Skin analysis system, configuration method and display device

Abstract

The invention discloses a skin analysis system, a configuration method and a display device, and the configuration method comprises the steps: obtaining a skin analysis task, determining at least one corresponding target diffraction feature, determining m regions at a first surface according to the target diffraction feature, obtaining a detection physiological index and a preset calibration physiological index, determining a loss value based on the detected physiological index and the calibrated physiological index, updating the structural information of the optical element, updating the configuration information of the processor or updating both the structural information of the optical element and the configuration information of the processor based on the loss value, and obtaining a configured skin analysis system corresponding to the skin analysis task. According to the configuration method provided by the invention, the skin analysis system considering skin detection accuracy and user privacy protection can be obtained through configuration.

Description

Technical Field

[0001] The present application relates to the field of optical detection technology, and in particular to a skin analysis system, configuration method, and display device. Background Art

[0002] As the largest organ in the human body, the skin serves as a physical barrier against external aggressors (protecting against pathogens and pollutants) and a key tissue for regulating body temperature and secretion. The skin's health is easily damaged by internal and external factors such as ultraviolet rays, environmental pollution, and aging, leading to wrinkles, dryness, and a decrease in barrier function. For example, the water content of the stratum corneum directly affects the skin's appearance, elasticity, and function. Therefore, accurate analysis of skin condition is crucial for health management.

[0003] Existing technologies primarily rely on traditional cameras to directly capture visible light images of the user's face and use algorithms to analyze the skin's surface features. While this type of technology can perform basic analysis, it suffers from fundamental flaws. First, the raw images captured by the device contain complete facial biometric features, posing a privacy risk of malicious recovery and identification during data storage or transmission, and failing to meet increasingly stringent personal data protection regulations. Second, due to limitations in imaging and algorithmic analysis capabilities, existing solutions can only capture limited information about the skin's surface and are unable to simultaneously extract deeper features. Consequently, existing technologies struggle to balance the two core requirements of privacy and security with the precise analysis of multi-dimensional skin features, hindering the development of the health monitoring field. Summary of the Invention

[0004] One of the purposes of this application is to provide a configuration method for a skin analysis system to solve the problem that the skin analysis system configured in the prior art cannot take into account both privacy security and the need for accurate analysis of multi-dimensional skin features.

[0005] One of the objectives of this application is to provide a skin analysis system.

[0006] One of the purposes of this application is to provide a display device.

[0007] To achieve one of the aforementioned objectives, one embodiment of the present application provides a configuration method for a skin analysis system. The skin analysis system includes: an optical element including a first surface for receiving incident light from a subject and modulating it to generate diffraction signature information; and a processor for determining a skin physiological indicator of the subject based on the diffraction signature information. The configuration method includes: obtaining a skin analysis task, determining at least one corresponding target diffraction signature, determining m regions on the first surface based on the target diffraction signature, the m regions being respectively used to modulate incident light in m target wavelength bands corresponding to the target diffraction signature, where m is an integer greater than or equal to 1; obtaining a detected physiological indicator and a preset calibration physiological indicator, the detected physiological indicator being obtained based on detection of a preset calibration object by the skin analysis system, the calibration physiological indicator corresponding to the calibration object; determining a loss value based on the detected physiological indicator and the calibration physiological indicator; and updating, based on the loss value, structural information of the optical element, configuration information of the processor, or both the structural information of the optical element and the configuration information of the processor to obtain a configured skin analysis system corresponding to the skin analysis task.

[0008] Optionally, the optical element is configured to generate diffraction feature information comprising only high-order skin features.

[0009] Optionally, the configuration method includes: determining m target bands corresponding to the target diffraction characteristics, and configuring the structure of the m regions to modulate only the incident light of the corresponding target bands.

[0010] Optionally, the target band includes at least one of the following: a band with a wavelength of 380nm to 780nm or other natural light bands, a band with a wavelength of 780nm to 2526nm or other near-infrared light bands, a band with a wavelength of 590nm to 610nm or other orange light bands, a band with a wavelength of 440nm to 475nm or other blue light bands, a band with a wavelength of 492nm to 577nm or other green light bands, a band with a wavelength of 570nm to 585nm or other yellow light bands, and a band with a wavelength of 625nm to 740nm or other red light bands.

[0011] Optionally, at least one of the following is included: obvious spot characteristics, pigmentation characteristics, skin texture characteristics and smoothness characteristics correspond to the natural light band, high-density color spot characteristics correspond to the orange light band, hemoglobin characteristics correspond to the near-infrared light band, acne characteristics, epidermal inflammation characteristics correspond to the blue light band, epidermal color spot characteristics, acne scar characteristics, skin redness characteristics, vascular dilation characteristics correspond to the green light band, sensitive state characteristics, microcirculation characteristics correspond to the yellow light band, collagen characteristics, deep inflammation characteristics, structural depression characteristics, pigment depth characteristics correspond to the red light band.

[0012] Optionally, the first surface is provided with microstructure units to form a metasurface, and the configuration method includes at least one of the following: updating the phase arrangement of the microstructure units in m areas at the first surface of the optical element based on the loss value; updating the material of the microstructure units in m areas at the first surface of the optical element based on the loss value.

[0013] Optionally, the skin analysis system includes: a light sensor, arranged on the light-emitting side of the optical element, the light sensor is used to receive diffraction characteristic information and generate a diffraction characteristic image, and the processor is used to determine the skin physiological indicators of the subject based on the diffraction characteristic image.

[0014] Optionally, the optical element is configured according to at least one of the following: the optical element modulates the incident light to generate diffraction characteristic information for constituting a blurred image of the object under test, and the optical element modulates the incident light to generate diffraction characteristic information of an image containing high-order skin features of the face of the object under test.

[0015] Optionally, the processor is configured according to at least one of the following: the processor determines the skin physiological indicators of the subject by implementing a convolutional neural network, and the processor is used to determine the skin health level based on diffraction feature information and a preset database.

[0016] To achieve one of the above-mentioned objectives, one embodiment of the present application provides a skin analysis system, comprising: an optical element including a first surface for receiving incident light from a subject and generating diffraction characteristic information; a processor for determining skin physiological indicators of the subject based on the diffraction characteristic information, wherein the skin analysis system is configured according to any configuration method of the present application.

[0017] Optionally, the first surface is provided with microstructure units to form a metasurface, the first surface is circular, and the first surface is configured according to one of the following: the m regions are arranged along the first diameter of the first surface to form a strip, the m regions are arranged from the center of the first surface along the first radius of the first surface to form a concentric circle and m-1 concentric rings, and the m regions are arranged around the center of the first surface to form a fan.

[0018] To achieve one of the above-mentioned purposes, an embodiment of the present application provides a display device, comprising: any skin analysis system of the present application, and a display screen for displaying the skin physiological indicators.

[0019] Optionally, the display device includes: a reflector, used to present an image of the object under test when the display device is implemented.

[0020] Compared with the prior art, the configuration method of the skin analysis system provided in the application can determine the physiological indicators of the skin through the diffraction characteristic information corresponding to multiple wave bands, and can detect the physiological conditions of the skin in multiple dimensions; the skin analysis system is based on diffraction characteristic information for analysis, so that the skin analysis is not limited to clear imaging of the tested object, thereby effectively protecting the privacy of the user; the skin analysis system is configured and trained in an end-to-end manner, so that the optical system containing the optical element and the electrical system containing the processor can be configured and fixed as a whole, the accuracy and reliability of the output results can be improved, and error accumulation can be prevented. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 is a schematic diagram of a skin analysis system in an embodiment of the application.

[0022] Figure 2 is a schematic diagram of a first surface in an embodiment of the application.

