Multi-device beauty mode rapid matching method and system based on intelligent skin measurement

Abstract

The invention discloses a multi-device beauty mode rapid matching method and system based on intelligent skin measurement, and belongs to the technical field of beauty equipment, the facial image of a target user is acquired through a user terminal, the usability and convenience of an individual user are improved, and the user experience is improved through facial image processing and feature recognition. According to the method, accurate facial skin feature data are obtained, intelligent analysis is carried out on the facial skin feature data according to a skin detection analysis model, a skin detection analysis comprehensive scoring result is obtained, and the integrated process of skin detection and beauty analysis is achieved; besides, the beauty modes are matched according to the skin detection and analysis comprehensive scoring result, each beauty mode corresponds to each target beauty device, and effective cooperative control of multiple devices is formed.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of cosmetic equipment, and particularly relates to a multi-device cosmetic mode rapid matching method and system based on intelligent skin testing. BACKGROUND

[0002] At present, with the development of the cosmetic industry, people's demand for cosmetics is getting higher and higher. In the cosmetic preparation process, the traditional skin testing method not only takes a long time, but also needs professional beauticians to make judgments according to experience, which leads to incomplete detection of the user's skin and easy misjudgment. Moreover, after obtaining the test results, the beautician needs to carefully analyze the specific analysis results, determine the cosmetic scheme according to the analysis results, and then select the corresponding cosmetic equipment for cosmetic treatment. First of all, the traditional skin testing judgment and test result analysis in this process are mostly based on the experience of beauticians, which is obviously not accurate. Therefore, an intelligent cosmetic skin testing method based on visual detection has appeared, such as the skin state prediction method in the existing patent CN114209288B. The method obtains the skin information of the user, analyzes the user's skin problems through a prediction model, forms an expected skin state through a repair model, combines the skin problems with the expected skin state, and outputs the scheme to the terminal. However, such a process is still too cumbersome for the overall cosmetic preparation process, as it still requires beauticians to analyze the skin problems and the expected skin state.

[0003] In addition, the existing intelligent skin testing method can only control one matched cosmetic device, which makes the existing intelligent skin testing cosmetic method unable to form multi-device collaborative control in use. Moreover, the cosmetic device terminal mainly targets the B-end market, and users need to use the cosmetic skin testing device in the line to realize skin testing, which does not have easy-to-use and convenient features for users.

[0004] As mentioned above, how to provide a skin testing and cosmetic integrated process that can realize multi-device collaborative control and improve the easy-to-use and convenient features of the multi-device cosmetic mode rapid matching method and system based on intelligent skin testing has become a problem to be solved. SUMMARY

[0005] The purpose of the present application is to provide a multi-device cosmetic mode rapid matching method based on intelligent skin testing to solve the above-mentioned problems existing in the prior art.

[0006] In order to achieve the above-mentioned purpose, the present application adopts the following technical solutions: In a first aspect, the present application provides a multi-device cosmetic mode rapid matching method based on intelligent skin testing, which includes: obtaining a facial image of a target user; performing image processing and feature extraction on the facial image to obtain facial skin feature data; obtaining a pre-trained skin detection analysis model, and obtaining a skin detection analysis result of the target user by the skin detection analysis model based on the facial skin feature data; obtaining a preset multi-dimensional skin index proportion corresponding table, and performing comprehensive score calculation on the skin detection analysis result according to the facial skin feature data to obtain a target user skin detection analysis comprehensive score result; based on the target user skin detection analysis comprehensive score result, generating a target user beauty mode, and receiving a user control instruction to control each household beauty device according to the target user beauty mode.

