Skin condition detection methods, devices, equipment, smart mirrors, and storage media

Abstract

This application provides a skin condition detection method, apparatus, device, smart mirror, and storage medium. The skin condition detection method acquires an infrared image of the area to be detected, analyzes the infrared image, determines the skin condition of each region of the area to be detected based on the mapping relationship between skin temperature and skin condition, and then performs visualization processing based on the skin condition of each region and the image of the area to be detected to obtain visualized display data of the skin condition. The skin condition detection method can detect specific problems existing in the skin and can analyze the skin condition independently based on the infrared image without relying on professionals. The detection is convenient, simple, and the detection results are more intuitive.

Description

Technical Field

[0001] This application relates to the field of skin detection technology, and in particular to a skin condition detection method, device, equipment, smart mirror, and storage medium. Background Technology

[0002] As living standards improve, people are paying more and more attention to their skin condition. Their understanding of skin is no longer limited to problems visible to the naked eye. People want to see deeper skin problems more intuitively and clearly, such as the risk of acne and spots that are not visible under natural light. Therefore, multispectral skin testing instruments like VISIA have emerged to help people see potential skin problems that are not visible under natural light.

[0003] Currently, the mainstream approach to skin testing is to use multispectral irradiation on the face. However, these methods can only detect the presence of skin problems, but not the specific problems. Furthermore, the instruments require professional operation, and users need to go to specialized institutions for testing, which is a high barrier to entry and inconvenient for daily use. Summary of the Invention

[0004] To address the existing technical problems, this application provides a simple and easy-to-use skin condition detection method, device, equipment, smart mirror, and storage medium.

[0005] A skin condition detection method, applied to a skin condition detection device, comprising:

[0006] Acquire infrared images of the area to be detected;

[0007] The infrared image is analyzed, and the skin condition of each area of ​​the area to be detected is determined based on the mapping relationship between skin temperature and skin condition.

[0008] Based on the skin condition of each region and the image of the area to be detected, visualization processing is performed to obtain the skin condition visualization display data.

[0009] A skin condition detection device, comprising:

[0010] Infrared image acquisition module, used to acquire infrared images of the area to be detected;

[0011] The skin condition analysis module is used to analyze the infrared image and determine the skin condition of each area of ​​the area to be detected based on the mapping relationship between skin temperature and skin condition.

[0012] The visualization processing module is used to perform visualization processing based on the skin condition of each region and the image of the area to be detected, so as to obtain the visualization display data of the skin condition.

[0013] A skin condition detection device, comprising:

[0014] When the processor executes the computer program instructions stored in the memory, it performs the steps of the skin condition detection method.

[0015] A smart mirror, comprising:

[0016] The aforementioned skin condition detection device;

[0017] An infrared image module is used to acquire infrared images of the area to be detected and send them to the skin condition detection device;

[0018] A mirror display module is used to display visual data of the skin condition.

[0019] A computer-readable storage medium storing computer program instructions;

[0020] The steps of the skin condition detection method are as follows when the computer program instructions are executed by the processor.

[0021] As can be seen from the above, the skin condition detection method, apparatus, device, smart mirror, and storage medium provided in this application acquire infrared images of the area to be detected, analyze the infrared images, determine the skin condition of each region of the area to be detected based on the mapping relationship between skin temperature and skin condition, and then perform visualization processing based on the skin condition of each region and the image of the area to be detected to obtain visualized display data of the skin condition. The skin condition detection method can detect specific skin problems and can analyze the skin condition independently based on the infrared images, without relying on professionals. The detection is convenient, simple, and the results are more intuitive. Attached Figure Description

[0022] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0023] Figure 1 This is a schematic flowchart of the skin condition detection method according to Embodiment 1 of this application;

[0024] Figure 2 This is a schematic diagram of the detection results obtained according to the skin condition detection method in Embodiment 1 of this application;

[0025] Figure 3 This is a schematic flowchart of the skin condition detection method according to Embodiment 2 of this application;

[0026] Figure 4This is a schematic flowchart of the skin condition detection method according to Embodiment 3 of this application;

[0027] Figure 5 This is a schematic flowchart of the skin condition detection method according to Embodiment 4 of this application;

[0028] Figure 6 This is a schematic diagram illustrating the process of constructing a skin temperature and skin state mapping model in the skin state detection method according to Embodiment 5 of this application;