[0023] Figure 3 is a schematic diagram of a display device in an embodiment of the application.

[0024] Figure 4 is a schematic diagram of a configuration method of a skin analysis system in an embodiment of the application.

[0025] Figure 5 is a schematic diagram of a tested object and a diffraction characteristic image in an embodiment of the application. DETAILED DESCRIPTION

[0026] The application will be described in detail below with reference to the specific embodiments shown in the drawings. However, these embodiments do not limit the application, and the structural, method, or functional changes made by those of ordinary skill in the art based on these embodiments are also included in the protection scope of the application.

[0027] It should be noted that the term "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article, or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or other elements inherent to such a process, method, article, or device.

[0028] In addition, the terms "first", "second", "third", "fourth", etc. are only for descriptive purposes and cannot be understood as indicating or implying relative importance. There is no necessary relationship between the terms "first", "second", "third", "fourth", etc. For example, an embodiment provided in the application contains "second", which does not mean that the embodiment necessarily contains "first", and so on.

[0029] Skin analysis system An embodiment of the present application provides a skin analysis system 100, such as Figure 1 shown.

[0030] The skin analysis system 100 includes an optical element 11. The optical element 11 includes a first surface M1. The optical element 11 is configured to receive incident light from a subject T1 and generate diffraction characteristic information.

[0031] The first surface M1 may be provided with microstructure units to form a metasurface. The optical element 11 including the first surface M1 formed as a metasurface may be defined as a metasurface optical element.

[0032] Metasurface optical elements are artificial layered materials with dimensions smaller than or approximately equal to the wavelength, and can be considered the two-dimensional counterpart of metamaterials. These elements can manipulate the polarization, phase, amplitude, frequency, and propagation mode of electromagnetic waves through subwavelength microstructure units (or metastructure units) on their surfaces, enabling properties such as beam shaping, beam deflection, superlenses, superholography, optical rotation, and anti-reflection and anti-reflection.

[0033] At the same time, the metasurface optical element is a sub-wavelength optical element, which is suitable for the current micron-scale sensor architecture. At the same time, its preparation process is compatible with mature semiconductor sensor technology and has strong practicality and economy.

[0034] Specifically, the metasurface optical element includes a substrate and a plurality of microstructure units arranged in an array on the substrate, and a nanostructure is provided at the center and / or vertex position of each microstructure unit. The microstructure unit is obtained by dividing the metasurface optical element to obtain a structure unit centered on each nanostructure. Among them, the nanostructures in each period constitute a microstructure unit. The microstructure unit is a densely packed figure, for example, it can be a regular quadrilateral, a regular hexagon, a fan, etc., each period contains a nanostructure, and the vertex and / or center of the microstructure unit can be provided with a nanostructure. In the case where the microstructure unit is a regular hexagon, at least one nanostructure is provided at each vertex and center position of the regular hexagon. Similarly, the same is true in the case of a fan or a square.

[0035] Among them, the substrate of the metasurface optical element can be selected from, for example: glass materials with similar refractive indices such as silicon dioxide, BF33, silicon, polymethyl methacrylate, etc.; the nanostructure can be selected from, for example: monomer silicon (c-Si), polycrystalline silicon (p-Si), amorphous silicon (a-Si), compound semiconductors (such as GaN, GaP, GaAs, SiC, etc.), TiO2, Si3N4, AlSb, AlAs, AlGaAs, AlGaInP, BP, ZnGeP2 and other suitable materials and combinations of the above materials.

[0036] Specifically, the nanostructure can be configured as a polarization-dependent structure or a polarization-independent structure. Depending on the usage scenario, the nanostructure unit can be configured as a polarization-dependent structure or a polarization-independent structure. Polarization-independent structures include, for example, cylinders, square cylinders, cross cylinders, and square cylinders with circular holes. Polarization-dependent structures include, for example, elliptical cylinders, rectangular cylinders, and hexagonal prisms. The nanostructure can be a positive structure or a negative structure. For example, the shapes of the nanostructure include cylinders, hollow cylinders, square prisms, and hollow square prisms.

[0037] The metasurface optical element may further include a protective layer covering the nanostructure. The material of the protective layer may be any material having a low refractive index and absorption coefficient in the visible light or near-infrared band, such as silicon dioxide (SiO2), spin-on glass (SOG), or polymers such as polymethyl methacrylate (PMMA), polydimethylsiloxane (PDMS), polymethylpentene (PMP), and combinations of the above materials, or air (i.e., no protective layer is provided).

[0038] One or more metasurfaces may be provided on the optical element 11. For example, a first surface M1 of the optical element 11 may be provided with a plurality of microstructure units to form a metasurface. The optical element 11 may also include a second surface, which may also be provided with a plurality of microstructure units to form another metasurface. The first surface M1 and the second surface may be two opposing surfaces of the substrate of the optical element 11.

[0039] Metasurfaces are used to achieve feature extraction. Compared with an optical element with only one metasurface, an optical element 11 provided with multiple metasurfaces has a stronger feature extraction capability and can obtain more skin feature information.

[0040] When the optical element 11 is disposed on one side of the object under test, the first surface M1 of the optical element 11 can be close to the object under test, and the second surface of the optical element 11 can be far away from the object under test; at least one of the first surface M1 and the second surface is formed as a metasurface.

[0041] In one embodiment, the optical element 11 may be a refractive optical element. In one embodiment, the optical element 11 may include a refractive optical element. The refractive optical element may be used to replace the metasurface optical element in the above-mentioned embodiment. The refractive optical element may include, but is not limited to, a lens or prism made of materials such as optical glass, optical plastic, or optical crystal.

[0042] In one embodiment, the optical element 11 may be a diffractive optical element. In one embodiment, the optical element 11 may include a diffractive optical element. The diffractive optical element may be used to replace the metasurface optical element in the above-mentioned embodiment. Diffractive optical elements may include, but are not limited to, two-step or multi-step diffractive optical elements, gratings, Dammann gratings, metasurfaces, holograms, diffusers, phase masks, intensity masks, spatial light modulators, and the like.

[0043] In one embodiment, the optical element 11 may be a scattering medium element. In one embodiment, the optical element 11 may include a scattering medium element. The scattering medium element may be used to replace the metasurface optical element in the above embodiment. The scattering medium element may include, but is not limited to, frosted glass.

[0044] When configuring the skin analysis system, at least one of the following may be specifically included: for the multiple optical elements 11, parameters such as the combination of different optical elements and the spacing between each optical element may be configured; for the metasurface optical element, parameters such as the arrangement period, material, shape, size, and position coordinates of its nanostructure may be configured; for the refractive optical element, parameters such as the refractive index and curvature radius may be configured; for the diffractive optical element, parameters such as its focal length characteristics, the phase function of the diffraction surface, the radial radius of each annular zone mutation point of the diffraction surface, the annular zone depth of the diffraction surface, and the diffraction efficiency may be configured.

[0045] Regardless of the type of optical element, the optical element may include a first surface, and the first surface may be divided into m regions to process incident light of different wavelength bands.

[0046] The skin analysis system 100 includes a processor 12. The processor 12 is configured to determine the skin physiological index of the subject according to the diffraction characteristic information.

[0047] In one embodiment, the processor 12 directly processes the diffraction characteristic information to determine the skin physiological index. In one embodiment, the diffraction characteristic information is transformed to generate another data information, and the processor 12 determines the skin physiological index of the subject based on the data information.

[0048] The skin physiological index may be information on the type of skin abnormality and location information of the skin abnormality. The skin abnormality may be spots, sensitivity, inflammation, acne scars, acne, wrinkles, etc.

