information processing apparatus based on the first or second aspect. When the absolute value of the value obtained by subtracting the first counting result from the hair volume prediction value is below a predetermined threshold, the evaluation unit calculates and displays an evaluation value of the hair growth inhibition effect based on the difference between the first counting result and the hair volume prediction value, and outputs the calculated evaluation value.

[0038] Therefore, if the absolute value of the value obtained by subtracting the first count result from the gross volume prediction value is below a specified threshold, it can be determined that an appropriate first count result has been obtained, and thus an appropriate evaluation value can be calculated.

[0039] The information processing apparatus involved in the fourth aspect of this disclosure is an information processing apparatus based on any one of the first to third aspects, wherein the evaluation unit outputs prompting information to prompt the subject to take a new skin image of the subject when the absolute value is greater than a predetermined threshold.

[0040] Therefore, if the evaluation value is greater than the specified threshold, it can be judged as a shooting failure, and thus an appropriate first count result can be obtained by prompting a reshoot.

[0041] The information processing apparatus involved in the fifth aspect of this disclosure is an information processing apparatus based on any one of the first to fourth aspects. The counting unit, for each of the multiple body hairs in the skin image, (i) extracts the outline of the body hair, and (ii) sets a rectangle that surrounds the extracted outline and has the smallest area; the number of one or more rectangles among the set rectangles whose length of at least one of the long side and the short side is within a specified range is counted as the number of body hairs.

[0042] Therefore, since it is possible to exclude the counting of body hair from areas other than wrinkles, pores, moles, etc., it is possible to accurately count body hair.

[0043] The information processing apparatus according to the sixth aspect of this disclosure is an information processing apparatus based on the fifth aspect. The counting unit defines an object region for detecting body hair between the nose and upper lip of the subject's face in the skin image, and defines the plurality of rectangles within the object region.

[0044] Therefore, it is possible to accurately count the facial hair that grows on a person's face.

[0045] The information processing apparatus according to the seventh aspect of this disclosure is an information processing apparatus based on any one of the first to sixth aspects. The information processing apparatus further comprises: a calculation unit that divides the skin region in the skin image, which is the object area, into multiple segmented regions and calculates the hair density in each of the multiple segmented regions; a generation unit that generates heat map data of the hair density in the skin region based on the calculation result of the calculation unit; and an output unit that outputs display information for displaying, in a comparable state, the first heat map data obtained from the first skin image and the second heat map data obtained from the second skin image.

[0046] Therefore, it is possible to visualize the distribution of body hair density.

[0047] The information processing method involved in the eighth aspect of this disclosure is a method executed by an information processing device having one or more processors and evaluating the hair growth inhibition effect obtained by an optical hair removal device. The one or more processors acquire skin images obtained by photographing a target area of ​​a subject, count the number of body hairs based on the skin images, and evaluate the hair growth inhibition effect by comparing the result of the counting performed on a first skin image taken at a first time moment, i.e., a first counting result, with a predicted hair amount at the first time moment based on a second counting result. The second counting result is the result of the counting performed on a second skin image taken at a second time moment, which is a first period earlier than the first time moment.

[0048] Therefore, by comparing the first count result of the first skin image at the first time point with the predicted hair volume based on the hair growth suppression effect obtained by the light treatment of the optical hair removal device at the time corresponding to the second time point, it is possible to determine whether the predicted hair growth suppression effect has been achieved. Thus, the hair growth suppression effect obtained by the optical hair removal device can be appropriately evaluated.

[0049] The program involved in the ninth aspect of this disclosure is a program for causing a computer to perform the information processing method described in the eighth aspect.

[0050] Furthermore, these general or specific methods can be implemented by devices, integrated circuits, computer programs, or non-transitory recording media such as computer-readable CD-ROMs, or by any combination of devices, integrated circuits, computer programs, and non-transitory recording media.

[0051] Hereinafter, embodiments will be described in detail with appropriate reference to the accompanying drawings. However, unnecessary detailed descriptions may be omitted. For example, detailed descriptions of well-known matters or repeated descriptions of substantially the same structures may be omitted. This is to avoid making the following description excessively lengthy and to facilitate understanding by those skilled in the art.

[0052] The accompanying drawings and the following description are provided by the inventors of the present invention to enable those skilled in the art to fully understand this disclosure, and are not intended to limit the scope of the technical solutions described herein.

[0053] (Implementation Method) [constitute] Figure 1 This is a diagram used to illustrate the outline of the information processing apparatus involved in the implementation method.

[0054] The information processing device 100 is used to evaluate the hair growth inhibition effect obtained by the optical hair removal device 10. The optical hair removal device 10 is a device for irradiating the skin with IPL (Intense Pulsed Light). Accordingly, the optical hair removal device 10 can damage the hair matrix cells or hair papilla of the skin that has been irradiated with IPL. As a result, a hair growth inhibition effect that inhibits the growth of body hair can be obtained.

[0055] For example, after a user (the subject) has shaved body hair (e.g., facial hair) with a razor or electric shaver (i.e., after shaving), the user applies IPL light treatment to the skin using the optical hair removal device 10. The light treatment is performed, for example, immediately after shaving. That is, the time of shaving and the time of light treatment can be considered to be approximately the same time and corresponding to each other.

[0056] Then, after a second period following the light treatment (e.g., 1 to 1.5 days), the user uses the information processing device 100 to photograph the light-treated object area. The reason for setting the second period to 1 to 1.5 days is that within 0.5 days after shaving, there are body hairs that have not yet appeared on the skin surface, making it difficult to detect the grown-out hairs in the skin image; and if more than 2 days have passed, the body hairs begin to intertwine with neighboring hairs, making it difficult to count them. In other words, with a second period of 1 to 1.5 days, it is easier to detect and count the grown-out hairs in the skin image.