[0029] Figure 7 This is a schematic diagram illustrating the construction process of the skin temperature and skin state mapping model in the skin state detection method according to Embodiment Six of this application;

[0030] Figure 8 This is a schematic flowchart of the skin condition detection method according to Embodiment 7 of this application;

[0031] Figure 9 This is a schematic flowchart of the skin condition detection method according to Embodiment 8 of this application;

[0032] Figure 10 This is a schematic diagram of the detection results obtained according to the skin condition detection method of Embodiment 8 of this application;

[0033] Figure 11 This is a schematic diagram of the skin condition detection device according to Embodiment 9 of this application;

[0034] Figure 12 This is a schematic diagram of the skin condition detection device according to Embodiment 10 of this application;

[0035] Figure 13 This is a schematic diagram of the skin condition detection device according to Embodiment Eleven of this application;

[0036] Figure 14 This is a schematic diagram of the structure of the smart mirror according to Embodiment Twelve of this application. Detailed Implementation

[0037] The technical solution of this application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0038] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the specification of this application is for the purpose of describing particular embodiments only and is not intended to limit the ways in which this application may be implemented. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0039] In the following description, the expression “some embodiments” is used, which describes a subset of possible embodiments. However, it should be understood that “some embodiments” can be the same subset or different subsets of all possible embodiments and can be combined with each other without conflict.

[0040] To address the problems existing in the prior art, this application provides a skin condition detection method applied to a skin condition detection device. The method involves acquiring an infrared image of the area to be detected using the skin condition detection device, analyzing the infrared image, determining the skin condition of the area based on the skin temperature of the area contained in the infrared image and the mapping relationship between skin temperature and skin condition, and then performing visualization processing based on the skin condition and the skin image of the area to be detected to finally obtain visualized display data of the skin condition. This skin condition detection method can view the skin's metabolism and existing skin problems, such as oily areas, pigmentation, and inflamed wounds, through the imaging image of the area to be detected. All of this can be achieved by the skin condition detection device without human assistance, allowing users to complete the skin detection themselves. Furthermore, this application also provides a skin condition detection device, equipment, smart mirror, and storage medium corresponding to the skin condition detection method. The following will describe embodiments one to twelve provided in this application, along with their corresponding embodiments. Figures 1 to 14 This application provides a detailed description of the skin condition detection method, device, equipment, smart mirror, and storage medium.

[0041] Please see Figure 1 The above is a flowchart illustrating the skin condition detection method according to Embodiment 1 of this application. In the embodiment, the skin condition detection method includes S02, S04 and S06.

[0042] S02: Acquire an infrared image of the area to be detected.

[0043] S02 can be derived from Figure 11 The infrared image acquisition module 101 in the skin condition detection device shown is used to implement this, or it is implemented by... Figure 12 The memory 202 in the skin condition detection device shown stores the corresponding infrared image acquisition program, which is then processed by... Figure 12 The processor 201 in the skin condition detection device shown is implemented when executing the infrared image acquisition program stored in the memory 202.

[0044] In this application, the area to be detected is a body part of a person or animal, such as the face, torso, or other parts. The skin of the area to be detected refers to the tissue covering the surface of the body part.

[0045] Infrared images, short for thermal infrared images, also known as thermal images, are images generated by an infrared imaging module (such as a thermal infrared scanner) receiving thermal radiation from the area being detected. Therefore, infrared images contain skin temperature information of the area being detected, reflecting the skin temperature distribution of that area.

[0046] The infrared image can be acquired by an infrared image module integrated inside the skin condition detection device, or by an infrared image module located outside the skin condition detection device, and then the infrared image is sent to the skin condition detection device. The infrared image module further includes an infrared acquisition module and an infrared imaging module. In Embodiment 1, the area to be detected is taken as a human face. The infrared acquisition module is used to acquire infrared facial image information. The infrared facial image information includes raw infrared data, which is an infrared electrical signal obtained by the infrared acquisition module receiving infrared radiation reflected from the human face and processing the received infrared radiation. The infrared electrical signal contains skin temperature information and facial image information. The infrared imaging module is used to perform imaging processing on the raw infrared data to obtain the infrared image. Imaging processing of the raw infrared data can include, but is not limited to, generating infrared images with significant color differences through image processing techniques such as temperature width stretching and pseudo-color mapping. In the infrared image, different temperatures are represented by different colors. Therefore, the temperature distribution of the infrared image can be obtained based on its color distribution, and each color distribution area of ​​the infrared image corresponds to the skin temperature distribution area of ​​the area to be detected.