[0049] The skin physiological index may also be evaluation information of skin abnormalities. For example, after identifying a skin abnormality, the severity of the skin abnormality is determined and quantified to obtain the evaluation information. The evaluation information may be a rating such as mild, moderate, or severe, or may be a numerical score.

[0050] The skin physiological index may also be information about the overall health of the skin. For example, based on information indicating skin abnormalities, the overall health of the skin may be determined by comparing it with a pre-defined database. The pre-defined database may be a public database on skin conditions such as ISIC 2019 or the Dermofit Image Library, or a private database established by screening and classifying public databases.

[0051] The skin physiological index may also be other quantitative indexes generated based on high-level skin characteristics, such as pigmentation index, moisture index, and oiliness index.

[0052] The high-order skin features may be hyperspectral features of the skin.

[0053] The high-order skin feature may be a type of the target diffraction feature. The target diffraction feature may include a high-order skin feature.

[0054] When the processor 12 is in operation, the aforementioned technical solution can be implemented by implementing a convolutional neural network. The convolutional neural network is configured to take the output of the optical system including the optical element 11 as input, and to process the output with the goal of determining skin abnormality or health, so as to determine the skin physiological indicators of the subject.

[0055] The skin analysis system 100 is configured according to a configuration method for a skin analysis system, which may be a configuration method described in any of the technical solutions below in this application.

[0056] When the processor 12 is operating to construct a convolutional neural network, the model parameters of the convolutional neural network and the configuration of the optical element 11 can be performed simultaneously, so that the electrical system including the convolutional neural network and the optical system can be configured and fixed as a whole. The model parameters of the convolutional neural network can be the weights of each parameter therein.

[0057] The skin analysis system 100 may further include a light sensor 13. The light sensor 13 may be disposed on the light-emitting side of the optical element 11. The light sensor 13 may be configured to receive diffraction characteristic information and generate a diffraction characteristic image.

[0058] The light sensor 13 may be a CMOS (Complementary Metal Oxide Semiconductor) photosensitive element (CIS), a CCD (Charge Coupled Device) photosensitive element or an array photodetector.

[0059] When skin analysis system 100 is implemented, optical element 11 receives a light signal reflected from subject T1. Different regions of optical element 11 respond to light signals of different wavelengths, generating corresponding diffraction signature information. This diffraction signature information is output to optical sensor 13 as a first distribution. Actual skin features corresponding to this diffraction signature information have a second distribution at subject T1. The first and second distributions can be identical or corresponding. Thus, the diffraction signature image generated by optical sensor 13 can indicate the corresponding locations of skin features at subject T1, facilitating further analysis.

[0060] In an embodiment where the diffraction feature information only includes high-order skin features, the diffraction feature image may be a high-order feature image, which only shows skin features corresponding to the configuration of the skin analysis system 100 and does not include other private information of the subject T1.

[0061] The high-order feature image may be a diffraction feature image for showing high-order skin features.

[0062] For example, when the skin analysis system 100 is configured to perform a first analysis task on the subject T1, the configured optical element 11 only obtains diffraction feature information in several wavelength bands corresponding to the first analysis task. Therefore, the resulting diffraction feature image only contains several high-order skin features corresponding to the first analysis task, while other information of the subject T1 is missing or ignored to a certain extent. It is precisely because of this missing or ignored information that other irrelevant information is hidden or blurred, thereby protecting the privacy of the subject T1.

[0063] The diffraction characteristic information may be in the form of a light signal.

[0064] The diffraction characteristic image may be in the form of digital information; the diffraction characteristic image includes all the diffraction characteristic information.

[0065] The skin analysis system 100 may include one or more optical elements 11. When the skin analysis system 100 includes multiple optical elements 11, the multiple optical elements 11 may have the same or different parameters and may be spaced apart in the direction of propagation of the incident light. The multiple optical elements 11 and the light sensor 13 together constitute the optical system of the skin analysis system 100.

[0066] The optical system may further include a lens.

[0067] In one embodiment, the skin analysis system 100 includes at least one lens, at least one optical element 11 and a light sensor 13 .

[0068] In one embodiment, the lens, the optical element 11, and the light sensor 13 may be arranged in sequence in the direction of propagation of the incident light. In another embodiment, a partial lens, the optical element 11, another partial lens, and the light sensor 13 may be arranged in sequence in the direction of propagation of the incident light, or a partial optical element 11, a lens, another partial optical element 11, and the light sensor 13 may be arranged in sequence, or a partial lens, a partial optical element 11, another partial lens, another partial optical element 11, and the light sensor 13 may be arranged in sequence.

[0069] The processor 12 may be configured to determine skin physiological indicators of the subject T1 according to the diffraction characteristic image.

[0070] The processor 12 may be coupled to the optical sensor 13 to receive the diffraction characteristic image. In this embodiment, the processor 12 may determine the skin physiological index based on the diffraction characteristic image containing diffraction characteristic information.

[0071] The processor 12 may also perform operations such as spectral data normalization to implement pre-processing of the diffraction feature image.

[0072] Combine Figure 2 As shown, the first surface M1 is provided with microstructure units to form a super surface.

[0073] The first surface M1 may be circular.

[0074] The circular first surface M1 can achieve uniform modulation of the incident light based on its rotational symmetry. Its boundary is less likely to produce diffraction anomalies than the corner areas of the rectangular structure, which can ensure the consistency of the light field distribution and improve the detection accuracy to a certain extent based on the full-angle phase response.

[0075] According to the configuration method provided in this application, the first surface M1 is determined to have m areas.

[0076] In one embodiment, Figure 2 As shown in (a), the m regions are arranged along the first diameter L1 of the first surface M1 to form a strip shape.

[0077] When the first surface M1 is arranged so that the first diameter L1 extends in the vertical direction, m regions are arranged in the vertical direction and m regions can extend in the horizontal direction. When the first surface M1 is arranged so that the first diameter L1 extends in the horizontal direction, m regions are arranged in the horizontal direction and m regions can extend in the vertical direction.

[0078] The m regions of the strip can have the same or different lengths, the same or different widths, and the same or different areas.

[0079] The nanostructures in the microstructure units at the m regions have the same or different phase arrangements, directions (or rotation angles), materials, shapes, sizes and position coordinates.

[0080] In one embodiment, Figure 2 As shown in (b), the m regions are arranged from the center O1 of the first surface M1 along the first radius R1 of the first surface to form a concentric circle and m-1 concentric rings.

[0081] The first radius R1 can be a radius extending in any direction from the center of the circular first surface M1. The circle and annulus thus formed have the same center and are arranged radiating outward from the center. The area closest to the center of the m areas is the concentric circle, and the remaining areas outside the concentric circle are annular.

[0082] The m regions thus arranged can have the same or different sizes in the direction of the first radius R1. For the concentric circles, the size in the direction of the first radius R1 is the radius of the circle; for the concentric rings, the size in the direction of the first radius R1 is the width of the ring. The m regions thus arranged can have the same or different areas.

[0083] The nanostructures in the microstructure units at the m regions have the same or different phase arrangements, directions (or rotation angles), materials, shapes, sizes and position coordinates.

[0084] In one embodiment, Figure 2 As shown in (c), the m regions are arranged around the center O1 of the first surface M1 to form a fan shape.

[0085] The m sectors of the sector may have the same radius, the same or different central angles, or the same or different areas.

[0086] The nanostructures in the microstructure units at the m regions have the same or different phase arrangements, directions (or rotation angles), materials, shapes, sizes and position coordinates.

[0087] The microstructure units in the m regions can be used to process optical signals in different wavelength bands respectively, and produce corresponding different responses, thereby achieving efficient and wide-band spectral splitting.

[0088] In one embodiment, the m regions include a region dedicated to processing a natural light band; specifically, the microstructure units in this region are configured to only process light signals with a wavelength of 380 nm to 780 nm.

