Information processing method, information processing device, skin thickness estimation system, and program

Abstract

For example, the present invention provides an information processing method, an information processing device, and a program capable of estimating skin thickness. [Solution] The information processing method performed on a computer according to the present disclosure includes an acquisition step of acquiring an image of the bounce of the sample off the skin after dropping the sample onto the skin, A calculation step of calculating the bounce distance of the sample from the skin based on the captured image, The method includes an estimation step of estimating the thickness of the skin based on the rebound distance.

Description

Technical Field

[0001] The present disclosure relates to an information processing method, an information processing apparatus, a skin thickness estimation system, a program, and the like.

Background Art

[0002] As a method for measuring the structure of the skin and the thickness of the skin or dermis, there is a method of measuring the collagen distribution in the dermis using an ultrasonic measuring device for the skin (for example, DermaLab, manufactured by Cortex Technology) and calculating these from the collagen distribution.

[0003] Further, Patent Document 1 describes a method of calculating the softness and elasticity of the skin using the displacement of a sphere as a method for measuring skin characteristics (Patent Document 1).

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] Thus, there is a problem that a dedicated device for skin measurement is required for measuring the thickness of the skin.

[0006] Therefore, an object of the present disclosure is to provide a new information processing method capable of estimating the thickness of the skin, for example.

Means for Solving the Problems

[0007] To achieve the aforementioned objective, the computer-based information processing method of this disclosure includes an acquisition step of acquiring an image of the sample bouncing off the skin after dropping the sample onto the skin; a calculation step of calculating the bounce distance of the sample from the skin based on the image; and an estimation step of estimating the thickness of the skin based on the bounce distance.

[0008] The information processing device for estimating skin thickness according to this disclosure includes an acquisition unit that acquires an image of the rebound of a sample from the skin after the sample has been dropped onto the skin, a calculation unit that calculates the rebound distance of the sample from the skin based on the image, and an estimation unit that estimates the skin thickness based on the rebound distance.

[0009] The skin thickness estimation system of this disclosure includes a sample to be dropped onto the skin of a subject, a dropping device capable of dropping the sample onto the skin of the subject, an imaging device capable of imaging the sample after it has been dropped, and an information processing device of this disclosure.

[0010] The program of this disclosure causes a computer to perform an acquisition process to acquire an image of the sample bouncing off the skin after dropping the sample onto the skin, a calculation process to calculate the bounce distance of the sample from the skin based on the acquired image, and an estimation process to estimate the skin thickness based on the bounce distance. [Effects of the Invention]

[0011] According to this disclosure, for example, the thickness of the skin can be estimated. [Brief explanation of the drawing]

[0012] [Figure 1] Figure 1 is a schematic diagram of the skin thickness estimation system 100 in Embodiment 1. [Figure 2] Figure 2 is a block diagram of the hardware configuration of the information processing device 10 in the skin thickness estimation system 100 in Embodiment 1. [Figure 3]Figure 3 is a schematic diagram of the skin thickness estimation system 100 in Embodiment 1. [Figure 4] Figure 4 is a flowchart showing the information processing method and program in Embodiment 1. [Figure 5] Figure 5 is a schematic diagram of the calculation of the rebound distance of sample S from the subject's skin T in the skin thickness estimation system 100 in Embodiment 1. [Figure 6] Figure 6 is a graph showing the measurement results of dermal collagen fiber density using DermaLab® Combo in Embodiment 1. [Figure 7] Figure 7 is a graph showing the measurement results of the bounce distance of sample S from the subject's skin T using the skin thickness estimation system 100 in Embodiment 1. [Figure 8] Figure 8 is a graph showing the measurement results of the bounce distance of sample S from the skin model using the skin thickness estimation system 100 in Embodiment 1. [Modes for carrying out the invention]

[0013] <Definition> In this specification, “skin” means the tissue of the skin, which consists of the epidermis, dermis, and subcutaneous tissue. The epidermis is the outermost tissue of the skin and includes the stratum corneum and the germinal layer. The dermis is the main tissue of the skin that forms the space between the epidermis and the subcutaneous tissue and is rich in collagen. The subcutaneous tissue is the innermost tissue of the skin and supports the epidermis and dermis.