[0047] S04: Analyze the infrared image and determine the skin condition of each area of ​​the area to be detected based on the mapping relationship between skin temperature and skin condition.

[0048] S04 can be derived from Figure 11 The skin condition analysis module 102 in the skin condition detection device shown is used to implement this, or it is implemented by... Figure 12 The memory 202 in the skin condition detection device shown stores the corresponding skin condition analysis program, which is then processed by... Figure 12 The processor 201 in the skin condition detection device shown is implemented when executing the skin condition analysis program stored in the memory 202.

[0049] The inventors of this application, during their research, believed that there is a direct and necessary correlation between skin metabolism and skin temperature. The infrared image of the area to be detected is actually a skin temperature distribution image of that area, containing skin temperature information. Therefore, the infrared image can be analyzed to determine the image itself and the skin temperature information it contains. Based on the necessary correlation between skin temperature and skin condition, the skin condition of the area to be detected can be determined. In Embodiment 1, the analysis of the infrared image is implemented using a data analysis module in the skin condition detection device, which includes a skin condition analysis module. In other embodiments, the data analysis module is also used to analyze the infrared image to obtain other detection results corresponding to the area to be detected. If the skin condition corresponding to a certain area of ​​the area to be detected is an abnormal skin condition, a corresponding skincare plan is determined based on the abnormal skin condition of the area to be detected. The corresponding skincare plan can be used as one of the detection results.

[0050] Skin temperature is a visual reflection of the skin's dermal condition. It can indicate the skin's metabolic rate and thus its overall health. For example, oily areas are prone to acne and enlarged pores, both indicative of skin condition. This establishes a mapping between skin temperature and skin problems. Infrared imaging visualizes skin temperature, and this mapping is then established with skin condition data, allowing for assessment of the skin's overall health. Skin condition can include aspects such as skin metabolism, oily areas, and pigmentation. The mapping between skin temperature and skin condition can be represented by a mapping table or a skin temperature-skin condition mapping model.

[0051] S06: Visualize the skin condition of each region and the image of the area to be detected to obtain visualized data of the skin condition.

[0052] S06 can be made by Figure 11 The visualization processing module 103 in the skin condition detection device shown implements this, or is implemented by... Figure 12 The memory 202 in the skin condition detection device shown stores the corresponding visualization processing program, which is then processed by... Figure 12 The processor 201 in the skin condition detection device shown is implemented when executing the visualization processing program stored in the memory 202.

[0053] The visualization processing based on the skin condition of each region and the image of the area to be detected includes visualizing the skin condition of each region to obtain corresponding display data. Based on this display data, the user can intuitively understand the skin condition information of the area to be detected. It also includes visualizing the image of the area to be detected based on the skin condition of each region to obtain image display data that intuitively displays the distribution of skin conditions (such as the distribution of abnormal skin conditions). Therefore, the skin condition detection device also includes a visualization processing module. This module is used to visualize the analysis results obtained by the data analysis module to obtain display data for the user to intuitively observe the skin condition detection results. In some embodiments, the display data includes image data and text data. For example, the detection results obtained according to the skin condition detection method provided in Embodiment 1 are as follows: Figure 2 As shown, the displayed data includes an image of the area to be detected and skin condition information of the area to be detected, such as... Figure 2 The displayed data includes metabolic status, skin tone evenness, and water-oil balance. The data also includes marking information for identifying problem skin areas corresponding to the image of the area to be detected, such as oily areas or wound areas. By obtaining the displayed data according to the skin condition detection method provided in this application embodiment, users can intuitively understand their own skin condition. In some embodiments, Figure 2 The image of the part to be detected can be an infrared image with pseudo-color mapping, where different temperature regions correspond to different colors, which can improve the intuitiveness.

[0054] As can be seen from the above, the skin condition detection method provided in Embodiment 1 acquires an infrared image of the area to be detected, then analyzes the infrared image, determines the skin condition of each region of the area to be detected based on the mapping relationship between skin temperature and skin condition, and then performs visualization processing based on the skin condition of each region and the image of the area to be detected to obtain visualized display data of the skin condition. This skin condition detection method can detect specific problems existing in the skin and can analyze the skin condition itself based on the infrared image, without relying on professionals. The detection is convenient, simple, and the results are more intuitive.