[0089] In one embodiment, the m regions include a region dedicated to processing near-infrared light band; specifically, the microstructure units in this region are configured to only process light signals with wavelengths of 780 nm to 2526 nm.

[0090] In one embodiment, the m regions include a region dedicated to processing an orange light band; specifically, the microstructure units in this region are configured to only process light signals with a wavelength of 590 nm to 610 nm.

[0091] In one embodiment, the m regions include a region dedicated to processing a blue light band; specifically, the microstructure units in this region are configured to only process light signals with a wavelength of 440 nm to 475 nm.

[0092] In one embodiment, the m regions include a region dedicated to processing a green light band; specifically, the microstructure units in this region are configured to only process light signals with a wavelength of 492 nm to 577 nm.

[0093] In one embodiment, the m regions include a region dedicated to processing the yellow light band; specifically, the microstructure units in this region are configured to only process light signals with a wavelength of 570 nm to 585 nm.

[0094] In one embodiment, the m regions include a region dedicated to processing a red light band; specifically, the microstructure units in this region are configured to only process light signals with a wavelength of 625 nm to 740 nm.

[0095] The above-mentioned band-dividing processing is a configuration of the microstructure units in the m regions. The light source actually used to illuminate the object under test and generate the incident light can be any visible light covering the required target band.

[0096] In one embodiment, m = 6. In other embodiments, m can be any integer greater than or equal to 1.

[0097] In one embodiment, the configuration of the m regions in the configured optical element 11 is related to the skin analysis task currently being performed by the skin analysis system 100. Specifically, a target diffraction characteristic is determined based on the skin analysis task, a corresponding target wavelength band is determined based on the target diffraction characteristic, and the number of regions is determined based on the number of target wavelength bands. In one embodiment, the number of target wavelength bands is equal to the number of regions on the first surface M1.

[0098] Display devices An embodiment of the present application provides a display device 1000, such as Figure 3 shown.

[0099] The display device 1000 comprises a skin analysis system. The skin analysis system can be the skin analysis system according to any of the technical solutions of the present application, and can be configured according to the configuration method of any of the technical solutions of the present application.

[0100] Specifically, the display device 1000 comprises an optical element 11. The optical element 11 comprises a first surface M1. The optical element 11 is configured to receive incident light from a subject and generate diffraction feature information.

[0101] The first surface M1 can be provided with a microstructure unit to form a metasurface.

[0102] Specifically, the display device 1000 comprises a processor 12. The processor 12 is configured to determine a skin physiological indicator of the subject according to the diffraction feature information.

[0103] At least the optical element 11 and the processor 12 are configured according to the configuration method of a skin analysis system provided by the present application. The configuration method can be the configuration method according to any of the technical solutions described later in the present application.

[0104] The optical element 11 and the first surface M1 thereof can be used to constitute a detection module of the display device 1000. The detection module can be arranged on the top of the display device 1000, and the skin detection and analysis of the subject can be realized without affecting the normal display of other parts.

[0105] In addition, the light sensor associated with the optical element 11 can also be included in the detection module. Based on the requirement of receiving incident light, the optical element 11 is at least partially exposed outside the shell of the display device 1000. In other words, at least part of the optical system of the skin analysis system is exposed outside the shell of the display device 1000.

[0106] The electrical system of the skin analysis system can be arranged inside the shell of the display device 1000. For example, the processor 12 is arranged inside the shell, and the user cannot directly observe the processor 12 from the appearance when using the display device 1000.

[0107] The processor 12 can be coupled to the detection module. In one embodiment, the processor 12 is coupled to the light sensor.

[0108] The display device 1000 comprises a display screen 101. The display screen 101 is configured to display a skin physiological indicator. The skin physiological indicator is generated by the skin analysis system.

[0109] When the skin physiological indicator is type information of skin abnormalities, the display screen 101 shows what kind of skin abnormalities exist in the current subject.

[0110] When the skin physiological index is evaluation information of skin abnormality, the display screen 101 shows the score or rating of the severity of the skin abnormality of the current subject.

[0111] When the skin physiological indicator is the overall health of the skin, the display screen 101 shows the score or rating of the current skin health of the subject.

[0112] The display device 1000 includes a reflector 102. The reflector 102 is used to present an image of the object under test when the display device 1000 is implemented.

[0113] When the display device 1000 includes a display screen 101 , the display screen 101 may also be made of a specular reflective material or covered with a cover plate made of a specular reflective material so as to have an integrated appearance with the reflector 102 .

[0114] In another embodiment, the display screen 101 and the reflector 102 may be formed as one body, which is equivalent to displaying skin physiological indicators on the reflector 102 .

[0115] In one embodiment, the display device 1000 includes the aforementioned light sensor, which is configured to generate a diffraction signature image. The display screen 101 or the reflector 102 can also be configured to output the diffraction signature image. Specifically, the display location of the diffraction signature image can correspond to the distribution area of ​​the measured object on the display screen 101 or the reflector 102, thereby achieving an augmented reality (AR) effect.

[0116] The display device 1000 may also have other additional functions. These additional functions may be achieved not only through further configuration of the electrical or optical systems, but also through further configuration of the display device itself. For example, based on the display device 1000 including the reflector 102, the display device 1000 may have the appearance of a cabinet and a cavity for placing items, thereby forming a smart mirror cabinet.

[0117] Configuration method of skin analysis system One embodiment of the present application provides a configuration method of a skin analysis system, such as Figure 4 shown.

[0118] Combine Figure 1 The skin analysis system 100 includes an optical element 11. The optical element 11 includes a first surface M1. The optical element 11 is configured to receive incident light from the object T1 and generate diffraction characteristic information.

[0119] The first surface M1 may be provided with microstructure units to form a super surface.

[0120] The optical element 11 can be configured based on any of the aforementioned technical solutions.

[0121] The measured object T1 may be a human face, a human body, or the face or limbs of another animal.

[0122] The diffraction characteristic information may be high-order skin characteristic information; the diffraction characteristic information may include high-order skin characteristic information.

[0123] The high-order skin feature may be a hyperspectral feature of the skin. The high-order skin feature information may be hyperspectral feature information of the skin.

[0124] Before executing the configuration method described below, the optical element 11 may determine the initial first surface M1 based on the initialization parameters, or determine the initial configuration of the first surface M1 and then perform fine adjustment through the configuration method described below.

[0125] The skin analysis system 100 includes a processor 12. The processor 12 is configured to determine the skin physiological index of the subject according to the diffraction characteristic information.

[0126] The skin physiological index may be information on the type of skin abnormality, information on the evaluation of skin abnormality, information on the overall health of the skin, or other quantitative indexes generated based on high-level skin characteristics.

[0127] When the processor 12 is working, it can determine the skin physiological indicators of the subject by implementing a convolutional neural network.

[0128] Before executing the configuration method described later, the processor 12 can determine the initial configuration of the processor 12 or determine the initial convolutional neural network based on the initialization parameters, and then perform fine-tuning through the configuration method described later.

[0129] The configuration of the first surface M1 (eg, the configuration of the microstructure units at the first surface M1 ) and the configuration information of the processor 12 may be uniformly fixed based on end-to-end training.

[0130] The processor 12 can be configured based on any of the aforementioned technical solutions.

[0131] Combine Figure 4 As shown, the configuration method of the skin analysis system includes at least one of the following steps.

[0132] Step S1: Obtain a skin analysis task and determine at least one corresponding target diffraction feature.

[0133] Step S2: determining m regions on the first surface according to the target diffraction characteristics.

[0134] The m regions are respectively used to modulate incident light of m target wavelength bands corresponding to the target diffraction characteristics.