[0014] In this specification, "sphere" means a round, three-dimensional object.

[0015] In this specification, "spherical fragment" means a three-dimensional object in which a sphere is cut by one or more planes.

[0016] In this specification, “topical skin preparation” means a preparation used for application to the skin. The topical skin preparation is preferably a preparation applied to the skin surface of the body, such as the face or body. Depending on the form of use, the topical skin preparation may take the form of an ampoule, capsule, powder, granules, liquid, gel, foam, emulsion, sheet, mist, spray, etc. Examples of the forms of use include pharmaceuticals; quasi-drugs; topical or systemic topical skin preparations; medicinal and / or cosmetic preparations applied to the scalp and hair; bath preparations used by adding them to bathwater; other preparations; etc. Examples of topical or systemic skin preparations include basic cosmetics such as lotions, emulsions, creams, ointments, oils, and packs; facial cleansers or skin cleansers such as bar soaps, liquid soaps, and hand washes; massage agents, cleansing agents, depilatory agents, hair removal agents, shaving agents, aftershave lotions, preshave lotions, shaving creams; makeup cosmetics such as foundations, lipsticks, blushes, eyeshadows, eyeliners, and mascaras; perfumes; nail care products, nail polish, nail polish removers; poultices, plasters, tapes, sheets, patches, aerosols; and mouthwashes and other gargles. Examples of medicinal and / or cosmetic preparations applied to the scalp and hair include shampoos, conditioners, hair treatments, pre-hair treatments, permanent solutions, hair dyes, hair styling products, hair tonics, hair growth and nourishing products, poultices, plasters, tapes, sheets, aerosols, etc. Examples of other preparations include deodorants or antiperspirants, antiperspirants, sanitary products, sanitary cotton, wet wipes, etc.

[0017] Hereinafter, the present disclosure will be described in detail with reference to examples and the drawings. However, the present disclosure is not limited by the following description. In the following FIGS. 1 to 8, the same parts may be denoted by the same reference numerals and the description thereof may be omitted. In the drawings, for convenience of explanation, the structure of each part may be appropriately simplified, and the dimensional ratios of each part may be different from the actual ones and may be shown schematically. Also, each embodiment and description can be combined with each other and the description thereof can be incorporated unless otherwise particularly mentioned. In this specification, when the expression "~" is used, it is used in the sense of including the numerical values or physical values before and after it. Also, in this specification, the expression "A and / or B" includes "only A", "only B", and "both A and B".

[0018] (Embodiment 1) Embodiment 1 relates to an information processing apparatus and an information processing method of the present disclosure.

[0019] This embodiment is an example of a skin thickness estimation system including the information processing apparatus of the present disclosure and an information processing method. FIG. 1 is a schematic diagram of a skin thickness estimation system 100 according to Embodiment 1. As shown in FIG. 1, the skin thickness estimation system 100 mainly includes a camera 20 and an information processing apparatus 10. The information processing apparatus 10 mainly includes an acquisition unit 11, a calculation unit 12, and an estimation unit 13. In the skin thickness estimation system 100 of this embodiment, the information processing apparatus 10 is connected to the camera 20. Also, in this embodiment, the information processing apparatus 10 is configured as a server in which the program of the present disclosure is installed.

[0020] The camera 20 is configured to be able to image the movement of the sample S when the sample S is dropped onto the skin. The camera 20 can use, for example, an optical camera (color, monochrome, sepia, etc.), an ultraviolet camera, etc. The camera 20 may use, for example, a smartphone equipped with a camera.

[0021] Sample S is a test object that is dropped onto the skin of a subject (e.g., a human). The material of the sample may be, for example, fibers, resins, minerals, etc. The sample may be beads. Specific examples include nylon beads, urethane beads, silicone beads, glass beads, brass beads, stainless steel beads, etc., and preferably nylon beads, urethane beads, stainless steel, polyester, and silicone. The sample has a shape, size, and weight that allows it to fall in a straight line. The shape of the sample may be, for example, a sphere or a spherical fragment. The size of the sample may be, for example, 3 to 15 mm in diameter. The weight of the sample may be, for example, 0.1 to 3 g.