[0055] In some embodiments, the image of the area to be detected in S06 is the infrared image in S02. Therefore, by acquiring the infrared image of the area to be detected using an infrared camera device, not only can the temperature distribution information of the skin at the area to be detected be obtained, but also the contour image information of the area to be detected. Thus, based on the mapping relationship between temperature and skin condition, the skin condition information of the area to be detected can be directly mapped onto the infrared image, allowing the user to intuitively perceive their skin condition. Furthermore, even in poor lighting conditions, the user can clearly obtain the contour information of the area to be detected through the infrared image, thereby understanding their skin condition anytime, anywhere. In other embodiments, the image of the area to be detected in S06 can also be a visible light image, a fusion image of an infrared light image and a visible light image, or any other information that can display the contour of the area to be detected. Please refer to [link to relevant documentation]. Figure 3 The diagram shown is a schematic flowchart of the skin condition detection method according to Embodiment 2 of this application. Embodiment 2 is basically the same as Embodiment 1, but in Embodiment 2, S04 is further defined. S04: Analyze the infrared image and determine the skin condition of each area of ​​the part to be detected according to the mapping relationship between skin temperature and skin condition, including S041a and S042a.

[0056] S041a: Analyze the infrared image to determine the temperature distribution areas in the part to be detected.

[0057] S042a: Determine the skin condition corresponding to each of the temperature distribution regions based on the temperature of each temperature distribution region and the mapping relationship between skin temperature and skin condition.

[0058] The infrared image is an image containing skin temperature information and image information of the area to be detected; in essence, it is a temperature image. Based on the infrared image, the temperature distribution of each region of the area to be detected can be determined, that is, the temperature magnitude and location information of each temperature distribution region of the area to be detected can be determined based on the infrared image.

[0059] Then, based on the mapping relationship between skin temperature and skin condition, the skin condition corresponding to each temperature distribution region of the area to be detected is determined, thereby determining the skin condition distribution of the area to be detected. The skin condition distribution includes skin condition types and the positional distribution of each skin condition type on the area to be detected. In Example 2, the mapping relationship between skin temperature and skin condition can be a mapping table or a corresponding deep learning-based mapping model.

[0060] Furthermore, in Embodiment 3, SO6: Visualization processing is performed on the skin condition of each region and the image of the area to be detected to obtain skin condition visualization display data. Specifically, visualization processing is performed on the skin condition of each temperature distribution region and the image of the area to be detected to obtain skin condition visualization display data.

[0061] Please see Figure 4 The diagram shows a flowchart of a skin condition detection method according to Embodiment 3 of this application. Embodiment 3 is essentially the same as Embodiment 2, except that in Embodiment 3, step S04: the infrared image is analyzed, and the skin condition of each region of the area to be detected is determined based on the mapping relationship between skin temperature and skin condition. This includes: inputting the infrared image into a skin temperature and skin condition mapping model, and determining the skin condition corresponding to each temperature distribution region in the infrared image through the skin temperature and skin condition mapping model. Clearly, the specific implementation methods for analyzing the infrared image and determining the skin condition of the area to be detected based on the mapping relationship between skin temperature and skin condition differ between Embodiment 3 and Embodiment 2. In Embodiment 2, the skin temperature distribution information of the area to be detected is first determined based on the infrared image, and then the skin temperature distribution information is analyzed, such as by inputting the skin temperature distribution information into a skin temperature and skin condition mapping model. This mapping model determines the skin condition distribution of the area to be detected based on the temperature magnitude and location information in the skin temperature distribution information. In Embodiment 3, the infrared image is directly input into the skin temperature and skin state mapping model. The mapping model analyzes the skin temperature distribution corresponding to the area to be detected based on the infrared image, and then maps the skin temperature to the skin state to determine the skin state corresponding to the infrared image, that is, to determine the mapping between the infrared image and the skin state.