[0057] The user repeatedly undergoes light treatment using the optical hair removal device 10 and takes photos using the information processing device 100 during a first-period cycle. Accordingly, the information processing device 100 stores multiple skin images taken at various different times. The first period is, for example, 2 to 8 weeks. The information processing device 100 evaluates the hair growth inhibition effect obtained by the optical hair removal device by performing image processing on the multiple skin images taken at various different times.

[0058] Alternatively, the first period can be set to different periods based on the elapsed time since the use of the optical hair removal device 10 for light treatment began. For example, if the elapsed time is 0 to 2 months, the first period can be set to 2 weeks; if the elapsed time is more than 3 months, the first period can be set to 4 to 8 weeks. In this way, the first period can also be set in such a way that the longer the elapsed time, the longer the first period.

[0059] Figure 2 This is a hardware configuration diagram of the information processing device in the implementation method.

[0060] like Figure 2 As shown, the information processing device 100 includes a processor 101, a main memory 102, a storage device 103, a communication interface 104, an input device 105, a display 106, and a camera 107 as hardware components.

[0061] The processor 101 is a processor that executes programs stored in the storage device 103, etc.

[0062] Main memory 102 is a volatile storage area used to temporarily store data generated during processing by processor 101, or as a working area when processor 101 executes a program, or to temporarily store data received by communication IF 104.

[0063] Storage device 103 is a non-volatile storage area that holds various types of data, such as programs. Storage device 103 stores, for example, various types of data generated as a result of processing by processor 101 and various types of data received by communication IF 104.

[0064] Communication IF104 is a communication interface used for sending and receiving information with other information processing devices via a network not shown. Communication IF104 can be, for example, a wireless LAN interface, a Bluetooth (registered trademark) interface, or an interface for wireless communication. Communication IF104 can also be an interface for wired communication, such as a USB (Universal Serial Bus) or a wired LAN interface.

[0065] Input device 105 is an interface for accepting input from a person. Input device 105 can be a pointing device such as a mouse, touchpad, touch screen, or ball, or it can be a keyboard.

[0066] Display 106 is a liquid crystal display, organic EL display, etc.

[0067] The camera 107 generates an image containing the subject by capturing the subject. The camera 107 can be a color camera (RGB camera) or a monochrome camera.

[0068] The information processing device 100 may be a portable terminal such as a smartphone or tablet, or a PC (Personal Computer).

[0069] Figure 3 This is a block diagram illustrating an example of the functional configuration of the information processing apparatus in the embodiment.

[0070] like Figure 3 As shown, the information processing apparatus 100 includes an acquisition unit 111, a counting unit 112, an evaluation unit 113, a calculation unit 114, a generation unit 115, an output unit 116, and a storage unit 117 as functional components. The information processing apparatus 100 may also omit the calculation unit 114, the generation unit 115, and the output unit 116.

[0071] The acquisition unit 111 acquires skin images obtained by photographing a target area of ​​the user (object). The acquisition unit 111 acquires skin images by photographing the target area. The acquisition unit 111 acquires a skin image each time a photograph is taken. That is, the acquisition unit 111 can also acquire multiple skin images taken at multiple different times. Since the acquisition unit 111 performs acquisition at the moment each skin image is photographed, it acquires each skin image at different times. The skin images acquired by the acquisition unit 111 are output to the counting unit 112 and the storage unit 117. The acquisition unit 111 is implemented, for example, by a camera 107.

[0072] The counting unit 112 performs counting processing to count the number of body hairs based on skin images. Whenever a skin image is acquired by the acquisition unit 111, the counting unit 112 performs counting processing on the acquired skin image. That is, the counting unit 112 performs counting processing on each of a plurality of skin images. The counting unit 112 is implemented, for example, by a processor 101, a main memory 102, and a storage device 103.

[0073] Evaluation unit 113 compares the counting result of the first skin image (i.e., the first counting result) with the hair volume prediction value based on the counting result of the second skin image (i.e., the second counting result). The first skin image is a skin image generated by acquisition unit 111 at a first moment from among multiple skin images. In other words, the first skin image is a skin image captured at the first moment. The second skin image is a skin image generated by acquisition unit 111 at a second moment from among multiple skin images. In other words, the second skin image is a skin image captured at the second moment. The second moment is a moment earlier than the first moment by a first period. Furthermore, the first moment is the moment after the second period has elapsed following the light treatment performed by optical hair removal device 10. Additionally, the second moment is the moment after the second period has elapsed following the light treatment performed by optical hair removal device 10 (i.e., the light treatment performed at a moment earlier than the first moment) followed by another light treatment performed by optical hair removal device 10.

[0074] The hair volume prediction value is the hair volume prediction value at a first time point, calculated based on a second count result obtained from a second skin image taken at a second time point. In other words, the hair volume prediction value is the hair volume (number of body hairs) at the first time point that is predicted to decrease due to the expected hair growth inhibition effect of the light treatment implemented at the time corresponding to the second time point. For example, the hair volume prediction value can be calculated by multiplying the second count result by a first proportion less than 1 (e.g., 85%). The hair volume prediction value is calculated under the assumption that the second count result decreases by a specified reduction rate (e.g., 15%). The specified reduction rate is the value obtained by subtracting the first proportion from 1.

[0075] Alternatively, the predicted gross weight can also be calculated considering the frequency of light treatment. In this case, the first proportion used to calculate the predicted gross weight can be determined to be smaller as the frequency of light treatment increases.

[0076] Furthermore, the first counting result is the number of body hairs contained in the object area of ​​the first skin image, and the second counting result is the number of body hairs contained in the object area of ​​the second skin image. The first skin image is an image obtained by taking a picture of the user's object area at a first moment, and the second skin image is an image obtained by taking a picture of the same object area at a second moment. That is, the common feature of the first skin image and the second skin image is that they both capture the same object area of ​​the user. In addition, the common feature of the first counting result and the second counting result is that they both show the number of body hairs in the object area. Furthermore, since the hair volume prediction value is calculated by multiplying the number of body hairs contained in the second skin image by a first ratio, the predicted number of body hairs is shown.