[0007] In a possible design, obtaining a facial image of a target user includes: obtaining multiple initial facial images of the target user through a terminal device of the target user; selecting an initial facial image with complete face and appropriate brightness from the multiple initial facial images as a preselected facial image; obtaining a preset facial angle standard, and performing facial angle determination on the preselected facial image according to the facial angle standard, wherein the facial angle standard includes a front facial angle standard, a left facial angle standard, and a right facial angle standard; if the preselected facial image meets the front facial angle standard, the preselected facial image is named as a front facial first image, if the preselected facial image meets the left facial angle standard, the preselected facial image is named as a left facial second image, and if the preselected facial image meets the right facial angle standard, the preselected facial image is named as a right facial third image; annotating the obtained front facial first image, left facial second image, and right facial third image according to the facial angle standard, and integrating the annotated front facial first image, left facial second image, and right facial third image to form a facial image of the target user.

[0008] In a possible design, performing image processing and feature extraction on the facial image to obtain facial skin feature data includes: performing illumination equalization processing on the facial image, and mapping the front facial first image, left facial second image, and right facial third image to a standard front facial coordinate system by a facial key point detection method to obtain a three-dimensional facial model, wherein the three-dimensional facial model includes each facial key point; Based on the three-dimensional face model, each face key point is aligned by using a SIFT technology, and each aligned face key point is projected to a two-dimensional plane to form a complete target user face texture map; From the target user face texture map, a cheek region texture map is extracted, and saturation and brightness features of the cheek region texture map are identified to obtain a target user skin type parameter, wherein the target user skin type parameter includes average skin saturation and average skin brightness; A preset skin type parameter threshold is obtained, and the target user skin type parameter is compared with the skin type parameter threshold to determine the skin type of the target user according to the comparison result, so as to take the skin type of the target user as skin type data; From the target user face texture map, a wrinkle region texture map is extracted, and wrinkle density and wrinkle depth of the wrinkle region texture map are identified to obtain a target user wrinkle feature, so as to take the target user wrinkle feature as a wrinkle feature data; The target user face texture map is subjected to circular dark spot identification to obtain a plurality of circular dark spots, and according to the diameters of the circular dark spots, the target user pore density is counted, so as to take the target user pore density as pore feature data; The target user face texture map is subjected to flaw identification to obtain a plurality of flaw feature points, each flaw feature point is analyzed to obtain a flaw type and a flaw position of each flaw feature point, and the flaw type and the flaw position of each flaw feature point are taken as flaw feature data; The skin type data, the wrinkle feature data, the pore feature data and the flaw feature data are integrated to form face skin feature data.

[0009] In a possible design, the training process of the skin detection and analysis model includes: Obtain historical user face skin feature data and historical user face skin score records, wherein the historical user face skin feature data includes historical user skin type data, historical user wrinkle feature data, historical user pore feature data and historical user flaw feature data, and the historical user face skin score records are percentage real score values of wrinkle features and flaw features of historical users with different skin types; The historical user face skin feature data is divided into historical user dry skin feature data, historical user oily skin feature data and historical user mixed skin feature data according to historical user skin type data; respectively, as input variables, and the historical user facial skin score records as output variables, to train sub-models and obtain a dry skin detection and analysis sub-model, an oily skin detection and analysis sub-model, and a mixed skin detection and analysis sub-model; The dry skin detection and analysis sub-model, the oily skin detection and analysis sub-model, and the mixed skin detection and analysis sub-model are integrated into a skin detection and analysis model.

[0010] In a possible design, based on the facial skin feature data, the skin detection and analysis model is used to obtain a skin detection and analysis result of the target user, including: The facial skin feature data is input into the skin detection and analysis model, and the target user skin type of the target user is determined according to the skin quality type data in the facial skin feature data, where the target user skin type is dry skin quality, oily skin quality, or mixed skin quality. Based on the target user skin type, the dry skin detection and analysis sub-model, the oily skin detection and analysis sub-model, or the mixed skin detection and analysis sub-model is selected as a target user skin detection and analysis sub-model in the skin detection and analysis model. The facial skin feature data is input into the target user skin detection and analysis sub-model to obtain a target user wrinkle score, a target user pore score, and target user each type of flaw score, and the target user skin type, the target user wrinkle score, the target user pore score, and the target user each type of flaw score are integrated to obtain a skin detection and analysis result of the target user.