[0062] Please see Figure 5 The diagram shows a flowchart of the skin condition detection method according to Embodiment 4 of this application. Embodiment 4 is essentially the same as Embodiment 3, but Embodiment 4 further specifies step S03. Specifically, before step S04: inputting the infrared image into the skin temperature and skin condition mapping model, and determining the skin condition corresponding to each temperature distribution region in the infrared image through the skin temperature and skin condition mapping model, the skin condition detection method further includes step S03: training a deep learning model using a sample set determined from infrared image samples of the detection area with calibrated skin conditions, to obtain the skin temperature and skin condition mapping model. Using infrared images of the detection area with calibrated corresponding skin conditions as the training sample set for the deep learning model, a robust skin temperature and skin condition mapping model can be obtained, which is beneficial for improving the accuracy of skin condition detection.

[0063] Please see Figure 6 As shown, it is a schematic diagram of the skin temperature and skin state mapping model construction process in the skin state detection method according to Embodiment 5 of this application. In Embodiment 5, S03: The deep learning model is trained based on the sample set determined by the infrared image samples of the detection area with calibrated skin state to obtain the skin temperature and skin state mapping model, which further includes S032, S034 and S036.

[0064] S032: Obtain a dataset, which includes infrared image samples of the parts to be detected corresponding to different objects at different time stages, locations and environments.

[0065] In Example 5, the region to be detected is a human face. Acquiring the dataset specifically includes acquiring infrared facial images of the same person at different times of the day, as well as infrared facial images of the same person in different seasons (spring, summer, autumn, winter). This process is repeated for different regions, acquiring infrared facial images of different people, and recording environmental information such as temperature, humidity, and weather on the day the infrared images were acquired. All acquired data constitutes the dataset.

[0066] S034: The skin condition corresponding to different temperature distribution regions of the infrared image samples in the dataset is calibrated to obtain a sample set.

[0067] The acquired data in the dataset are organized, and the skin conditions corresponding to each skin region on the infrared facial images in the dataset are marked, including but not limited to metabolism, oiliness, pigmentation, and wound condition, as well as areas with skin problems, including but not limited to oily areas and wound areas, to obtain a sample set that is convenient for machine deep learning. Specifically, the corresponding skin conditions are marked on the infrared images according to the mapping relationship between skin temperature and skin condition.

[0068] S036: Train the deep learning model based on the sample set to obtain the skin temperature and skin state mapping model.

[0069] The facial infrared images in the sample set that indicate skin condition include skin temperature and corresponding skin condition, i.e., they contain skin temperature and skin condition mapping information. Therefore, during the training process, the deep learning model can learn the mapping relationship between skin temperature and skin condition in the indicated facial infrared images, and after training, a skin temperature and skin condition mapping model can be obtained.

[0070] Please see Figure 7The diagram illustrates the process of constructing a skin temperature and skin state mapping model in the skin state detection method according to Embodiment Six of this application. Embodiment Six is ​​essentially the same as Embodiment Five, except that in Embodiment Six, S036: training a deep learning model based on the sample set to obtain the skin temperature and skin state mapping model includes: importing the infrared image samples of the calibrated skin state from the sample set into the deep learning model for training; the deep learning model learns the autocorrelation between skin temperature and skin state of the target area based on a self-attention mechanism learning strategy to obtain the skin temperature and skin state mapping model.

[0071] After determining the sample set, the calibrated facial infrared images are imported. The autocorrelation between facial skin temperature and skin condition is learned through a self-attention mechanism using a transformer structure. Based on facial infrared images of different objects at different times and locations in the dataset, the generalization ability of the designed encoding and decoding deep learning model is enhanced, thereby establishing a robust skin temperature and skin condition mapping model.

[0072] Please see Figure 8 The diagram shown is a flowchart of the skin condition detection method according to Embodiment 7 of this application. Embodiment 7 is basically the same as Embodiment 1, but in Embodiment 7, S06 is further defined, namely: S06: the step of performing visualization processing based on the skin condition of each region and the image of the area to be detected to obtain skin condition visualization display data includes: according to the skin condition of each region, using at least one of text, graphics or color to annotate the corresponding region in the image of the area to be detected, to obtain image display data of skin condition visualization.

[0073] The visualization data analysis module in the skin condition detection device is used to analyze the analysis results of the data analysis module. The data analysis module includes a skin condition analysis module, and the analysis results include the skin condition of each area in the area to be detected, as well as images of the area to be detected that are mapped to the skin condition. Therefore, in S06, the visualization processing module performs visualization processing on the skin condition of the area to be detected and the images of the area to be detected mapped to the skin condition. The images of the area to be detected are labeled and the skin condition information of the area to be detected is described using at least one of text, images, or colors. For example, the skin condition corresponding to each area is labeled on the image of the area to be detected, or only skin conditions with skin problems are labeled, such as circling oily areas or circling areas where wounds are inflamed. Alternatively, the skin condition information of the area to be detected is displayed within a display frame containing the image of the area to be detected, to intuitively describe the skin condition and problems, allowing the user to clearly understand the detected skin health.