[0077] Then, the evaluation unit 113 evaluates the hair growth inhibition effect based on the comparison result between the first count result and the predicted hair volume value. If the result of comparing the first count result and the predicted hair volume value is close, the evaluation unit 113 calculates and displays an evaluation value of the hair growth inhibition effect based on the difference between the first count result and the predicted hair volume value, and outputs the calculated evaluation value. The difference between the first count result and the predicted hair volume value can be, for example, the absolute value of the difference between the predicted hair volume value and the first count result (i.e., the difference). Alternatively, the difference between the first count result and the predicted hair volume value can also be the ratio of the first count result to the predicted hair volume value (i.e., the ratio). Furthermore, regarding the first count result and the predicted hair volume value, if the absolute value of the value obtained by subtracting the first count result from the predicted hair volume value is less than or equal to a first hair count, or if the ratio of the first count result to the predicted hair volume value is within the range of ± a second ratio, it can also be determined that the first count result and the predicted hair volume value are close.

[0078] The evaluation value can be the calculated difference itself, or a value related to the magnitude of the difference. When the difference is a numerical value, the smaller the difference, the higher the evaluation. When the difference is a ratio, the closer the ratio is to 1, the higher the evaluation. In other words, the evaluation value is calculated as follows: the closer the first count result is to the gross quantity forecast, the higher the evaluation.

[0079] Furthermore, if the absolute value of the difference between the first count result and the hair volume prediction value (hereinafter also referred to as "absolute value") is greater than a predetermined threshold, the evaluation unit 113 outputs a prompt message to encourage the user to take a new skin image (i.e., retake the image). For example, the situation where the absolute value is greater than the predetermined threshold may occur when the first count result (i.e., the number of body hairs detected from the first skin image) is greater than the hair volume prediction value (the number of body hairs predicted based on the number of body hairs detected from the second skin image) by more than a second number. The second number is a value greater than the first number. The evaluation unit 113 can output the prompt message, for example, by displaying it on the output unit 116. The prompt message includes, for example, a message prompting the user to retake the skin image. In this way, by displaying the prompt message on the information processing device 100, the user can be encouraged to use the information processing device 100 to retake the user's skin image.

[0080] Furthermore, the reason for prompting a retake when the absolute value exceeds a predetermined threshold is as follows: Considering that the hair growth suppression effect achieved by the optical hair removal device 10 has been achieved, although the hair quantity is expected to be less at the first moment than at the second moment, the absolute value still exceeds the predetermined threshold; that is, the first count result is more than two hairs greater than the predicted hair quantity. In other words, this is because the situation where the absolute value exceeds the predetermined threshold is presumed to be due to a failed capture.

[0081] The calculation unit 114 divides the skin region in the skin image, which is the object area, into multiple segmented regions, and calculates the hair density for each of the multiple segmented regions.

[0082] The generation unit 115 generates heat map data of body hair density in the skin region based on the calculation results of the calculation unit 114.

[0083] The output unit 116 outputs display information for displaying, in a comparable manner, first heatmap data obtained from the first skin image and second heatmap data obtained from the second skin image. The output unit 116 outputs display information by performing a display. The output unit 116 can also output the display information by sending it to another information processing device. In this case, the other information processing device can also display the received display information on its own display screen when it receives the display information from the information processing device 100.

[0084] Storage unit 117 stores multiple skin images acquired by acquisition unit 111. Storage unit 117 may also store the skin images along with time information indicating the time when the skin image was captured. For each skin image acquired, storage unit 117 performs the storage. The time information can show either an absolute time or a relative time based on a predetermined reference time, as long as it indicates the time when the skin image was captured. Furthermore, storage unit 117 may also store the counting result of counting unit 112 each time counting unit 112 completes its counting.

[0085] [Details of the counting process] Next, refer to Figures 4 to 14 The details of the counting process performed by the counting unit 112 will be explained.

[0086] Figure 4 This diagram illustrates the process of defining the region of a countable object in a skin image. Figure 4 (a) shows a skin image 200 containing the user's entire face. Figure 4 (b) shows a magnified view of the area A1 containing the user's mouth periphery in the skin image 200.

[0087] In the skin image 200, the counting unit 112 defines an object region 207 between the nose and upper lip of the user's face as the target area for detecting body hair. That is, the counting unit 112 detects body hair from the object region 207. On the other hand, the counting unit 112 does not detect body hair from areas other than the object region 207.

[0088] In order to define the target region 207, the counting unit 112 detects multiple feature points 201 to 206 on the user's face in the skin image 200, and defines multiple straight lines L1 to L3 and a polyline L4 passing through the multiple feature points 201 to 206. Then, the counting unit 112 defines the region enclosed by the multiple straight lines L1 to L3 and the polyline L4 as the target region 207.

[0089] Feature point 201 corresponds to the outer corner of the user's eye. Feature point 202 corresponds to the center of the lower end of the user's nose in the left-right direction. Feature points 203 correspond to the two ends of the user's lips in the left-right direction. Feature points 204 and 206 correspond to the cupid's bow of the user's upper lip. Feature point 205 corresponds to the center of the user's upper lip in the left-right direction.

[0090] One of the two straight lines L1 passes through two feature points 201 and 203, specifically the feature points 201 and 203 located on the left side of the face. The other line passes through two feature points 201 and 203 located on the right side of the face. Line L2 passes through feature point 202 and extends in a left-right direction. Line L3 passes through two feature points 203. The polyline L4 is a polyline consisting of multiple line segments connecting adjacent feature points 203 to 206. These multiple line segments include: a line segment connecting feature points 203 and 204 on the right side of the lips; a line segment connecting feature points 204 and 205; a line segment connecting feature points 205 and 206; and a line segment connecting feature point 206 and feature point 203 on the left side of the lips.