[0011] In a possible design, a preset multi-dimension skin index proportion corresponding table is obtained, and a comprehensive score of the skin detection and analysis result is calculated according to the facial skin feature data to obtain a target user skin detection and analysis comprehensive score result, including: A preset multi-dimension skin index proportion corresponding table is obtained, where the multi-dimension skin index proportion corresponding table includes index proportions of wrinkles, pores, and each type of flaw in each skin quality type, and the each type of flaw includes blackheads, acne, and color spots. Based on the multi-dimension skin index proportion corresponding table, weights of wrinkles, pores, and each type of flaw in each skin quality type are calculated to obtain a multi-dimension weight analysis table. The multi-dimension weight analysis table is used to perform weighted processing on the skin detection and analysis result of the target user to obtain a target user wrinkle weighted score, a target user pore weighted score, and target user each type of flaw weighted score. summing the target user wrinkle weighted score, the target user pore weighted score and the target user each type of flaw weighted score to obtain a target user skin detection analysis comprehensive score result; Correspondingly, after obtaining the target user skin detection analysis comprehensive score result, the method further includes: Based on the target user wrinkle weighted score, the target user pore weighted score, the target user each type of flaw weighted score and the target user skin detection analysis comprehensive score result, a target user skin detection analysis report is generated; The target user skin detection analysis report is sent to the terminal device of the target user to visually display the target user skin detection analysis report.

[0012] In a possible design, based on the target user skin detection analysis comprehensive score result, a target user beauty mode is generated, and a user control instruction is received to control each household beauty device according to the target user beauty mode, including: A preset beauty mode library is obtained, wherein the beauty mode library is used to record the correspondence between a plurality of beauty modes and each user skin detection analysis comprehensive score result; According to the beauty mode library, a beauty mode corresponding to the target user skin detection analysis comprehensive score result is matched as a target user beauty mode; According to the target user beauty mode, at least one household beauty device is selected as a target beauty device, wherein the household beauty device includes a radio frequency beauty instrument, an LED light therapy beauty mask, a micro-current beauty instrument, an electroporation beauty instrument, an ultrasonic beauty instrument and an ionophoresis instrument; The target user beauty mode is sent to each target beauty device through wireless communication by using the terminal device of the target user, wherein the wireless communication includes Bluetooth communication and WiFi communication; The terminal device of the target user sends a beauty mode start instruction to each target beauty device, and controls each target beauty device to start according to the beauty mode start instruction to correspondingly execute the target user beauty mode.

[0013] In a possible design, the target user beauty mode includes a target beauty device identification code and a target beauty device control priority, and according to the target user beauty mode, at least one household beauty device is selected as a target beauty device, including: Through the terminal device of the target user, the ID numbers of each household beauty device wirelessly connected to the terminal device of the target user are obtained, and a household beauty device with an ID number matching the target beauty device identification code in the target user beauty mode is selected as a target beauty device; Correspondingly, the target user beauty mode is executed, and the target user beauty mode comprises: Each target beauty device enters a pre-start state after receiving the beauty mode start instruction, and completes device start in stages according to a target beauty device control priority in the target user beauty mode, to execute the target user beauty mode.

[0014] In a second aspect, the present application provides a multi-device beauty mode fast matching system based on intelligent skin testing, which is used to implement the multi-device beauty mode fast matching method based on intelligent skin testing as described in the first aspect or any possible design of the first aspect, and comprises: a face image acquisition unit, configured to acquire a face image of a target user; a face skin feature extraction unit, configured to perform image processing and feature extraction on the face image to obtain face skin feature data; a skin testing and analysis unit, configured to acquire a pre-trained skin testing and analysis model, and obtain a skin testing and analysis result of the target user by the skin testing and analysis model based on the face skin feature data; a skin comprehensive scoring unit, configured to acquire a preset multi-dimensional skin index proportion corresponding table, and perform comprehensive scoring calculation on the skin testing and analysis result according to the face skin feature data to obtain a target user skin testing and analysis comprehensive scoring result; a beauty mode matching unit, configured to generate a target user beauty mode based on the target user skin testing and analysis comprehensive scoring result, and receive a user control instruction to control each household beauty device according to the target user beauty mode.