[0074] Please see Figure 9 The diagram shown is a flowchart illustrating the skin condition detection method according to Embodiment 8 of this application. It is essentially the same as Embodiment 8, except that in Embodiment 8, after analyzing the infrared image in S04 and determining the skin condition of each area of ​​the area to be detected based on the mapping relationship between skin temperature and skin condition, the skin condition detection method further includes S05: analyzing the infrared image and determining the skin care plan corresponding to the area to be detected based on the skin condition of each area of ​​the area to be detected and the mapping relationship between skin condition and skin care plan. Figure 10 As shown, it is the detection result (display data) obtained according to the skin condition detection method provided in Embodiment 8 of this application, and... Figure 2 The difference is, Figure 10 The document further outlines skincare recommendations for problem skin areas, with different recommendations for different problem skin areas. For example, oily skin areas are advised to use moisturizing skincare products, while wound areas are advised to keep the wound clean and hygienic to reduce infection.

[0075] Furthermore, S06: Visualize the skin condition of each region and the image of the area to be detected to obtain visualized display data of the skin condition, including: visualizing the skin condition and the skin care plan of each region and the image of the area to be detected to obtain visualized display data of the skin condition and the skin care plan.

[0076] Skin temperature can be used to assess skin metabolism and thus skin condition. For example, oily areas are prone to acne and enlarged pores, all of which are reflections of skin condition. This establishes a mapping between skin temperature and skin problems. Since infrared imaging represents skin temperature in image form, a mapping between infrared images and skin condition can be established. This allows for the assessment of skin conditions, such as skin metabolism, oily areas, and pigmentation, based on the infrared image of the area being tested. Users can then take targeted measures based on their skin condition. For instance, areas with high sebum secretion are more prone to acne and require more intensive care, while areas with inflammation can be treated with targeted anti-inflammatory medications. Furthermore, the system allows for continuous monitoring of skin condition and tracking of changes.

[0077] Therefore, different skin conditions can correspond to different skincare strategies. After determining the mapping relationship between the infrared image of the area to be detected and the skin condition, the mapping relationship between the infrared image, skin condition, and skincare plan can be further determined based on the mapping relationship between skin condition and skincare plan. That is, based on the infrared image of the area to be detected, the corresponding skin condition and skincare plan can be obtained. During the visualization process in S06, visualization processing is also required based on the corresponding skincare plan. That is, the image of the area to be detected is visualized based on the mapping relationship between the infrared image, skin condition, and skincare plan to display skin condition information and corresponding skincare plan information within the frame displayed on the image of the area to be detected, and to mark the areas corresponding to the image of the area to be detected as having problematic skin conditions. Therefore, the data analysis module also includes analyzing the infrared image to obtain the skin condition of the area to be detected and the recommended skincare plan based on the skin condition.

[0078] The skin condition detection device implementing the aforementioned skin condition detection method also includes a display module. This display module displays visualized data, including image data and text data. Specifically, it outputs analysis results and processed infrared images. The skin analysis results are displayed visually and intuitively on a screen; for example, problematic areas can be circled on the output infrared image, or text descriptions can be provided for easy user understanding. Furthermore, it can recommend corresponding skincare solutions based on the user's skin problems. The display module can also be a module separate from the skin condition detection device itself. After obtaining the display data, the skin condition detection device sends it to the display module for display.

[0079] Please see Figure 11The diagram shown is a schematic representation of a skin condition detection device according to Embodiment 9 of this application. In Embodiment 9, the skin condition detection device includes an infrared image acquisition module 101, a skin condition analysis module 102, and a visualization processing module 103. The infrared image acquisition module 101 acquires infrared images of the area to be detected; the skin condition analysis module 102 analyzes the infrared images and determines the skin condition of each region of the area to be detected based on the mapping relationship between skin temperature and skin condition; the visualization processing module 103 performs visualization processing on the skin condition of each region and the image of the area to be detected to obtain visualized data of the skin condition.