[0091] The object region 207 can, for example, be a region enclosed by two lines L1, L2, and L4 from among multiple straight lines L1 to L3 and polyline L4. In this case, line L3 may not be specified. Furthermore, the object region 207 is not limited to the region described above; for example, it can also be a region enclosed by two lines L1, L2, and L3 from among multiple straight lines L1 to L3 and polyline L4. In this case, polyline L4 may not be specified, and feature points 204 to 206 may not be detected.

[0092] Next, the counting unit 112 performs binarization processing on the skin image to detect body hair. Specifically, the counting unit 112 binarizes the skin image by setting the pixel values ​​of pixels that are candidate body hairs to 1 and setting the pixel values ​​of other pixels to 0. Furthermore, the values ​​set as pixel values ​​during binarization are not limited to 0 and 1; other values ​​can also be set. Additionally, the counting unit 112 may set the pixel values ​​of candidate body hairs to 0 and set the pixel values ​​of other pixels to 1.

[0093] Figure 5 This is a diagram illustrating the process of calculating the constants used to determine the threshold in the binarization of a skin image.

[0094] The counting unit 112 sets up multiple blocks 210 for the target area 207. Figure 5 This is an example of setting multiple blocks 210 in region 208, which is part of object region 207. The following explanation uses region 208 as an example.

[0095] Multiple blocks 210 are defined by dividing region 208. In Figure 5 In the image, region 208 is divided into 7×9 blocks 210. Each of the blocks 210 can be, for example, a 32×32 block with a vertical dimension of 32 pixels and a horizontal dimension of 32 pixels. Alternatively, the size of the blocks 210 is not limited to the above dimensions and can be other sizes such as 16×16 blocks. For each of the blocks 210, the counting unit 112 calculates a constant c corresponding to the average brightness value of the 32×32 pixels within that block 210, i.e., the first average brightness, and sets the constant c for that block 210. The constant c is used to determine the threshold Th in the binarization of the skin image. The constant c can be calculated, for example, based on relational information showing the relationship between the first average brightness and the constant c. The relational information can be represented, for example, by a table or by a formula. The relationship represented by the relational information is, for example, that as the first average brightness increases, the constant c also increases. The relational information is stored in the storage unit 117. The counting unit 112 reads the relational information from the storage unit 117 and calculates the constant c using the first average brightness and the relation represented by the read relational information.

[0096] Figure 6 This is a diagram used to illustrate the brightness values ​​used in the binarization of skin images. Figure 7 It is a graph used to determine which pixels are candidates for body hair in the binarization of a skin image. Figure 8 It is a graph used to determine candidate pixels other than body hair in the binarization of skin images.

[0097] The counting unit 112 performs binarization processing on each of the multiple pixels (e.g., all pixels) constituting the skin image. For example... Figure 6 As shown, the counting unit 112 determines a 21×21 block 221 centered on the pixel 220 of the processing object, with a vertical dimension of 21 pixels and a horizontal dimension of 21 pixels. Then, the counting unit 112 calculates the average value of the brightness values ​​of the 21×21 pixels contained in the determined block 221, which is the second average brightness.

[0098] The counting unit 112 calculates the threshold Th by subtracting a constant c set in the block 210 containing the pixel 220 of the processing object from the second average brightness of the 21×21 block 221 containing the pixel 220 of the processing object. Then, the counting unit 112 determines whether the brightness of the pixel 220 of the processing object is less than the threshold Th. Figure 7 As shown, when the brightness of pixel 220 of the processing target is less than the threshold Th, the counting unit 112 determines that pixel 220 of the processing target is a candidate pixel for body hair. Therefore, the counting unit 112 sets a pixel value (e.g., 1) for pixel 220 of the processing target indicating that it is a candidate pixel for body hair. Furthermore, as... Figure 8 As shown, when the brightness of pixel 220 of the processing object is above the threshold Th, the counting unit 112 determines that pixel 220 of the processing object is not a candidate pixel for body hair. Therefore, the counting unit 112 sets a pixel value (e.g., 0) for pixel 220 of the processing object indicating that it is not a candidate pixel for body hair. Accordingly, the counting unit 112 performs binarization processing on the object region 207 of the skin image 200.

[0099] Figure 9 This is a graph showing the relationship between the second average brightness and the threshold used to determine which pixels are candidates for becoming body hair.

[0100] like Figure 9 As shown, a threshold Th is set according to the second average brightness. Pixels with pixel values ​​less than the threshold Th are candidate pixels for body hair, while pixels with pixel values ​​greater than the threshold Th are not candidate pixels for body hair. Pixels that are not candidate pixels for body hair can be considered as pixels from areas other than body hair, such as skin, wrinkles, pores, and shallow moles.

[0101] The counting unit 112 performs binarization processing on the object region 207 of the skin image 200, thereby achieving... Figure 10 The generated binarized image 230 is shown. Additionally... Figure 10 This is a diagram showing an example of a binarized image.

[0102] Next, the counting unit 112 detects a group of pixels in the binarized image 230 that are adjacent to each other and are candidate pixels for body hair. In other words, the counting unit 112 detects blocks of pixels that are candidate pixels for body hair as a group of pixels.

[0103] Figure 11 This is an example diagram used to illustrate a method for detecting pixel groups. In Figure 11 In the image, region 231, which is part of the binarized image 230, is shown.