[0015] In a third aspect, the present application provides an electronic device, comprising a memory, a processor and a transceiver connected in sequence and in communication, wherein the memory is configured to store a computer program, the transceiver is configured to transceive messages, and the processor is configured to read the computer program and execute the multi-device beauty mode fast matching method based on intelligent skin testing as described in the first aspect or any possible design of the first aspect.

[0016] In a fourth aspect, the present application provides a computer readable storage medium, wherein the computer readable storage medium stores instructions, and when the instructions run on a computer, the multi-device beauty mode fast matching method based on intelligent skin testing as described in the first aspect or any possible design of the first aspect is executed.

[0017] In a fifth aspect, the present application provides a computer program product comprising instructions, and when the instructions run on a computer, the computer is caused to execute the multi-device beauty mode fast matching method based on intelligent skin testing as described in the first aspect or any possible design of the first aspect.

[0018] Beneficial Effects: This invention provides a method and system for rapid matching of beauty modes across multiple devices based on intelligent skin analysis, comprising: first, acquiring a facial image of a target user; second, performing image processing and feature extraction on the facial image to obtain facial skin feature data; then, acquiring a pre-trained skin detection and analysis model, and obtaining the target user's skin detection and analysis results based on the facial skin feature data; furthermore, acquiring a preset multi-dimensional skin index ratio correspondence table, and calculating a comprehensive score for the skin detection and analysis results based on the facial skin feature data to obtain a comprehensive skin detection and analysis score for the target user; finally, based on the target user's skin detection score... The system analyzes the comprehensive scoring results, generates a beauty mode for the target user, and receives user control commands to control various home beauty devices according to the target user's beauty mode. It acquires the target user's facial image through the user terminal, improving ease of use and convenience for individual users. Through facial image processing and feature recognition, accurate facial skin feature data is obtained, and intelligent analysis of the facial skin feature data is performed based on a skin detection and analysis model to obtain a comprehensive skin detection and analysis score. This achieves an integrated process for skin testing and beauty analysis. Furthermore, beauty modes are matched according to the comprehensive skin detection and analysis score, and each beauty mode corresponds to a specific target beauty device, forming effective collaborative control of multiple devices. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating the steps of a method for rapidly matching multiple device beauty modes based on intelligent skin analysis, as provided in an embodiment of the present invention. Figure 2 This is a functional structure diagram of a multi-device beauty mode rapid matching system based on intelligent skin analysis provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the present invention will be briefly introduced below in conjunction with the accompanying drawings and descriptions of the embodiments or the prior art. Obviously, the following description of the structure of the accompanying drawings is only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. It should be noted that the description of these embodiments is for the purpose of helping to understand the present invention, but does not constitute a limitation of the present invention.

[0021] It should be understood that although the terms first, second, etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit, without departing from the scope of the exemplary embodiments of the invention.

[0022] It should be understood that the term "and / or" that may appear in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, B exists alone, and A and B exist simultaneously. The term " / and" that may appear in this document describes another relationship between related objects, indicating that two relationships can exist. For example, A / and B can mean: A exists alone, and A and B exist alone. In addition, the character " / " that may appear in this document generally indicates that the related objects before and after it are in an "or" relationship.