[0080] Please see Figure 12 The diagram shown is a schematic representation of a skin condition detection device according to Embodiment 10 of this application. In Embodiment 10, the skin condition detection device includes a memory 202 and a processor 201. When the processor 201 executes the computer program instructions stored in the memory 202, it performs the steps of the skin condition detection method according to any embodiment of this application.

[0081] Please see Figure 13 The diagram shown is a schematic representation of a skin condition detection device according to Embodiment 11 of this application. In Embodiment 11, the skin condition detection device includes: an infrared acquisition module 210, an infrared imaging module 220, a data analysis module 310, a visualization processing module 320, and a display module 400.

[0082] The infrared acquisition module 210 is used to acquire the raw infrared data of the part to be detected and send it to the infrared imaging module 220.

[0083] The infrared imaging module 220 is used to obtain an infrared image of the part to be detected by performing temperature and width stretching, pseudo-color mapping, etc. on the original infrared image data.

[0084] The data analysis module 310 is used to analyze the infrared image, determine the skin condition of the area to be detected and the mapping relationship between the skin condition and the infrared image based on the infrared image, and further determine the mapping relationship between the infrared image, skin condition and skin care plan based on the mapping relationship between the skin condition and the skin care plan.

[0085] The visualization processing module 320 performs visualization processing on the analysis results of the data analysis module. The analysis results include the mapping relationship between the infrared image and the skin condition or the mapping relationship between the infrared image, skin condition, and skin care plan. The image of the area to be detected is visualized to obtain display data of skin condition or skin condition and skin care plan visualization. The display data includes image data and text data.

[0086] The display module 400 is used to display the visualized display data, including visualized images of the area to be detected, skin condition information, and skincare plan information.

[0087] The infrared imaging module 220, the data analysis module 310, and the visualization processing module 320 are all processing modules in the processor 201 in Embodiment 10.

[0088] In some embodiments, the infrared acquisition module 210 and / or the display module 400 may be integrated inside the skin condition detection device, or they may be modules that have a communication connection with the skin condition detection device and are located outside the skin condition detection device.

[0089] Please see Figure 14 The diagram shows a schematic of a smart mirror according to Embodiment Twelve of this application. In Embodiment Twelve, the smart mirror includes a skin condition detection device 300, an infrared image module 200, and a mirror display module 400, as provided in Embodiment Ten of this application. The infrared image module 200 is used to acquire infrared images of the area to be detected and send them to the skin condition detection device 300. The mirror display module 400 is used to display visualized data of the skin condition. It also includes a switch module 500 for controlling the power on / off state of the smart mirror. When the smart mirror is powered on, it acquires infrared images of the user's area to be detected, analyzes them to determine the skin condition of the area to be detected or the skin condition and corresponding skincare plan, and visualizes the analysis results and displays the visualized data on the mirror display module 400. When the smart mirror is powered off, the mirror display module 400 functions as a mirror.

[0090] Furthermore, other multispectral imaging technologies can be integrated into the smart mirror, as can an operating system, allowing it to be used as a tablet. The smart mirror with skin detection functionality provided in this application solves the problem of people having to go to professional institutions for skin testing; users can monitor their skin condition at home anytime.

[0091] In addition, this application also provides a computer-readable storage medium storing computer program instructions; when the computer program instructions are executed by a processor, they implement the steps of the skin condition detection method according to any embodiment of this application.

[0092] The aforementioned processor may be a CPU (Central Processing Unit), an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement embodiments of the present invention. The moving target detection device includes one or more processors, which may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0093] The aforementioned memory may include high-speed RAM (Random Access Memory) and may also include NVM (Non-Volatile Memory), such as at least one disk storage device.

[0094] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A skin condition detection method, applied to a skin condition detection device, characterized in that, include: Acquire infrared images of the area to be detected; The infrared image is analyzed, and the skin condition corresponding to each temperature distribution region of the area to be detected is determined based on the mapping relationship between skin temperature and skin condition. This analysis includes: inputting the infrared image into a skin temperature and skin condition mapping model, and determining the skin condition corresponding to each temperature distribution region in the infrared image through the model. The skin temperature and skin condition mapping model is obtained by training a deep learning model based on a sample set, which includes infrared image samples of the area to be detected labeled with skin condition. Before inputting the infrared image into the skin temperature and skin condition mapping model and determining the skin condition corresponding to each temperature distribution region in the infrared image through the model, the skin condition detection method further includes: acquiring the sample set, importing the infrared image samples labeled with skin condition from the sample set into a deep learning model for training, and the deep learning model learning the autocorrelation between skin temperature and skin condition of the area to be detected based on a self-attention mechanism learning strategy to obtain the skin temperature and skin condition mapping model. The images of the skin condition and the area to be detected corresponding to each temperature distribution region are visualized to obtain visualized data of the skin condition.