[0022] The information processing device 10 may be a personal computer (PC) on which the program of this disclosure is installed, or it may be incorporated into a server or the like as part of a system. Alternatively, the information processing device 10 in this embodiment may be a system consisting of one or more computers or servers capable of executing the program of this disclosure, i.e., a cloud computing system. The personal computers may constitute a computer cluster. Although not shown in the figures, the information processing device 10 may be configured to connect to an external terminal of a system administrator via a communication network, allowing the system administrator to manage the information processing device 10 from the external terminal.

[0023] Figure 2 illustrates a block diagram of the hardware configuration of the information processing device 10 in the skin thickness estimation system 100. The information processing device 10 includes, for example, a CPU (central processing unit) 101, memory 102, bus 103, storage device 104, input device 107, display 108, and communication device (communication unit) 109, which are all computational elements. Each part of the information processing device 10 is connected via the bus 103 through its respective interface (I / F).

[0024] The CPU 101 operates in conjunction with other components via controllers (system controller, I / O controller, etc.) and is responsible for the overall control of the information processing device 10. In the information processing device 10, the CPU 101 executes the program 105, captured image 106, and other programs of this disclosure, and also reads or writes various types of information. Specifically, in this embodiment, the CPU 101 functions as an acquisition unit 11, a calculation unit 12, and an estimation unit 13. The information processing device 10 is equipped with a CPU 101 as an arithmetic unit (arithmetic element), but may also be equipped with other arithmetic units such as a GPU (Graphics Processing Unit) or an APU (Accelerated Processing Unit), or a combination of the CPU and these.

[0025] Memory 102 includes main memory. This main memory is also called primary memory. When the CPU 101 performs processing, memory 102 reads various operational programs, such as the program 105 of this disclosure, which are stored in the storage device 104 (auxiliary storage device) described later. The CPU 101 then reads and decodes the data from memory 102 and executes the program. This main memory is RAM (random access memory). Memory 102 may further include ROM (read-only memory).

[0026] Bus 103 can also be connected to external devices. Examples of such external devices include external storage devices (external databases, etc.) and printers. The information processing device 10 can be connected to a communication network, for example, by a communication device 109 connected to bus 103, and can also be connected to external devices such as external servers and terminals via the communication network.

[0027] The storage device 104 is also called an auxiliary storage device, for example, in relation to the main memory (primary memory). As described above, the storage device 104 includes an operating program, including the program 105 of this disclosure. The storage device 104 may store data, including captured images 106, etc. The storage device 104 includes, for example, a storage medium and a drive for reading and writing to the storage medium. The storage medium is not particularly limited and may be internal or external, and examples include HD (hard disk), FD (floppy disk), CD-ROM, CD-R, CD-RW, MO, DVD, flash memory, memory card, etc., and the drive is not particularly limited. The storage device 104 may be, for example, a hard disk drive (HDD) in which the storage medium and the drive are integrated.

[0028] The information processing device 10 further includes an input device 107 and an output device, a display 108. The input device 107 may be, for example, a pointing device such as a touch panel, trackpad, or mouse; a keyboard; imaging means such as a camera or scanner; a card reader such as an IC card reader or magnetic card reader; or an audio input means such as a microphone. The display 108 may be, for example, an LED (light-emitting diode) display or a liquid crystal display. In this embodiment, the input device 107 and the display 108 are configured separately, but the input device 107 and the display 108 may be configured as an integrated unit, such as a touch panel display. Furthermore, in the information processing device 10, the input device 107 and the display 108 are of any configuration and may be omitted, or one or more of them may be included.

[0029] Next, an example of processing using the skin thickness estimation system 100 of this embodiment will be explained using the schematic diagram of the skin thickness estimation system 100 in Figure 3 and the flowchart in Figure 4.