[0104] The counting unit 112 counts the pixels constituting the binary image 230, for example, starting from the top left pixel, such as... Figure 11 As indicated by the horizontal arrow, a raster scan is performed while searching for pixels with a pixel value of 1. Then, when the counting unit 112 finds a pixel with a pixel value of 1, it starts from the pixel to the lower left of the found pixel and searches for pixels with a pixel value of 1 in a counter-clockwise direction, targeting the unsearched pixels. By repeating this search until the initially found pixel with a pixel value of 1 is returned, the outline of the pixel group composed of pixels with a pixel value of 1 is determined. Thus, as... Figure 12 As shown, the counting unit 112 detects multiple pixel groups 241 consisting of pixels with a pixel value of 1 in the binarized image 230. Pixel groups 241 in Figure 12 The area in the middle is represented by the black area enclosed by a circle of 240. Figure 12 This is a diagram illustrating an example of detecting a group of pixels that are candidates for body hair in a binarized image.

[0105] Next, the counting unit 112 sets a rectangle with the smallest area that surrounds the outline (i.e. the outline of the body hair) of each of the detected multiple pixel groups. Figure 13 This is a diagram showing an example of a rectangle enclosing a group of pixels. (See diagram for example.) Figure 13 As shown, the counting unit 112 can set multiple rectangles 242 and 243 surrounding the pixel group 241, and set the rectangle 243 with the smallest area among the multiple rectangles 242 and 243 as the rectangle surrounding the pixel group 241 with the smallest area.

[0106] Such as combination Figures 11-13 As described above, the counting unit 112, for each of the multiple body hairs in the skin image 200, (i) extracts the outline of the body hair, and (ii) sets a rectangle that surrounds the extracted outline and has the smallest area.

[0107] Next, as Figure 14 As shown, the counting unit 112 determines the length of the long side of the set rectangle 243 as the length of the body hair. Figure 14This diagram illustrates the process for determining the length of body hair. The length of body hair is represented by the number of pixels corresponding to the long side of the rectangle. Then, the counting unit 112 counts the number of rectangles within the multiple rectangles of the multiple pixel groups whose length of body hair (i.e., the length of the long side of the rectangle) falls within a specified range, as the number of body hairs. The specified range is, for example, represented by the number of pixels greater than a threshold Th1 and less than or equal to a threshold Th2. The threshold Th1 is a value less than the threshold Th2 and is a value equivalent to the number of pixels. For example, the threshold Th1 could be 1 and the threshold Th2 could be 100. The threshold Th1 and threshold Th2 are examples of settings when the shooting distance is 20cm and 1 pixel is equivalent to 0.06mm. That is, the values ​​are not limited to those mentioned above, as long as the threshold Th1 is set to the number of pixels equivalent to 0.06mm and the threshold Th2 is set to the number of pixels equivalent to 6mm.

[0108] [Details on heatmap data generation and processing] Next, details of the heatmap data generation process performed by the calculation unit 114 and the generation unit 115 will be explained.

[0109] The counting result of the counting unit 112 may also include the position (two-dimensional position) of one or more rectangles identified as body hair in the skin image 200. Using the counting result of the counting unit 112, the calculation unit 114 counts the number of rectangles identified as body hair contained in each of the multiple segmented regions after the skin region, which is the target area, is divided in the skin image. Thus, the calculation unit 114 calculates the body hair density for each of the multiple segmented regions. When the multiple segmented regions have the same area, the body hair density can be the number of rectangles identified as body hair contained in one segmented region. When the multiple segmented regions have different areas, the body hair density can be the value obtained by dividing the number of rectangles identified as body hair contained in one segmented region by the area of ​​that segmented region.

[0110] The generation unit 115 classifies the body hair density calculated by the calculation unit 114 into multiple levels for each of the multiple segmented regions, and represents the segmented region in a display manner showing the classified levels. For example, as Figure 15 As shown, the generation unit 115 can classify body hair density into five display levels and generate heatmap data 300 representing the segmented regions by displaying the classified levels. Furthermore, the display mode with multiple levels is not limited to five levels; it can also be six or more levels. Figure 15In this display, a higher density of dots (i.e., a darker color) indicates a higher density of body hair. The display mode can be set to vary depending on the density of the dots (color depth). Alternatively, the display mode can be set to use different colors based on the hue value. For example, when set to use different colors based on the hue value, the area with the highest body hair density can be represented in red, and the area with the lowest body hair density can be represented in blue.

[0111] Then, as Figure 16 As shown, the output unit 116 outputs display information 400 for displaying, in a comparable state, the first heatmap data 402 obtained from the first skin image and the second heatmap data 401 obtained from the second skin image.

[0112] [action] Next, the information processing method executed by the information processing device 100 will be described.

[0113] Figure 17 This is a diagram illustrating an example of a process that captures a skin image and detects hair volume at a second moment (e.g., the first time).

[0114] The information processing device 100 activates the camera 107 and switches to the shooting preparation mode (S11).

[0115] The information processing device 100 determines, based on the detection results detected by the image sensor of the camera 107, whether the illumination around the camera 107 is appropriate for capturing the user's face (S12).

[0116] If the information processing device 100 determines that the illumination is appropriate (S12 "Yes"), it proceeds to step S13; if it determines that the illumination is inappropriate (S12 "No"), it returns to step S11. Alternatively, if the information processing device 100 determines "No" in step S12, it may also display a message prompting adjustment of the illumination due to inappropriate illumination. This message may be displayed on the display 106 or output as voice through a speaker (not shown) provided with the information processing device 100. Furthermore, if the information processing device 100 determines "No" in step S12, it may also return to step S12.

[0117] The information processing device 100 determines whether the size of the user's face detected by the image sensor of the camera 107 is appropriate (S13).

[0118] If the information processing device 100 determines that the face size is appropriate (S13 "Yes"), it proceeds to step S14; if it determines that the face size is inappropriate (S13 "No"), it returns to step S11. Alternatively, if the information processing device 100 determines "No" in step S13, it may also display a message prompting adjustment of the distance between the camera 107 of the information processing device 100 and the user's face due to inappropriate face size. This message may be displayed on the display 106 or output as voice through a speaker (not shown) provided by the information processing device 100. Furthermore, if the information processing device 100 determines "No" in step S13, it may also return to step S13.