[0135] m is an integer greater than or equal to 1.

[0136] Step S3: obtaining the detected physiological index and the preset calibration physiological index.

[0137] The detected physiological indicators are obtained based on the detection of a preset calibration object by the skin analysis system.

[0138] The calibration physiological index corresponds to the calibration object.

[0139] Step S4: determining the loss value based on the detected physiological index and the calibrated physiological index.

[0140] Step S5: Based on the loss value, the structural information of the optical element, the configuration information of the processor, or both the structural information of the optical element and the configuration information of the processor are updated to obtain a configured skin analysis system corresponding to the skin analysis task.

[0141] In this way, on the one hand, m areas corresponding to the target diffraction characteristics are determined for the corresponding skin analysis task, and each area processes the target band corresponding to the target diffraction characteristics, which enables the configured skin feature analysis system to perform hyperspectral skin feature analysis and achieve accurate analysis of skin features; and, since different areas process incident light of corresponding bands, the output of the optical element usually does not contain all the light signals required for complete imaging of the object under test, which not only achieves privacy protection from the output of the optical element, but also reduces the internal data transmission pressure of the skin analysis system and prevents error accumulation.

[0142] On the other hand, the configuration method constitutes an end-to-end training method, and the structural information of the optical element and the configuration information of the processor can be uniformly trained and determined, maintaining the integrity of the system, especially realizing the unification of the optical system and the electrical system; the loss value used to adjust the configuration is determined based on the output of the processor, which also reduces the amount of calculation and the complexity of the configuration process to a certain extent.

[0143] There is a corresponding relationship between skin analysis tasks and target diffraction features. For example: When the skin analysis task is to evaluate and manage acne-prone skin, the target diffraction features include epidermal inflammation features, acne scar features, and skin redness features. When the skin analysis task is to formulate anti-aging solutions for "early aging / mature skin", the target diffraction features include structural depression features (or wrinkle features) and microcirculation features; When the skin analysis task is to provide whitening and lightening care for "pigmentation / uneven skin tone", the target diffraction features include epidermal color spot features and pigment depth features.

[0144] Assuming that there are n target diffraction features, step S2 can specifically be: first determine the m target bands corresponding to the n target diffraction features, determine m areas corresponding to the m target bands on the first surface, and then configure the initial structural information at the m areas according to the m target bands.

[0145] Specifically, initial structural information of microstructure units in m regions is respectively configured according to m target bands.

[0146] The value of n is determined according to the number of target diffraction features corresponding to the skin analysis task, and the value of m is determined according to the number of target bands corresponding to the target diffraction features. m is also the number of areas divided on the first surface.

[0147] The values ​​of m and n can be equal, in which case the number of target diffraction features, target bands, and regions is equal. The values ​​of m and n can also be unequal, in which case a single target diffraction feature may correspond to multiple target bands, or multiple target diffraction features may correspond to a single target band.

[0148] Based on this, when executing steps S1 and S2, several target diffraction features corresponding to the skin analysis task are first determined. On the one hand, the target band corresponding to each target diffraction feature is determined. On the other hand, the first surface is divided into m areas, and the microstructure units in the m areas are configured to process the m target bands respectively, thereby realizing hyperspectral diffraction feature extraction.

[0149] When the skin analysis system includes multiple first surfaces for extracting target diffraction features, preferably, the multiple first surfaces are divided into the same area, and the corresponding areas on the multiple first surfaces process light signals in the same target wavelength band.

[0150] When constructing the correspondence between the target diffraction characteristics and multiple regions on the first surface, it can be specifically configured by configuring the microstructure units in the region so that the region only processes light signals with the corresponding target band; or it can be configured by making the microstructure units in the region have a higher transmittance for light signals in the target band.

[0151] The calibration object corresponds to the calibration physiological indicator. The calibration object or its information can be a preset, known subject or information about the subject, and the calibration physiological indicator is a known skin physiological indicator of the known subject. In step S3, the skin analysis system performs skin analysis on the calibration object information to obtain the detected physiological indicator as a measured quantity, which is then compared with the standard quantity, the calibration physiological indicator, in step S4.

[0152] The loss value can represent the difference between the detected physiological index and the calibrated physiological index, and can be determined by calculating the mean square error or other loss functions.

[0153] The goal of the configuration method is to bring the detected physiological indicators closer to the calibrated physiological indicators. Therefore, step S5 may include updating the optical element's structural information and / or the processor's configuration information until the loss value is less than a preset value or converges. The optical element's structural information and the processor's configuration information at that point in time are then fixed as the final structural information, and the processor's configuration information is fixed as the final configuration information, thereby finalizing the configured skin analysis system.

[0154] The structural information of the adjusted optical element may be structural information of m regions.

[0155] Microstructure units can be set at m areas. In this case, the structural information of the adjusted optical element can be at least one of the phase arrangement, direction (or rotation angle), material, shape, size and position coordinates of the nanostructures in the microstructure units at the m areas.

[0156] Taking phase arrangement as an example, after the skin analysis system determines the final phase arrangement information based on the loss value, since each of the m areas has a corresponding central wavelength, the shape, direction (or rotation angle) and size of the nanostructure of the microstructure unit in the area can be determined accordingly, and a phase map (Phase map) of the microstructure unit that can cover the 2π range at the current central wavelength is obtained. The final optical element is comprehensively determined in combination with the previously determined phase arrangement information.

[0157] When the skin analysis system includes multiple optical elements, the structural information may further include the combination of the optical elements, the spacing between the optical elements, etc.

[0158] The configuration information of the processor to be adjusted may be parameters, instructions, weights, etc. inside the processor.

[0159] The optical element may be configured to generate diffraction signature information comprising only high-order skin features.

[0160] The high-order skin features may be hyperspectral features of the skin.

[0161] The high-order skin feature may be a type of the target diffraction feature. The target diffraction feature may include a high-order skin feature.

[0162] In one embodiment, the optical element configured based on the initial structural information is configured to generate diffraction signature information that includes only high-order skin features. In one embodiment, the optical element in the configured skin analysis system is configured to generate diffraction signature information that includes only high-order skin features. In one embodiment, the optical element in the skin analysis system always generates diffraction signature information that includes only high-order skin features.

[0163] This configuration allows the skin analysis system to extract only high-level skin features without generating images, protecting private information such as faces. Imaging refers to the process of obtaining complete information about the subject and generating a display showing the subject's complete details. The optical element provided in this application modulates the output of only the diffraction signature information of the subject in the corresponding wavelength band. Even if a diffraction signature image is subsequently generated based on this diffraction signature information, it does not include the complete details of the subject, thus distinguishing it from the imaging process used in prior art.

[0164] On the other hand, the m regions correspond to the feature extraction process under different bands, and the skin physiological indicators are comprehensively determined based on the high-order skin features of multiple bands, which is equivalent to making a comprehensive judgment based on richer skin status information, and can obtain more accurate analysis results.

[0165] In one embodiment, the configuration method further includes: determining m target bands corresponding to the target diffraction characteristics; and configuring the structures of the m regions to modulate only the incident light of the corresponding target bands.

[0166] In one embodiment, before performing end-to-end training configuration, the optical element is configured so that different regions process optical signals of different wavelength bands respectively.

[0167] In one embodiment, after the end-to-end training configuration, different regions in the determined optical element process optical signals of different wavelength bands respectively.

[0168] The two embodiments can be combined. In other embodiments, the optical element can also be always configured so that different areas thereon process optical signals of different wavelength bands respectively.

[0169] In one embodiment, the target wavelength band includes a wavelength band from 380 nm to 780 nm.

[0170] In one embodiment, the target wavelength band includes a natural light wavelength band.