[0030] As shown in Figure 3, the skin thickness estimation system 100 of this embodiment includes a sample S to be dropped onto the subject's skin T, a dropping device 30 capable of dropping the sample S onto the subject's skin T, a camera (imaging device) 20 capable of imaging the sample S after it has been dropped, and an information processing device 10.

[0031] The dropping device 30 can be shaped to accommodate the sample S and to drop or drop the sample S onto the subject's skin T. In this embodiment, the dropping device 30 is a cylindrical tube with a gate, but its shape is not particularly limited, and for example, it may be a housing with a polygonal cross-section.

[0032] The position (height) at which the sample S is dropped onto the subject's skin T can be set as long as it does not harm the subject, taking into consideration the material, shape, size, weight, etc. of the sample S. For example, the height of the sample S can be set to 20-50 cm, with the subject's skin T as the reference point (0 cm).

[0033] The skin sample T of the subject can be from any part of the subject's body, but the arm, back of the hand, cheek, etc. are preferred.

[0034] As shown in Figure 4, the information processing method and program of Embodiment 1 perform the following processes in this order: S1 (acquisition of captured image), S2 (calculation of bounce distance), and S3 (measurement of thickness).

[0035] In step S1, the acquisition unit 11 acquires multiple (n, where n is an integer of 2 or more) captured images 106 taken by the camera 20 (S1). Specifically, first, the sample S is dropped from the dropping device 30 onto the subject's skin T. Simultaneously, the camera 20 is used to capture images 106 over time, including the dropped sample S and skin T. The captured images 106 taken by the camera 20 are stored in the storage device 104 of the information processing device 10. The period during which the camera 20 is used for imaging is, for example, the period during which the bounce distance in step S2, described later, can be calculated. Preferably, the imaging period includes, for example, the time from when the sample S is dropped from the dropping device 30 and makes contact with the skin T, to the time after contact with the skin T, when it bounces off the skin T and reaches the highest point after the jump. The camera 20 captures images 106 over time during the imaging period. The number of images 106 captured by the camera 20 can be multiple, for example, 2 to 100, 2 to 50, 2 to 20, or 2 to 10. The camera 20 may capture video. In the case of video, the video frame rate can be, for example, 10 to 500 fps (frames per second) or 100 to 300 fps.

[0036] The acquisition unit 11 acquires the captured images 106 stored in the storage device 104 of the information processing device 10. The number of captured images 106 acquired by the acquisition unit 11 can be multiple, for example, 2 to 100 images, 2 to 50 images, 2 to 20 images, or 2 to 10 images. The multiple captured images 106 include images taken from the time the sample S touches the subject's skin T after being dropped onto the subject's skin T, through the period after the sample S touches the subject's skin T, and up to the highest point after bouncing off the skin T.

[0037] Next, in step S2, the calculation unit 12 calculates the bounce distance of the sample S from the subject's skin T based on the captured images 106 (S2). Specifically, in step S2, first, the position (coordinates) of the sample S in each captured image 106 is calculated. The position of the sample S may be, for example, the position of the center of the sample S or the position of the upper end of the sample S. Next, in step S2, the position of the sample S in each captured image 106 is compared, and the lowest position (lowest point) and the highest position (highest point) of the sample S are extracted from multiple captured images 106. Specifically, in step S2, the positions (heights) of multiple captured images 106 are compared, and as shown in Figure 5, the lowest point (height) of the sample S in multiple captured images 106 (the position of the center of the sample S in Figure 5(A)) and the highest point (height) after bouncing off the subject's skin T and jumping (the position of the center of the sample S in Figure 5(B)) are extracted. Then, in step S2, the rebound distance is calculated from the difference between the lowest point of the sample S and the highest point after it bounces off the subject's skin T (Figure 5(C)).