2. The skin condition detection method according to claim 1, characterized in that, The step of analyzing the infrared image and determining the skin condition corresponding to each temperature distribution area of ​​the area to be detected based on the mapping relationship between skin temperature and skin condition includes: The infrared image is analyzed to determine the temperature distribution regions in the area to be detected; Based on the temperature of each temperature distribution area and the mapping relationship between skin temperature and skin condition, the skin condition corresponding to each temperature distribution area is determined.

3. The skin condition detection method according to claim 1, characterized in that, The process of obtaining the sample set includes: Obtain a dataset, which includes infrared image samples of the parts to be detected corresponding to different objects at different time stages, locations and environments; The skin condition corresponding to different temperature distribution regions of the infrared image samples in the dataset is calibrated to obtain a sample set.

4. The skin condition detection method according to claim 1, characterized in that, The step of visualizing the skin condition based on the skin condition corresponding to each temperature distribution region and the image of the area to be detected to obtain visualized skin condition display data includes: Based on the skin condition corresponding to each temperature distribution area, the corresponding area in the image of the part to be detected is marked using at least one of text, graphics, or color to obtain image display data that visualizes the skin condition.

5. The skin condition detection method according to claim 1, characterized in that, The skin condition detection method also includes: The infrared image is analyzed, and the skin condition corresponding to each temperature distribution area of ​​the area to be detected and the mapping relationship between the skin condition and the skin care plan are determined to determine the skin care plan corresponding to the area to be detected. Based on the skin condition corresponding to each temperature distribution area, the corresponding skin care plan, and the image of the area to be detected, visualization processing is performed to obtain visualized display data of skin condition and skin care plan.

6. The skin condition detection method according to any one of claims 1 to 5, characterized in that, The skin condition detection method also includes: Based on the skin condition corresponding to each temperature distribution area and the infrared image, visualization processing is performed to obtain skin condition visualization display data.

7. A skin condition detection device, characterized in that, include: Infrared image acquisition module, used to acquire infrared images of the area to be detected; The skin condition analysis module is used to analyze the infrared image and determine the skin condition corresponding to each temperature distribution region of the area to be detected based on the mapping relationship between skin temperature and skin condition. The analysis of the infrared image and determination of the skin condition corresponding to each temperature distribution region of the area to be detected includes: inputting the infrared image into a skin temperature and skin condition mapping model, and determining the skin condition corresponding to each temperature distribution region in the infrared image through the skin temperature and skin condition mapping model; wherein the skin temperature and skin condition mapping model is obtained by training a deep learning model based on a sample set. The sample set includes infrared image samples of the detection area labeled with skin condition. Before inputting the infrared image into the skin temperature and skin condition mapping model and determining the skin condition corresponding to each temperature distribution area in the infrared image through the skin temperature and skin condition mapping model, the skin condition analysis module is further configured to: acquire the sample set, import the infrared image samples labeled with skin condition in the sample set into a deep learning model for training, and the deep learning model learns the autocorrelation between the skin temperature and skin condition of the detection area based on a self-attention mechanism learning strategy to obtain the skin temperature and skin condition mapping model. The visualization processing module is used to perform visualization processing on the skin condition corresponding to each temperature distribution area and the image of the area to be detected, so as to obtain the visualization display data of the skin condition.

8. A skin condition detection device, characterized in that, include: Processor and memory; When the processor executes the computer program instructions stored in the memory, it performs the steps of the skin condition detection method according to any one of claims 1 to 6.

9. A smart mirror, characterized in that, include: The skin condition detection device as described in claim 8; An infrared image module is used to acquire infrared images of the area to be detected and send them to the skin condition detection device; A mirror display module is used to display visual data of the skin condition.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions; When the computer program instructions are executed by the processor, they implement the steps of the skin condition detection method according to any one of claims 1 to 6.

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