[0171] For example, if the target bands corresponding to the target diffraction features include the natural light band, at least one area on the first surface can be configured to only modulate the incident light in the natural light band to accurately obtain the target diffraction features corresponding to the natural light band.

[0172] In one embodiment, the target wavelength band includes a wavelength band from 780 nm to 2526 nm.

[0173] In one embodiment, the target wavelength band includes a near-infrared light band.

[0174] For example, if several target bands corresponding to several target diffraction features include a near-infrared light band, at least one area on the first surface can be configured to only modulate the incident light in the near-infrared light band to accurately obtain the target diffraction features corresponding to the near-infrared light band.

[0175] In one embodiment, the target wavelength band includes a wavelength band from 590 nm to 610 nm.

[0176] In one embodiment, the target wavelength band includes an orange light wavelength band.

[0177] For example, if the target bands corresponding to the target diffraction features include an orange light band, at least one area on the first surface can be configured to only modulate the incident light in the orange light band to accurately obtain the target diffraction features corresponding to the orange light band.

[0178] In one embodiment, the target wavelength band includes a wavelength band from 440 nm to 475 nm.

[0179] In one embodiment, the target wavelength band includes a blue light wavelength band.

[0180] For example, if the target wavelengths corresponding to the target diffraction features include a blue light wavelength, at least one area on the first surface can be configured to modulate only the incident light in the blue light wavelength to accurately obtain the target diffraction features corresponding to the blue light wavelength.

[0181] In one embodiment, the target wavelength band includes a wavelength band from 492 nm to 577 nm.

[0182] In one embodiment, the target wavelength band includes a green light wavelength band.

[0183] For example, if the target wavelengths corresponding to the target diffraction features include a green light wavelength, at least one area on the first surface can be configured to modulate only the incident light in the green light wavelength to accurately obtain the target diffraction features corresponding to the green light wavelength.

[0184] In one embodiment, the target wavelength band includes a wavelength band from 570 nm to 585 nm.

[0185] In one embodiment, the target wavelength band includes a yellow light wavelength band.

[0186] For example, if the target wavelengths corresponding to the target diffraction features include a yellow light wavelength, at least one area on the first surface can be configured to modulate only the incident light in the yellow light wavelength to accurately obtain the target diffraction features corresponding to the yellow light wavelength.

[0187] In one embodiment, the target wavelength band includes a wavelength band from 625 nm to 740 nm.

[0188] In one embodiment, the target wavelength band includes a red light wavelength band.

[0189] For example, if the target diffraction features corresponding to the target wavebands include a red light waveband, the first surface can be configured to modulate only the incident light in the red light waveband to accurately obtain the target diffraction features corresponding to the red light waveband.

[0190] In an embodiment, the obvious spot feature corresponds to a natural light waveband. In an embodiment, the pigment deposition feature corresponds to a natural light waveband. In an embodiment, the skin texture feature corresponds to a natural light waveband. In an embodiment, the flatness feature corresponds to a natural light waveband.

[0191] For example, if at least one of the target diffraction features corresponding to the skin analysis task includes one of the obvious spot feature, the pigment deposition feature, the skin texture feature, and the flatness feature, the natural light waveband is determined as one of the target wavebands, and the structure at the first surface is configured to modulate only the incident light in the natural light waveband. The natural light waveband can be a 380 nm to 780 nm waveband.

[0192] In an embodiment, the high-density color spot feature corresponds to an orange light waveband.

[0193] For example, if the target diffraction features corresponding to the skin analysis task include the high-density color spot feature, the orange light waveband is determined as one of the target wavebands, and the structure at the first surface is configured to modulate only the incident light in the orange light waveband. The orange light waveband can be a 590 nm to 610 nm waveband.

[0194] The high-density color spot includes chloasma, freckle, nevus spilus, etc.

[0195] In an embodiment, the hemoglobin feature corresponds to a near-infrared light waveband.

[0196] For example, if the target diffraction features corresponding to the skin analysis task include the hemoglobin feature, the near-infrared light waveband is determined as one of the target wavebands, and the structure at the first surface is configured to modulate only the incident light in the near-infrared light waveband. The near-infrared light waveband can be a 780 nm to 2526 nm waveband.

[0197] The hemoglobin feature corresponds to capillary dilation, sensitive skin area, etc.

[0198] In an embodiment, the acne feature corresponds to a blue light waveband. In an embodiment, the epidermal inflammation feature corresponds to a blue light waveband.

[0199] For example, if at least one target diffraction feature corresponding to a skin analysis task includes at least one of an acne feature and an epidermal inflammation feature, a blue light band is determined as one of the target bands, and the structure on the first surface is configured to modulate only incident light in the blue light band. The blue light band may be 440nm to 475nm.

[0200] Blue light can also correspond to other inflammatory conditions.

[0201] In one embodiment, the characteristic of epidermal spots corresponds to the green light band. In one embodiment, the characteristic of acne scars corresponds to the green light band. In one embodiment, the characteristic of skin redness corresponds to the green light band. In one embodiment, the characteristic of vascular dilation corresponds to the green light band.

[0202] For example, if the at least one target diffraction feature corresponding to the skin analysis task includes at least one of epidermal spot characteristics, acne scar characteristics, skin redness characteristics, and vascular dilation characteristics, the green light band is determined as one of the target bands, and the structure on the first surface is configured to modulate only incident light in the green light band. The green light band can be the 492nm to 577nm band.

[0203] In one embodiment, the sensitive state characteristic corresponds to the yellow light band. In one embodiment, the microcirculation characteristic corresponds to the yellow light band.

[0204] For example, if the at least one target diffraction feature corresponding to the skin analysis task includes at least one of a sensitivity state feature and a microcirculation feature, the yellow light band is determined as one of the target bands, and the structure on the first surface is configured to modulate only incident light in the yellow light band. The yellow light band can be 570nm to 585nm.

[0205] Microcirculation characteristics may also specifically include fine line characteristics, skin sagging characteristics, etc.

[0206] In one embodiment, the collagen feature corresponds to the red light band. In one embodiment, the deep inflammation feature corresponds to the red light band. In one embodiment, the structural depression feature corresponds to the red light band. In one embodiment, the pigment depth feature corresponds to the red light band.

[0207] For example, if the at least one target diffraction feature corresponding to the skin analysis task includes at least one of a collagen feature, a deep inflammation feature, a structural depression feature, and a pigment depth feature, the red light band is determined as one of the target bands, and the structure on the first surface is configured to modulate only incident light in the red light band. The red light band can be the 625nm to 740nm band.

[0208] In one embodiment, the first surface is provided with microstructure units to form a super surface.

[0209] In one embodiment, the configuration method of the present application includes the step of updating the phase arrangement of the microstructure units in m regions on the first surface of the optical element based on the loss value.

[0210] This step may be included in step S5, and in particular, may be included in the step of "updating the structural information of the optical element based on the loss value".

[0211] After determining the phase arrangement, the shape, rotation angle and size of the nanostructure can be adjusted in combination with the central wavelength of the region. After determining the phase map of the region, the structural information of the optical element can be determined by combining the phase map and the phase arrangement.

[0212] The phase arrangement includes at least one of an arrangement of nanostructures within a microstructure unit and an arrangement of microstructure units on a metasurface.

[0213] In one embodiment, the configuration method of the present application includes the step of updating the materials of the microstructure units in m regions on the first surface of the optical element based on the loss value.

[0214] This step may be included in step S5, and in particular, may be included in the step of "updating the structural information of the optical element based on the loss value".