[0038] Next, in step S3, the estimation unit 13 estimates the skin thickness based on the bounce distance calculated in step S2. As described later, the bounce distance of the sample S correlates with the skin thickness, particularly the dermal thickness. Therefore, in step S3, the estimation unit 13 estimates the skin thickness using this correlation. Specifically, in step S3, the skin thickness is estimated based on the bounce distance using a pre-created correlation between the bounce distance and the skin thickness. As an example, in step S3, the skin thickness is estimated using the bounce distance and an equation or model relating to the correlation between the bounce distance and the skin thickness. This equation or model can be created, for example, by analyzing the skin thickness and the corresponding bounce distance using a skin aging model through multivariate analysis. Furthermore, the above formula or model can be constructed, for example, by analyzing skin thickness and the corresponding bounce distance using multivariate analysis with subjects of different ages. The above formula and / or model may include regression equations and / or regression models, or multiple regression equations. The above formula may also be a calibration curve.

[0039] Then, the information processing method of Embodiment 1 terminates.

[0040] (Effects of Embodiment 1) In the information processing device 10 of Embodiment 1, the rebound distance is calculated from the lowest point of the sample S when it comes into contact with the subject's skin T and the highest point after contact with the subject's skin T. As will be described later, in the information processing device 10 of Embodiment 1, the rebound distance is correlated with the thickness of the skin, particularly the thickness of the dermis. Therefore, using this correlation, the thickness of the skin, particularly the thickness of the dermis, can be estimated based on the rebound distance. Thus, the estimation system 100 of Embodiment 1 can estimate the thickness of the skin, particularly the thickness of the dermis. Furthermore, it is generally believed that the thickness of the skin correlates with the amount of collagen contained in the dermis that makes up the skin. Thus, the estimation system 100 of Embodiment 1 can also estimate, for example, the amount of collagen in the subject's skin.

[0041] Figure 6 shows the results of measuring the dermal collagen fiber density of the skin (area) of the arm of three healthy female subjects (N=3, aged 20-40) using DermaLab® Combo. Figure 7 shows the results of calculating the bounce distance when a urethane resin ball (6.35 mm, 0.163 g) was dropped from a height of 30 cm onto the skin of the arm of three healthy female subjects (N=3, aged 20-40) using the estimation system 100 of Embodiment 1, and photographed with camera 20. The measurement results shown in Figure 7 are the results of measurements performed immediately after the measurement shown in Figure 6 on the same subjects (N=3, aged 20-40). The values ​​shown in Figure 6 are: Subject A: 80.15, Subject B: 81.65, Subject C: 58.71. The values ​​shown in Figure 7 are: Subject A: 10.23, Subject B: 10.53, and Subject C: 5.05. The measurement results shown in Figures 6 and 7 show a similar trend for all three subjects: A, B, and C. In other words, it is considered that the amount of collagen in the subject's skin can also be estimated using the estimation system 100 of Embodiment 1.

[0042] Figure 8 shows the results of calculating the bounce distance when a urethane resin ball (6.35 mm, 0.163 g) was dropped from a height of 30 cm onto skin models with different skin thicknesses using the estimation system 100 of Embodiment 1, and the results were captured by camera 20. The skin model (dermal thickness change model) uses a model that simulates the skin structure and the hardness of each layer, in which a urethane fat layer (hardness 15 kPa), a urethane dermal layer (hardness 80 kPa), and a silicone epidermal layer (hardness 1500 kPa) are stacked in this order. The bounce distance is the difference between the lowest point of the urethane resin when it contacts the skin model and the highest point of the urethane resin after it bounces off the skin model and jumps. The values ​​shown in Figure 8 are: Model a (aging skin model): 13.06, Model b (slightly aging skin model): 15.83, Model c (normal skin model): 18.21. As shown in Figure 8, the bounce distance increases in the order of aging skin model, slightly aging skin model, and normal skin model, i.e., as the thickness of the dermis increases, indicating a correlation between skin thickness (thickness of the dermis) and bounce distance. Therefore, it can be said that the estimation system 100 of Embodiment 1 can be used to calculate the bounce distance for each skin model and to create an equation and / or model relating to the correlation between the bounce distance and the skin thickness. Furthermore, according to the estimation system 100 of Embodiment 1, for example, the thickness of the subject's skin can be estimated by comparing the bounce distance of sample S from the subject's skin T with the equation and / or model relating to the correlation between the bounce distance and skin thickness. It has also been confirmed that the bounce distance decreases with age when using subjects of different ages.