[0023] Example: like Figure 1 As shown, the first aspect of this embodiment provides a method for rapid matching of beauty modes across multiple devices based on intelligent skin analysis, which may include, but is not limited to, the following steps: S1. Obtain the facial image of the target user; In one possible implementation, step S1, acquiring the facial image of the target user, can be broken down into, but is not limited to, the following steps S11-S15, including: S11. Obtain multiple initial facial images of the target user through the target user's terminal device; S12. Select an initial facial image with a complete, unobstructed face and moderate brightness from multiple initial facial images as a pre-selected facial image; S13. Obtain a preset facial angle standard, and determine the facial angle of the pre-selected facial image according to the facial angle standard, wherein the facial angle standard includes a frontal facial angle standard, a left facial angle standard, and a right facial angle standard; S14. If the pre-selected facial image meets the frontal face angle standard, it is named the first frontal face image; if the pre-selected facial image meets the left face angle standard, it is named the second left face image; if the pre-selected facial image meets the right face angle standard, it is named the third right face image. S15. The obtained first frontal image, second left facial image, and third right facial image are labeled according to the facial angle standard, and the labeled first frontal image, second left facial image, and third right facial image are integrated to form the facial image of the target user.

[0024] It should be noted that the target user's terminal device mentioned in this embodiment includes smartphones, computers, and handheld camera devices with general computing power. Any device capable of capturing clear, high-resolution images of the user's face can serve as the target user's terminal device. This is because, in this embodiment, the image analysis process involves sending the obtained facial image to the corresponding deployed cinema analysis equipment via a mini-program or software on the terminal device. The user's terminal device does not require powerful computing power or a built-in analysis system. Therefore, this significantly reduces the computing power requirements of the terminal device in this embodiment, making it more universal and improving ease of use and convenience for individual beauty users. Furthermore, the accurate acquisition and screening of multiple images ensures complete data support for subsequent feature recognition and analysis processes, resulting in more accurate final analysis results (facial skin feature data and comprehensive skin detection analysis score).

[0025] S2. Perform image processing and feature extraction on the facial image to obtain facial skin feature data; In one possible implementation, step S2 involves image processing and feature extraction of the facial image to obtain facial skin feature data. This can be broken down into, but is not limited to, the following steps S21-S15, including: S21. Perform illumination equalization processing on the facial image, and use the facial key point detection method to uniformly map the first frontal face image, the second left face image, and the third right face image to the standard frontal face coordinate system to obtain a three-dimensional facial model, wherein the three-dimensional facial model includes various facial key points. S22. Based on the three-dimensional facial model, SIFT technology is used to align each facial key point, and the aligned facial key points are projected onto a two-dimensional plane to form a complete facial texture map of the target user. S23. Extract the cheek region texture map from the target user's facial texture map, and perform saturation and brightness feature recognition on the cheek region texture map to obtain the target user's skin type parameters, wherein the target user's skin type parameters include average skin saturation and average skin brightness; S24. Obtain a preset skin type parameter threshold, compare the target user's skin type parameter with the skin type parameter threshold, determine the target user's skin type based on the comparison result, and use the target user's skin type as skin type data; S25. Extract the wrinkle region texture map from the target user's facial texture map, and identify the wrinkle density and wrinkle depth of the wrinkle region texture map to obtain the target user's wrinkle features, and use the target user's wrinkle features as wrinkle feature data. S26. Circular dark spots are identified on the facial texture map of the target user to obtain multiple circular dark spots. Based on the diameter of each circular dark spot, the pore density of the target user is calculated to use the pore density of the target user as pore feature data. S27. Perform blemish identification on the facial texture map of the target user to obtain multiple blemish feature points, analyze each blemish feature point to obtain the blemish type and blemish location of each blemish feature point, and use the blemish type and blemish location of each blemish feature point as blemish feature data. S28. Integrate the skin type data, wrinkle feature data, pore feature data, and blemish feature data to form facial skin feature data.

[0026] It should be noted that in this embodiment, the 3D facial model is obtained by 3D stitching the target user's facial image to simulate the structure of a real human face, making subsequent feature recognition more accurate. In specific applications, the facial key point detection method can use 68-point facial key point detection to uniformly map the key points detected in the first frontal image, the second left facial image, and the third right facial image to a standard frontal coordinate system to form a 3D facial model. The standard frontal coordinate system mentioned here can be determined according to actual analysis needs, based on some important or significant key points in the user's facial image. Preferably, through 68-point facial key point detection, the nose tip point detected in the first frontal image is selected as the origin, the line connecting the inner canthus of the left eye to the inner canthus of the right eye is the x-axis, the line connecting the nose tip point to the center of the eyebrows is the y-axis, and the direction perpendicular to the frontal face outward is the z-axis, thus establishing the standard frontal coordinate system.