[0119] The information processing device 100 takes multiple consecutive shots (S14). For example, the information processing device 100 takes three consecutive shots. As a result, three skin images obtained by shooting the user's face are acquired.

[0120] The information processing device 100 performs a counting process (S15) on the skin image with higher clarity among the three skin images obtained in step S14. Details of the counting process will be provided using... Figure 18 This will be explained later.

[0121] Next, the information processing device 100 determines whether to store the counting result obtained through the counting process (S16). For example, the information processing device 100 may determine whether the counting result is within a specified range. If it is within the specified range, it determines to store the counting result; if it is not within the specified range, it determines not to store the counting result.

[0122] If the information processing device 100 determines that it will store the counting result obtained through the counting process ("Yes" in S16), it proceeds to step S17; if it determines that it will not store the counting result ("No" in S16), it returns to step S11.

[0123] The information processing device 100 stores the counting result obtained through counting processing in the storage unit 117 (S17).

[0124] The information processing device 100 generates display information based on the counting results (S18). The display information may include, for example, the counting results. The display information may also include the heat map data described above.

[0125] The information processing device 100 outputs display information (S19). Specifically, the information processing device 100 displays the display information on the display 106.

[0126] Figure 18This is a flowchart showing the details of the counting process (S15). In step S15, steps S21 to S26, which will be described below, are performed.

[0127] In the skin image 200, the information processing device 100 sets the area between the nose and upper lip of the user's face as the object region 207 for detecting body hair (S21).

[0128] Next, the counting unit 112 of the information processing device 100 performs binarization processing on the skin image 200 in order to detect body hair (S22). As a result, a binarized image 230 is obtained.

[0129] Next, the information processing device 100 determines the pixels that define the outline of a pixel group consisting of pixels with a pixel value of 1 by searching for pixels with a pixel value of 1 among the multiple pixels constituting the binarized image 230. In other words, the information processing device 100 determines the outline of the body hair based on the binarized image 230 (S23).

[0130] Next, the information processing device 100 sets a rectangle (S24) that surrounds the outline (i.e. the outline of the body hair) of each of the multiple pixel groups detected based on the contour.

[0131] Next, the information processing device 100 determines the length of the body hair as the long side of the set rectangle (S25).

[0132] Next, the information processing device 100 counts the number of rectangles whose hair length (i.e., the length of the long side of the rectangle) is within a specified range as the number of hairs (S26).

[0133] Figure 19 This is a diagram illustrating an example of a process that captures skin images and detects hair volume at a first moment (e.g., after the second moment).

[0134] The information processing device 100 activates the camera 107 and switches to the shooting preparation mode (S21).

[0135] The information processing device 100 determines, based on the detection results detected by the image sensor of the camera 107, whether the illumination around the camera 107 is appropriate for capturing the user's face (S32).

[0136] If the information processing device 100 determines that the illumination is appropriate (S32 "Yes"), it proceeds to step S33; if it determines that the illumination is inappropriate (S32 "No"), it returns to step S31. Alternatively, if the information processing device 100 determines "No" in step S32, it may also display a message prompting adjustment of the illumination due to inappropriate illumination. This message may be displayed on the display 106 or output as voice through a speaker (not shown) provided with the information processing device 100. Furthermore, if the information processing device 100 determines "No" in step S32, it may also return to step S32.

[0137] The information processing device 100 determines whether the size of the user's face detected by the image sensor of the camera 107 is appropriate (S33).

[0138] If the information processing device 100 determines that the face size is appropriate (S33 "Yes"), it proceeds to step S34; if it determines that the face size is inappropriate (S33 "No"), it returns to step S31. Alternatively, if the information processing device 100 determines "No" in step S33, it may also display a message prompting adjustment of the distance between the camera 107 of the information processing device 100 and the user's face due to inappropriate face size. This message may be displayed on the display 106 or output as voice through a speaker (not shown) provided by the information processing device 100. Furthermore, if the information processing device 100 determines "No" in step S33, it may also return to step S33.

[0139] The information processing device 100 takes multiple consecutive shots (S34). For example, the information processing device 100 takes three consecutive shots. As a result, three skin images obtained by shooting the user's face are acquired.

[0140] The information processing device 100 performs counting processing (S35) on the skin image with higher clarity among the three skin images obtained in step S34. The counting processing and... Figure 18 The processing is the same.

[0141] The information processing device 100 compares the counting processing result of the first skin image captured at the first moment, i.e., the first counting result, with the hair volume prediction value based on the counting processing result of the second skin image captured at the second moment, i.e., the second counting result, and determines whether the absolute value of the difference between the first counting result and the hair volume prediction value is below a predetermined threshold (S36).

[0142] If the information processing device 100 determines that the absolute value is below a predetermined threshold (S36 "Yes"), it proceeds to step S37; if it determines that the absolute value is greater than the predetermined threshold (S36 "No"), it returns to step S31. Alternatively, if the information processing device 100 determines "No" in step S36, it may also prompt the user to retake the skin image. The message may be displayed on the display 106 or output as voice through a speaker (not shown) provided by the information processing device 100.

[0143] The information processing device 100 calculates an evaluation value showing the hair growth inhibition effect based on the difference between the first counting result and the predicted hair volume value (S37). Alternatively, the evaluation value can also be calculated in step S36 when comparing the first counting result with the second counting result.

[0144] The information processing device 100 stores the first counting result obtained through counting processing (S38).

[0145] The information processing device 100 generates display information based on the first counting result and the second counting result (S39). The display information may include, for example, the first counting result and the second counting result. Furthermore, the display information may also include an evaluation value calculated based on the difference between the first counting result and the predicted gross volume value. Figure 16 As shown, the display information may also include display information 400 that includes first heatmap data 402 obtained from the first skin image and second heatmap data 401 obtained from the second skin image and configured in a comparable manner with the first heatmap data 402.