[0215] Compared to the phase arrangement of the microstructure units, the configuration of the materials of the microstructure units or the materials of the nanostructures can be used to improve the information diversity of feature extraction. Specifically, the microstructure units in different regions can be configured to be prepared based on different materials. In one embodiment, the microstructure units and nanostructures in one of the m regions can be configured to be prepared from TiO2, which can be used to extract visible light-related features, such as the extraction of obvious spot features, pigmentation features, skin texture features, and flatness features. In one embodiment, the microstructure units and nanostructures in one of the m regions can be configured to be prepared from amorphous silicon, which can be used to extract near-infrared light-related features, such as the extraction of hemoglobin features.

[0216] Combine Figure 1 As shown, the skin analysis system 100 may further include a light sensor 13. The light sensor 13 may be disposed on the light-emitting side of the optical element 11. The light sensor 13 may be configured to receive diffraction characteristic information and generate a diffraction characteristic image.

[0217] The optical sensor 13 obtains diffraction characteristic information from the optical element 11 , and the formed diffraction characteristic image does not include other features except the diffraction feature, thereby achieving privacy protection.

[0218] The processor 12 may be configured to determine skin physiological indicators of the subject T1 according to the diffraction characteristic image.

[0219] The optical sensor 13 can be configured based on any of the aforementioned technical solutions.

[0220] In one embodiment, the optical element may be configured to modulate incident light to generate diffraction feature information for forming a blurred image of the object under test.

[0221] In this embodiment, the diffraction characteristic information output by the optical element is used to generate a blurred image. Blur refers to the state of the object under test in the image after being blurred.

[0222] The blurred image may be the diffraction characteristic image. The object under test appears blurred in the diffraction characteristic image. The optical sensor generates a diffraction characteristic image with a blurred encryption effect based on the diffraction characteristic information.

[0223] In one case, the blurring can be the result of generating a diffraction signature image based on the diffraction signature information. In other words, because the diffraction signature information corresponds to a target wavelength, the various diffraction signature information corresponding to multiple target wavelengths does not produce detailed images of the subject, but rather a distributional mapping relationship exists. Therefore, the generated diffraction signature image presents a blurred image of the subject, but this does not affect the privacy protection characteristics of the skin analysis system.

[0224] In another embodiment, the blurring can be configured on the first surface. In one feasible embodiment, the microstructure units in all areas of the first surface can be configured to have a blurred and encrypted structural configuration, thereby producing a blurred image with a better encryption effect. In another feasible embodiment, a separate area on the first surface can be configured for blurred imaging, ensuring the privacy of the subject while making the diffraction characteristic image more referenceable.

[0225] When the loss value converges or is less than a preset value, the diffraction feature image can be actually output to present the target diffraction feature and / or the distribution of the target diffraction feature.

[0226] In one embodiment, the optical element configured based on the initial structural information is configured to generate diffraction signature information for forming a blurred image of the object under test. In one embodiment, the optical element in the configured skin analysis system is configured to generate diffraction signature information for forming a blurred image of the object under test.

[0227] In one embodiment, the optical element may be configured to modulate incident light to generate diffraction feature information of an image containing high-order skin features of the subject's face.

[0228] The image including the high-order skin features of the face of the subject may be the diffraction feature image. The light sensor generates the diffraction feature image including the high-order skin features of the face based on the diffraction feature information.

[0229] Specifically, different areas of the optical element correspond to different bands, and the diffraction characteristic image generated based on the diffraction characteristic information under multiple bands has high spectral characteristics, so it can present high-order skin features of the face.

[0230] In one embodiment, the processor may be configured to determine the skin physiological indicators of the subject by implementing a convolutional neural network.

[0231] Based on this, the configuration information of the processor may include model parameters and weights of the convolutional neural network, etc. The model parameters and weights of the convolutional neural network participate in the configuration method and are finally determined together with the structural information of the optical element.

[0232] In one embodiment, the processor may be configured to determine the health of the skin based on the diffraction characteristic information and a preset database.

[0233] In one scenario, the skin health level may be the skin physiological index, or the skin health level may be included in the skin physiological index. In this case, the determined diffraction feature information may be matched in the database to determine the skin health level indicated by the diffraction feature information, and this may be determined as the output skin physiological index.

[0234] In another case, the skin health level is determined based on skin physiological indicators and used as one of the outputs of the processor. In this case, the skin health level indicated by the skin physiological indicators can be determined and output based on the determined skin physiological indicators.

[0235] In one embodiment, in order to further enhance confidentiality, the display device or skin analysis system does not exchange data with the Internet. In this case, the display device or skin analysis system further includes a memory for constructing the database as a local database.

[0236] In one embodiment, after determining the diffraction feature information, skin physiological indicators or skin health level, skin care suggestions (for example, including "hydration recommendation for dehydrated skin") or a health report (for example, including "UV damage detected") can be given based on the comparison results of the database.

[0237] In one scenario, the skin analysis task is to assess and manage acne-prone skin. Target diffraction features can be determined, including epidermal inflammation, acne scarring, and skin redness. These features are determined to correspond to blue and green light bands, respectively. Furthermore, the first surface can be divided into at least two regions (preferably, m regions, where m is a multiple of 2). Microstructure elements in different regions are used to modulate the blue and green light bands in the incident light, respectively, and generate diffraction signature information. Based on the diffraction signature information or the resulting diffraction signature image, the processor implements a convolutional neural network to determine skin physiological indicators representing inflammation, acne scarring, or redness.

[0238] When blue light shines on the skin's surface, its shorter wavelength clearly highlights imperfections in the epidermis. More importantly, inflamed, active acne typically appears red or purple. Under blue light, the color of these inflamed areas creates a stronger contrast with the surrounding healthy skin, allowing them to be clearly identified. This can help assess the current level of inflammation and activity of acne.

[0239] Green light is particularly effective at detecting red and brown features. Red acne scars (post-inflammatory erythema) are essentially caused by dilated capillaries, and green light is strongly absorbed by hemoglobin, allowing for a very precise delineation of their extent and severity. Brown acne scars (post-inflammatory hyperpigmentation) are essentially caused by melanin deposition, and green light is also sensitive to melanin, allowing for clear identification of these areas. Green light also provides excellent assessment of full-face redness and the skin sensitivity and redness associated with acne.

[0240] In one scenario, the skin analysis task involves developing anti-aging strategies for both early-stage and mature skin. Target diffraction features can be determined, including structural depressions (also known as wrinkle features) and microcirculatory features. These features are determined to correspond to red and yellow light bands, respectively. Furthermore, a first surface can be divided into at least two regions (preferably, m regions, where m is a multiple of 2). Microstructure elements in different regions are used to modulate the red and yellow light bands of incident light, respectively, and generate diffraction feature information. Based on the diffraction feature information or the resulting diffraction feature image, the processor implements a convolutional neural network to determine skin physiological indicators representing wrinkle conditions, skin texture, or microcirculatory conditions.

[0241] Red light can penetrate the dermis, where its reflection indirectly reflects skin firmness and elasticity. Skin with abundant collagen and a firm structure reflects red light more evenly and brightly. Conversely, areas of sagging and structural depressions (i.e., wrinkles) appear as distinct shadows and dark areas in red light images. By analyzing the distribution and depth of these shadows, deeper wrinkles and overall skin plumpness can be effectively assessed.

[0242] Yellow light has a penetration depth between green and red light, reaching the superficial dermis. Its primary function is to assess skin texture and microcirculation. Regarding skin texture, yellow light effectively highlights the skin's surface texture and is particularly effective in identifying rough and fine lines caused by dryness or aging. Regarding microcirculation and skin tone, yellow light stimulates blood and lymphatic circulation. By observing the skin's reaction and color under yellow light (for example, whether it improves dullness), one can indirectly assess the health of the skin's microcirculation and overall complexion. This provides valuable guidance for improving the dull complexion commonly seen in mature skin.