[0043] The estimation system 100 of Embodiment 1 may, for example, suggest a topical skin agent based on the estimated skin thickness. As mentioned above, the skin thickness is estimated to reflect the amount of collagen in the dermis. There are various topical skin agents that can restore the amount of collagen in the dermis. Therefore, by pre-setting the suggested topical skin agents according to the skin thickness or a numerical range of skin thickness, it is possible to suggest a topical skin agent suitable for restoring the collagen amount in the subject's skin based on the subject's skin thickness.

[0044] (Embodiment 2) The program of this embodiment is a program that causes a computer to execute the information processing method described herein. In the program of this embodiment, "processing" can also be said to be, for example, a "procedure" or an "instruction". The program of this embodiment may also be recorded on, for example, a computer-readable storage medium. The storage medium is not particularly limited and includes, for example, random access memory (RAM), read-only memory (ROM), hard disk (HD), solid state drive (SSD), optical disc, floppy disk (FD), and the like.

[0045] While the present disclosure has been described above with reference to embodiments, the present disclosure is not limited to the embodiments described above. Various modifications to the structure and details of the present disclosure may be made that will be understood by those skilled in the art within the scope of the present disclosure.

[0046] <Note> Some or all of the above embodiments and examples may be described as follows, but are not limited to the following. <Information Processing Methods> (Note 1) The process involves dropping a sample onto the skin and then acquiring an image of the sample bouncing off the skin. A calculation step of calculating the bounce distance of the sample from the skin based on the captured image, A computer-based information processing method, comprising an estimation step of estimating the thickness of the skin based on the rebound distance. (Note 2) The information processing method described in Appendix 1, wherein the calculation step involves calculating the rebound distance from the lowest point of the sample at the time of skin contact and the highest point after contact with the skin in the captured image. (Note 3) The information processing method according to Appendix 1 or 2, wherein the estimation step involves estimating the thickness of the skin based on the rebound distance, using the correlation between the rebound distance and the thickness of the skin. (Note 4) The information processing method according to any one of the appendices 1 to 3, wherein the captured image includes an image taken from the time the sample comes into contact with the skin after the sample is dropped onto the skin, through the period after the sample comes into contact with the skin, until the sample reaches its highest point. (Note 5) The information processing method according to any one of the appendices 1 to 4, wherein the sample is a spherical fragment or a sphere. (Note 6) The information processing method described in any one of the appendices 1 to 5, wherein the thickness of the skin is the thickness of the dermis. <Information Processing Device> (Note 7) After dropping the sample onto the skin, an acquisition unit acquires an image of the sample bouncing off the skin, A calculation unit that calculates the bounce distance of the sample from the skin based on the captured image, An information processing device for estimating skin thickness, comprising an estimation unit that estimates skin thickness based on the rebound distance. (Note 8) The calculation unit calculates the rebound distance from the lowest point of the sample at the time of skin contact and the highest point after contact with the skin in the captured image, as described in Appendix 7. (Note 9) The information processing apparatus according to Appendix 7 or 8, wherein the estimation unit estimates the thickness of the skin based on the rebound distance, using the correlation between the rebound distance and the thickness of the skin. (Note 10) The information processing apparatus according to any one of appendices 7 to 9, wherein the captured image includes an image taken from the time the sample comes into contact with the skin after the sample is dropped onto the skin, through the period after the sample comes into contact with the skin, until the sample reaches its highest point. (Note 11) The information processing apparatus according to any one of appendices 7 to 10, wherein the sample is a spherical missing body or a sphere. (Note 12) The information processing device according to any one of the appendices 7 to 11, wherein the thickness of the skin is the thickness of the dermis. <System for estimating skin thickness> (Note 13) The sample to be dropped onto the subject's skin, The aforementioned sample is dropped onto the skin of the subject using a dropping device, An imaging device capable of imaging the sample after it has fallen, A system for estimating skin thickness, comprising an information processing device described in any of Appendix 7 to 12. <Program> (Note 14) On the computer, After dropping the sample onto the skin, an acquisition process is performed to obtain an image of the sample bouncing off the skin. A calculation process is performed to calculate the bounce distance of the sample from the skin based on the captured image, A program that performs an estimation process to estimate the thickness of the skin based on the aforementioned bounce distance. (Note 15) The calculation process described above involves calculating the rebound distance from the lowest point of the sample at the time of skin contact and the highest point after contact with the skin in the captured image, as described in Appendix 14. (Note 16) The estimation process described above uses the correlation between the rebound distance and the skin thickness to estimate the skin thickness based on the jump distance, as described in Appendix 14 or 15. (Note 17) The program according to any one of appendices 14 to 16, wherein the captured images include images taken from the time the sample makes contact with the skin after the sample is dropped onto the skin, until the sample reaches its highest point after contact with the skin. (Note 18) The program described in any of appendices 14 to 17, wherein the sample is a spherical fragment or a sphere. (Note 19) The aforementioned skin thickness is the thickness of the dermis, as described in any of the programs in Appendix 14 to 18. <Recording medium> (Note 20) A computer-readable recording medium on which a program described in any of the appendices 14 to 19 is recorded. [Explanation of symbols]