[0146] The information processing device 100 outputs the generated display information (S40). Specifically, the information processing device 100 displays the display information on the display 106.

[0147] [Effects, etc.] The information processing apparatus 100 according to this embodiment is an information processing apparatus 100 for evaluating the hair growth suppression effect obtained by the optical hair removal apparatus 10. The information processing apparatus 100 includes an acquisition unit 111, a counting unit 112, and an evaluation unit 113. The acquisition unit 111 acquires a skin image 200 obtained by photographing a target area of ​​a user (the subject). The counting unit 112 counts the number of body hairs based on the skin image 200. The evaluation unit 113 evaluates the hair growth suppression effect based on a comparison between the first count result (i.e., the first count result) of a first skin image taken at a first time and a hair volume prediction value at the first time based on a second count result, where the second count result is the result of counting a second skin image taken at a second time, which is a first period earlier than the first time.

[0148] Accordingly, by comparing the first count result corresponding to the first skin image at the first time point with the predicted hair volume based on the hair growth suppression effect obtained by the light treatment of the optical hair removal device 10 at the second time point, it is possible to determine whether the predicted hair growth suppression effect has been achieved. Thus, the hair growth suppression effect obtained by the optical hair removal device 10 can be appropriately evaluated.

[0149] Furthermore, in the information processing apparatus 100 according to this embodiment, the first time is the time after a second period has elapsed following the light treatment performed by the optical hair removal device 10. The second time is the time after the optical hair removal device 10 performs light treatment again and after a second period has elapsed following the light treatment performed by the optical hair removal device 10.

[0150] Therefore, since both the first and second moments can be taken as the moments after the second period following the corresponding light treatment, the hair growth inhibition effect can be evaluated in a way that reduces the error caused by the amount of body hair growth.

[0151] Furthermore, in the information processing apparatus 100 according to this embodiment, when the first counting result is below the hair volume prediction value, the evaluation unit 113 calculates an evaluation value showing the hair growth inhibition effect based on the difference between the first counting result and the hair volume prediction value, and outputs the calculated evaluation value.

[0152] Therefore, if the first count result is below the predicted gross amount, it can be determined that the shooting was successful and an appropriate first count result was obtained, thus enabling the calculation of an appropriate evaluation value.

[0153] Furthermore, in the information processing apparatus 100 of this embodiment, the evaluation unit 113 outputs a prompt message to encourage the user to take a new skin image of the user (the subject) when the absolute value is greater than a predetermined threshold.

[0154] Therefore, if the absolute value is greater than the specified threshold, it can be determined that the shooting has failed, and thus a proper first count result can be obtained by prompting a reshoot.

[0155] Furthermore, in the information processing apparatus 100 according to this embodiment, the counting unit 112, for each of the multiple body hairs in the skin image 200, (i) extracts the outline of the body hair, and (ii) sets a rectangle that surrounds the extracted outline and has the smallest area. The counting unit 112 counts the number of body hairs as the number of rectangles among the set rectangles whose length of at least one of the long side and short side is within a predetermined range.

[0156] Therefore, since it is possible to exclude the counting of body hair from areas other than wrinkles, pores, moles, etc., it is possible to accurately count body hair.

[0157] Furthermore, in the information processing apparatus 100 of this embodiment, the counting unit 112 sets an object region in the skin image 200 between the nose and upper lip of the user's (object's) face as the object for detecting body hair, and sets multiple rectangles within the object region.

[0158] Therefore, it is possible to accurately count the facial hair that grows on a person's face.

[0159] Furthermore, the information processing apparatus 100 according to this embodiment also includes a calculation unit 114, a generation unit 115, and an output unit 116. The calculation unit 114 divides the skin region in the skin image 200, which is the target area, into multiple segmented regions, and calculates the hair density for each of the multiple segmented regions. The generation unit 115 generates heat map data 300 of the hair density in the skin region based on the calculation result of the calculation unit 114. The output unit 116 outputs display information 400 for displaying, in a comparative state, the first heat map data 402 obtained from the first skin image and the second heat map data 401 obtained from the second skin image.

[0160] Therefore, it is possible to visualize the distribution of body hair density.

[0161] [Variation Example] (1) In the above embodiment, although the information processing device 100 is provided with a camera 107, it is not limited thereto. As long as skin images can be acquired (received) from other information processing devices via the communication IF 104, the camera 107 may not be required. For example, the information processing device 100 may acquire skin images from a digital camera, or from an information terminal with a camera function such as a smartphone or tablet terminal, or from other information processing devices that store skin images. In this case, the acquisition unit 111 is implemented by the communication IF 104.

[0162] (2) In the above embodiment, although facial hair is used as an example of body hair in the target area, it is not limited to this and can also be body hair in other areas. For example, body hair in the target area can be body hair growing in any part of the armpit, chest, hands, legs and legs.

[0163] (3) In the above embodiment, although the evaluation unit 113 outputs the prompt information by displaying it on the output unit 116, it is not limited to this. The prompt information can also be output by sending it to the user's portable terminal. The portable terminal can also display the prompt information upon receiving it. As a result, the user can visually confirm the prompt information displayed on the portable terminal, which can encourage the user to use the information processing device 100 to take a picture of the user's skin.

[0164] [other] Furthermore, in the above embodiments, each component can be implemented by dedicated hardware or by executing software programs suitable for each component. Each component can also be implemented by a program execution unit such as a CPU or processor reading and executing software programs recorded on a recording medium such as a hard disk or semiconductor memory. Here, the software of the information processing apparatus, etc., implementing the above embodiments is a program that causes the computer to execute the steps included in the flowchart shown in the figure.

[0165] In addition, the following situations are also included in this disclosure.

[0166] (1) Specifically, each of the above-mentioned devices is a computer system composed of a microprocessor, ROM, RAM, hard disk unit, display unit, keyboard, mouse, etc. A computer program is stored in the RAM or hard disk unit. The microprocessor operates according to the computer program, thereby enabling each device to perform its respective function. Here, the computer program is a combination of multiple command codes that issue instructions to the computer in order to achieve the specified function.