[0027] SIFT (Scale-Invariant Feature Transform) is a keypoint detection and description algorithm widely used in the field of computer vision. It is scale, rotation and brightness invariant, and can stably extract features under complex image changes. By using it to align each facial keypoint, stable facial keypoint features can be obtained, so as to form a clear and complete facial texture map of the target user.

[0028] Furthermore, identifying the target user's skin type involves extracting the cheek area (excluding key points corresponding to facial features) from the HSV (Hue, Saturation, and Value) color space, and calculating the average saturation and brightness of the cheek area to determine the skin type. Specific skin types may include, but are not limited to, dry, oily, and combination skin. Identifying wrinkle density and depth requires extracting texture features from the target user's facial texture image, calculating the percentage of wrinkle pixels per unit area as wrinkle density, and calculating the grayscale gradient change in the wrinkle area as wrinkle depth. Identifying the target user's pore density requires setting a diameter threshold for circular dark spots. In a high-resolution facial texture image, circular dark spots of suitable diameter can be selected as pores based on the diameter threshold, and the number of pores per unit area can be counted to obtain pore density. Obtaining blemish feature data requires the use of visual detection models (e.g., YOLO (You Only Look)). The algorithm model of the Once series, preferably the YOLOv5 model in this embodiment, is used to implement the final defect types, which may include, but are not limited to, blackheads, acne and blemishes.

[0029] S3. Obtain a pre-trained skin detection and analysis model, and based on the facial skin feature data, obtain the skin detection and analysis results of the target user through the skin detection and analysis model; In one possible implementation, the training process of the skin detection and analysis model in step S3 may include, but is not limited to, the following steps S301-S304: S301. Obtain historical user facial skin feature data and historical user facial skin score records, wherein the historical user facial skin feature data includes historical user skin type data, historical user wrinkle feature data, historical user pore feature data and historical user blemish feature data, and the historical user facial skin score records are percentage-based real number scores for wrinkle features and blemish features of historical users for each different skin type. S302. The historical user facial skin feature data is divided into historical user dry skin feature data, historical user oily skin feature data and historical user combination skin feature data according to the historical user skin type data; S303. Using the historical user dry skin feature data, the historical user oily skin feature data, and the historical user combination skin feature data as inputs, and the historical user facial skin score records as outputs, sub-model training is performed to obtain a dry skin detection and analysis sub-model, an oily skin detection and analysis sub-model, and a combination skin detection and analysis sub-model. S304. Integrate the dry skin detection and analysis sub-model, the oily skin detection and analysis sub-model, and the combination skin detection and analysis sub-model into a skin detection and analysis model.

[0030] In one possible implementation, step S3, based on the facial skin feature data, obtains the skin detection analysis result of the target user through the skin detection analysis model, which can be decomposed into, but is not limited to, the following steps S31-S33, including: S31. Input the facial skin feature data into the skin detection and analysis model, and determine the target user's skin type based on the skin type data in the facial skin feature data, wherein the target user's skin type is dry skin, oily skin, or combination skin. S32. Based on the target user's skin type, select the dry skin detection and analysis sub-model, the oily skin detection and analysis sub-model, or the combination skin detection and analysis sub-model as the target user's skin detection and analysis sub-model in the skin detection and analysis model. S33. Input the facial skin feature data into the target user skin detection and analysis sub-model to obtain the target user wrinkle score, target user pore score and target user blemish scores of various types. Integrate the target user skin type, the target user wrinkle score, the target user pore score and the target user blemish scores of various types to obtain the target user skin detection and analysis results.