[0047] 10 Information Processing Devices 11 Acquisition Department 12 Calculation Section 13 Estimation part 20 cameras 30 Drop device 100 Skin Thickness Estimation System 101 CPU 102 memory 103 Bus 104 Storage device 105 Programs 106 Acquired Images 107 Input device 108 displays 109 Communication devices

Claims

1. The process involves dropping a sample onto the skin and then acquiring an image of the sample bouncing off the skin. A calculation step of calculating the bounce distance of the sample from the skin based on the captured image, A computer-based information processing method, comprising an estimation step of estimating the thickness of the skin based on the rebound distance.

2. The information processing method according to claim 1, wherein in the calculation step, the rebound distance is calculated from the lowest point of the sample at the time of skin contact and the highest point after contact with the skin in the captured image.

3. The information processing method according to claim 1 or 2, wherein the estimation step involves estimating the thickness of the skin based on the rebound distance, using the correlation between the rebound distance and the thickness of the skin.

4. The information processing method according to any one of claims 1 to 3, wherein the captured image includes an image taken from the time the sample comes into contact with the skin after the sample is dropped onto the skin, until the sample reaches its highest point after contact with the skin.

5. The information processing method according to any one of claims 1 to 4, wherein the sample is a spherical missing body or a sphere.

6. After dropping the sample onto the skin, an acquisition unit acquires an image of the sample bouncing off the skin, A calculation unit that calculates the bounce distance of the sample from the skin based on the captured image, An information processing device for estimating skin thickness, comprising an estimation unit that estimates skin thickness based on the rebound distance.

7. The information processing apparatus according to claim 6, wherein the calculation unit calculates the rebound distance from the lowest point of the sample at the time of skin contact and the highest point after contact with the skin in the captured image.

8. The information processing apparatus according to claim 6 or 7, wherein the estimation unit estimates the thickness of the skin based on the rebound distance, using the correlation between the rebound distance and the thickness of the skin.

9. The information processing apparatus according to any one of claims 6 to 8, wherein the captured image includes an image taken from the time the sample comes into contact with the skin after the sample is dropped onto the skin, through the period after the sample comes into contact with the skin, until the sample reaches its highest point.

10. The information processing apparatus according to any one of claims 6 to 9, wherein the sample is a spherical missing body or a sphere.

11. The sample to be dropped onto the subject's skin, The aforementioned sample is dropped onto the skin of the subject using a dropping device, An imaging device capable of imaging the sample after it has fallen, A system for estimating skin thickness, comprising an information processing device according to any one of claims 6 to 10.

12. On the computer, After dropping the sample onto the skin, an acquisition process is performed to obtain an image of the sample bouncing off the skin. A calculation process is performed to calculate the bounce distance of the sample from the skin based on the captured image, A program that performs an estimation process to estimate the thickness of the skin based on the aforementioned bounce distance.

Images