[0243] In one scenario, the skin analysis task is to provide whitening and freckle reduction treatment for "pigmentation / uneven skin tone." Based on this, target diffraction features can be determined, including epidermal pigmentation features and pigment depth features. These features are determined to correspond to green and red light bands, respectively. Furthermore, a first surface can be divided into at least two regions (preferably, m regions, where m is a multiple of 2). Microstructure elements in different regions are used to modulate the green and red light bands of incident light, respectively, and generate diffraction feature information. Based on the diffraction feature information or the resulting diffraction feature image, the processor implements a convolutional neural network to determine a skin physiological indicator that quantifies the surface pigmentation or uneven skin tone.

[0244] Green light has a high absorption rate for melanin, making it ideal for identifying superficial pigmentation (such as sun spots, freckles, age spots, and brown acne scars). Under green light, these pigmented areas appear very dark, creating a strong contrast with the surrounding skin, facilitating precise location and area calculation. It also clearly reveals uneven skin tone across the face.

[0245] Red light can provide some clues about pigmentation intensity. Because red light penetrates deeper, if a spot is very visible under green light (indicating a high concentration of melanin in the surface layer) but less noticeable under red light (because red light "passes" through the surface and is more reflected by deeper tissue), then the spot is likely primarily located in the epidermis. Conversely, if a spot is still clearly visible under red light, it may indicate a darker pigmentation or a structural shadow. This contrast can provide a reference for judging the persistence of the spot.

[0246] Figure 5 (a) shows a subject to be tested when the skin analysis system provided by the present application is in operation (the portion of the face in the figure is blurred, but when the technical solution of the present application is implemented, the subject to be tested has a relatively clear face, and the image of the subject to be tested through mirror reflection can be presented as a relatively clear face). Figure 5 Panel (b) shows the diffraction signature image and related data generated by the skin analysis system provided by this application for the subject. This data can be used as a skin physiological indicator. As can be seen, the diffraction signature image cannot distinguish the subject's facial features and details, but the subject's high-level skin features are clearly presented in the diffraction signature image. This allows for refined skin analysis while protecting privacy.

[0247] In summary, the configuration method of the skin analysis system provided in this application is such that the configured skin analysis system determines skin physiological indicators through diffraction characteristic information corresponding to multiple bands, and can detect the physiological condition of the skin in multiple dimensions; the skin analysis system performs analysis based on the diffraction characteristic information, so that skin analysis is not limited to clear imaging of the subject, thereby effectively protecting the user's privacy; the skin analysis system is configured and trained in an end-to-end manner, so that the optical system including optical elements and the electrical system including the processor can be configured and fixed as a whole, which can improve the accuracy and credibility of the output results and prevent error accumulation.

[0248] It should be understood that although this specification is described in terms of implementation methods, not every implementation method contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each implementation method can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

[0249] The series of detailed descriptions listed above are only specific descriptions of feasible implementation methods of this application. They are not intended to limit the scope of protection of this application. Any equivalent implementation methods or changes that do not deviate from the technical spirit of this application should be included in the scope of protection of this application.

Claims

1. A configuration method for a skin analysis system, characterized in that: The skin analysis system comprises: The optical element comprises a first surface for receiving incident light from the object to be measured, modulating and generating diffraction characteristic information, a processor, configured to determine a skin physiological index of a subject according to the diffraction characteristic information; The configuration method includes: Obtain a skin analysis task and determine at least one corresponding target diffraction feature, m regions are determined on the first surface according to the target diffraction characteristics, and the m regions are respectively used to modulate incident light of m target wavelength bands corresponding to the target diffraction characteristics, where m is an integer greater than or equal to 1. Obtaining a detection physiological index and a preset calibration physiological index, wherein the detection physiological index is obtained based on detection of a preset calibration object by a skin analysis system, and the calibration physiological index corresponds to the calibration object, Determine the loss value based on the detected physiological index and the calibrated physiological index, Based on the loss value, the structural information of the optical element, the configuration information of the processor, or both the structural information of the optical element and the configuration information of the processor are updated to obtain a configured skin analysis system corresponding to the skin analysis task.

2. The configuration method according to claim 1, characterized in that: The optical element is configured to generate diffraction signature information comprising only high-order skin features.

3. The configuration method according to claim 1, wherein: include: Determine the m target bands corresponding to the target diffraction characteristics, The structure of the m regions is configured to modulate only the incident light in the corresponding target wavelength band.

4. The configuration method according to claim 3, characterized in that: The target band includes at least one of the following: Wavelengths from 380nm to 780nm or other natural light bands, Wavelengths from 780nm to 2526nm or other near-infrared light bands, The wavelength band is 590nm to 610nm or other orange light bands, The wavelength band is 440nm to 475nm or other blue light bands, The wavelength band is 492nm to 577nm or other green light bands, The wavelength is 570nm to 585nm or other yellow light bands, The wavelength band is from 625nm to 740nm or other red light bands.

5. The configuration method according to claim 3, characterized in that: Include at least one of the following: The obvious spot characteristics, pigmentation characteristics, skin texture characteristics and smoothness characteristics correspond to the natural light bands. The high-density color spot feature corresponds to the orange light band. Hemoglobin characteristics correspond to the near-infrared light band. Acne characteristics and epidermal inflammation characteristics correspond to the blue light band. Epidermal pigmentation, acne scars, skin redness, and vascular dilation correspond to the green light band. Sensitive state characteristics and microcirculation characteristics correspond to the yellow light band. Collagen characteristics, deep inflammation characteristics, structural depression characteristics, and pigment depth characteristics correspond to the red light band.

6. The configuration method according to claim 1, characterized in that: The first surface is provided with microstructure units to form a super surface, The configuration method includes at least one of the following: Based on the loss value, updating the phase arrangement of the microstructure units in m regions on the first surface of the optical element, Based on the loss value, the materials of the microstructure units in the m regions at the first surface of the optical element are updated.

7. The configuration method according to claim 1, characterized in that: The skin analysis system includes: A light sensor is provided on the light-emitting side of the optical element, and is used to receive diffraction characteristic information and generate a diffraction characteristic image. The processor is used to determine the skin physiological index of the tested object according to the diffraction characteristic image.

8. The configuration method according to claim 1, characterized in that: The optical element is configured according to at least one of the following: The optical element modulates the incident light to generate diffraction characteristic information for forming a blurred image of the object under test. The optical element modulates the incident light to generate diffraction feature information of an image containing high-order skin features of the subject's face.

9. The configuration method according to claim 1, characterized in that: The processor is configured according to at least one of the following: The processor determines the skin physiological indexes of the subject by implementing a convolutional neural network. The processor is used to determine the health of the skin based on the diffraction characteristic information and a preset database.

10. A skin analysis system, characterized in that: include: The optical element comprises a first surface for receiving incident light from the object to be measured and generating diffraction characteristic information. A processor is used to determine the skin physiological index of the subject according to the diffraction characteristic information, The skin analysis system is configured according to the configuration method according to any one of claims 1-9.

11. The skin analysis system according to claim 10, characterized in that The first surface is provided with microstructure units to form a super surface, The first surface is circular, and the first surface is configured according to one of the following: The m regions are arranged along the first diameter of the first surface to form a strip shape, The m regions are arranged from the center of the first surface along the first radius of the first surface to form a concentric circle and m-1 concentric rings, The m regions are arranged around the center of the first surface to form a fan shape.

12. A display device, characterized in that: include: The skin analysis system according to claim 10 or 11, A display screen is used to display the skin physiological indicators.

13. The display device according to claim 12, wherein: The display device comprises: The reflector is used to present an image of the object under test when the display device is implemented.

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