[0031] It should be noted that the target user's wrinkle score, pore score, and various types of blemish scores in this embodiment are all out of 100. This scoring mechanism can be achieved based on the scoring steps of existing AI intelligent skin analysis models, so it will not be elaborated here. Through facial image processing and feature recognition, accurate facial skin feature data is obtained. Furthermore, this embodiment utilizes a skin detection and analysis model to intelligently analyze the facial skin feature data, obtaining the target user's skin detection and analysis results. This corresponds to the step in the traditional beauty preparation process where the beautician analyzes the specific detection results. Compared to the traditional step, this embodiment not only saves on complex analysis procedures but also calculates more accurate analysis results and precise score values ​​based on machine algorithms, achieving refined analysis and standardized scoring to ensure that the obtained skin detection and analysis results are more objective and reasonable.

[0032] S4. Obtain a preset multi-dimensional skin index ratio correspondence table, and calculate a comprehensive score for the skin detection and analysis results based on the facial skin feature data to obtain the comprehensive skin detection and analysis score result for the target user; In one possible implementation, step S4 involves obtaining a preset multi-dimensional skin index ratio correspondence table, and calculating a comprehensive score for the skin detection and analysis results based on the facial skin feature data to obtain the comprehensive skin detection and analysis score result for the target user. This step can be broken down into, but is not limited to, the following steps S41-S44, including: S41. Obtain a preset multi-dimensional skin index ratio correspondence table, wherein the multi-dimensional skin index ratio correspondence table includes the index ratios of wrinkles, pores and various types of blemishes in each skin type, and the various types of blemishes include blackheads, acne and pigmentation. S42. Based on the multi-dimensional skin index ratio correspondence table, calculate the weights of wrinkles, pores and various types of blemishes in each skin type to obtain a multi-dimensional weight analysis table; S43. Using the multi-dimensional weight analysis table, the skin detection analysis results of the target user are weighted to obtain the target user's wrinkle weight score, target user's pore weight score, and target user's various types of blemish weight scores. S44. Sum the target user's wrinkle weighted score, the target user's pore weighted score, and the target user's weighted scores for each type of blemish to obtain the target user's comprehensive skin detection and analysis score. Accordingly, in step S4, after obtaining the comprehensive score result of the target user's skin detection and analysis, the following steps S451-S452 may also be included, but are not limited to: S451. Based on the target user's wrinkle weighted score, the target user's pore weighted score, the target user's weighted scores for each type of blemish, and the target user's comprehensive skin detection and analysis score, generate a target user's skin detection and analysis report. S452. Send the target user's skin detection and analysis report to the target user's terminal device to visualize the target user's skin detection and analysis report.

[0033] It should be noted that the calculation of the comprehensive skin analysis score incorporates a multi-dimensional weighted analysis process. This enables precise skin analysis based on skin type, and calculates the weights of wrinkles, pores, and various types of blemishes within each skin type. This yields the impact of wrinkles, pores, and various types of blemishes on different skin types, allowing for the analysis of differences among users with different skin types. This ensures that the final comprehensive skin analysis score for the target user includes skin type factors, making the results more comprehensive and accurate, and facilitating an integrated process for skin analysis and beauty analysis.

[0034] The generation of the target user's skin detection and analysis report ensures that users can receive the analysis report in advance when they are unable to undergo cosmetic treatments in a timely manner, and make preparations and arrangements accordingly. This obviously ensures the convenience of this embodiment for individual users.

[0035] S5. Based on the comprehensive score result of the target user's skin detection analysis, generate a beauty mode for the target user and receive user control instructions to control each home beauty device according to the target user's beauty mode.