[0167] (2) Some or all of the constituent elements of the above-mentioned devices can be constituted by a system LSI (Large Scale Integration). A system LSI is a multifunctional LSI in which multiple constituent parts are integrated and manufactured on a single chip. Specifically, it is a computer system consisting of a microprocessor, ROM, RAM, etc. The RAM stores a computer program. The microprocessor operates according to the computer program, thereby enabling the system LSI to perform its functions.

[0168] (3) Some or all of the constituent elements of the above-mentioned devices may be composed of IC cards or individual modules that can be installed and removed from each device. The IC card or the module is a computer system composed of a microprocessor, ROM, RAM, etc. The IC card or the module may also include the aforementioned multi-functional LSI. The IC card or the module performs its respective functions by operating according to the computer program through the microprocessor. The IC card or the module may also have tamper-proof properties.

[0169] (4) This disclosure may also be the method shown above. In addition, it may be a computer program that implements these methods, or a digital signal composed of said computer program.

[0170] Furthermore, this disclosure can also be implemented as a computer-readable recording medium on which the computer program or the digital signal is recorded, such as a floppy disk, hard disk, CD-ROM, MO, DVD, DVD-ROM, DVD-RAM, BD (Blu-ray Disc), semiconductor memory, etc. Alternatively, it can be implemented as the digital signal recorded on these recording media.

[0171] Furthermore, this disclosure allows the computer program or the digital signal to be transmitted via electronic communication lines, wireless or wired communication lines, networks such as the Internet, data playback, etc.

[0172] Furthermore, this disclosure may be a computer system having a microprocessor and a memory, wherein the memory stores the aforementioned computer program, and the microprocessor operates according to the computer program.

[0173] Furthermore, the program or digital signal can be transmitted by recording it onto the recording medium, or by transmitting it via the network, etc., thereby allowing it to be executed by a separate computer system.

[0174] (5) The above-described embodiments and the above-described variations can also be combined separately.

[0175] Industrial availability This disclosure is useful as an information processing device or the like, capable of properly evaluating the hair growth inhibition effect obtained by an optical hair removal device.

[0176] Symbol Explanation 10. Optical hair removal device 100 Information Processing Device 101 processor 102 Main Memory 103 Memory 104 Communication IF 105 Input Devices 106 monitor 107 cameras 111 Acquisition Department 112 Counting Section 113 Evaluation Department 114 Computing Department 115 Production Department 116 Output Section 117 Storage Department 200 skin images Feature points 201-206 207 Object Region Areas 208 and 231 210 and 221 pieces 220 Pixels of the processed object 230 Binarized Image 240 yuan 241 pixel group 242, 243 Rectangles 300 heat map data 400 Display Information 401 Second Heatmap Data 402 First Heatmap Data Area A1 Line L1~L3 L4 broken line Th, Th1, Th2 thresholds c constant

Claims

1. An information processing device for evaluating the hair growth inhibition effect obtained by an optical hair removal device. The information processing device includes: The acquisition unit acquires skin images obtained by photographing specific body parts of the subject. The counting unit counts the number of body hairs based on the skin image; and The evaluation unit evaluates the hair growth inhibition effect based on a comparison between the first count result (i.e., the result of counting on a first skin image taken at a first time) and a predicted hair volume value at the first time based on a second count result. The second count result is the result of counting on a second skin image taken at a second time, which is a first period earlier than the first time.

2. The information processing apparatus as described in claim 1, The first moment is the time after the second period has elapsed following the light treatment by the optical hair removal device. The second moment is the moment after the optical hair removal device has performed the light treatment and then performed the light treatment again, and after the second period has elapsed.

3. The information processing apparatus as described in claim 1 or 2, The evaluation unit calculates and outputs an evaluation value of the hair growth inhibition effect based on the difference between the first count result and the hair volume prediction value when the absolute value of the value obtained by subtracting the first count result from the hair volume prediction value is below a predetermined threshold.

4. The information processing apparatus as described in claim 3, When the absolute value is greater than a predetermined threshold, the evaluation unit outputs a prompt message to encourage the subject to take a new skin image of the subject.

5. The information processing apparatus as described in any one of claims 1 to 3, The counting unit, For each of the multiple body hairs in the skin image, (i) extract the contour of the body hair, and (ii) define a rectangle with the smallest area that encloses the extracted contour. The number of rectangles among the set rectangles, where the length of at least one of the long side and the short side is within the specified range, is counted as the number of body hairs.

6. The information processing apparatus as described in claim 5, The counting unit defines an object region for detecting body hair between the nose and upper lip of the subject's face in the skin image, and defines the plurality of rectangles within the object region.

7. The information processing apparatus as described in any one of claims 1 to 3, The information processing device also includes: The calculation unit divides the skin region in the skin image, which is the object area, into multiple segmented regions, and calculates the hair density for each of the multiple segmented regions. The generation unit generates heat map data of the body hair density in the skin region based on the calculation results of the calculation unit. as well as The output unit outputs display information for displaying, in a comparative state, the first heatmap data obtained from the first skin image and the second heatmap data obtained from the second skin image.

8. An information processing method, executed by an information processing device, said information processing device having one or more processors and evaluating the hair growth inhibition effect obtained by an optical hair removal device. The more than one processor To obtain skin images of a subject by photographing specific body parts. The number of body hairs is counted based on the skin image. The hair growth inhibition effect is evaluated by comparing the result of the counting performed on a first skin image taken at a first time point, i.e., the first counting result, with the hair volume prediction value at the first time point based on the second counting result, the second counting result being the result of the counting performed on a second skin image taken at a second time point, the second time point being a first period earlier than the first time point.

9. A program for causing a computer to perform the information processing method of claim 8.

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