[0036] In one possible implementation, step S5, based on the comprehensive score result of the target user's skin detection analysis, generates a beauty mode for the target user and receives user control instructions to control various home beauty devices according to the target user's beauty mode. This can be broken down into, but is not limited to, the following steps S51-S55, including: S51. Obtain a preset beauty mode library, wherein the beauty mode library is used to record the correspondence between various beauty modes and the comprehensive score results of skin detection and analysis for each user; S52. Based on the beauty mode library, match the beauty mode corresponding to the comprehensive score result of the target user's skin detection and analysis, and use it as the target user's beauty mode; S53. Select at least one home beauty device as the target beauty device according to the target user's beauty mode, wherein the home beauty device includes a radio frequency beauty device, an LED light therapy beauty mask, a microcurrent beauty device, an electroporation beauty device, an ultrasonic beauty device, and an iontophoresis device; S54. Using the target user's terminal device, the target user's beauty mode is sent to each target beauty device via wireless communication, wherein the wireless communication includes Bluetooth communication and WiFi communication; S55 uses the target user's terminal device to send a beauty mode activation command to each target beauty device, and controls each target beauty device to start according to the beauty mode activation command, so as to execute the target user's beauty mode accordingly.

[0037] In one possible implementation, in step S5, the target user beauty mode includes a target beauty device identification code and a target beauty device control priority, and in step S53, selecting at least one home beauty device as the target beauty device according to the target user beauty mode may include, but is not limited to, the following step S531: S531. Obtain the ID number of each home beauty device that is wirelessly connected to the target user's terminal device through the target user's terminal device, and select the home beauty device whose ID number matches the target beauty device identification code in the target user's beauty mode as the target beauty device; Accordingly, in step S55, executing the target user's beauty mode may include, but is not limited to, the following step S551: S551. After receiving the beauty mode start command, each target beauty device enters the pre-start state and completes the device start-up step by step according to the target beauty device control priority in the target user beauty mode to execute the target user beauty mode.

[0038] It should be noted that in this embodiment, a beauty mode library is preset, and beauty modes are matched accordingly based on the comprehensive score results of skin detection analysis. In specific applications, each beauty mode corresponds to at least one home beauty device, and the association between each beauty mode and each target beauty device can be stored in the beauty mode library. When the target user confirms the beauty mode, the corresponding association in the beauty mode library can be retrieved to select each beauty device. Based on this association and the comprehensive score results of skin detection analysis, corresponding device control commands are generated for each target beauty device, thereby realizing effective collaborative control of multiple devices.

[0039] Furthermore, this embodiment also introduces the acquisition of beauty mode activation commands. In specific applications, the user receives the target user beauty mode through the terminal device and directly matches it with the target beauty device. After matching is completed, the target beauty mode can be regarded as entering the ready-to-start state. At this time, the target user's terminal device can actively send a prompt to the target user whether to start. The target user completes the start command according to the prompt, realizing one-click start control of each target beauty device. Each target beauty device performs corresponding work according to the target beauty mode to provide beauty care to the target user. Moreover, after starting, the target user's terminal device will display a control interface. The user can use this interface to control the beauty pause and restart functions in real time, greatly improving the convenience of beauty care for users.

[0040] In practical applications, users only need to take a photo of their face and start the control with one click using the terminal device. They can then control various home beauty devices to complete beauty work without the guidance of a beautician or any other external assistance, greatly improving the convenience of beauty operations for users.

[0041] Furthermore, in the actual implementation of the method corresponding to this embodiment, each home beauty device has its own ID number. When each home beauty device connects to the target user's terminal device via Bluetooth or WiFi, the target user's terminal device automatically identifies the model and ID number of each home beauty device. When the model and ID number of each home beauty device successfully matches the target beauty device's identification code, the matched home beauty device is identified as the target beauty device, thus achieving accurate identification and matching of each home beauty device. Each beauty mode's pre-design includes a certain beauty project preference; that is, each beauty mode pre-matches the functions of different home beauty devices to ensure that the corresponding beauty projects can be completed. Based on the emphasis on different beauty projects in each beauty mode, the working order of the devices in each beauty mode is sorted, thereby forming the target beauty device control priority. Through the target beauty device control priority, coordinated control of each home beauty device is achieved, avoiding the problem of device malfunction.

[0042] like Figure 2 As shown, the second aspect of this embodiment provides a hardware system for implementing the multi-device beauty mode rapid matching method based on intelligent skin analysis described in the first aspect of the embodiment, including: A facial image acquisition unit is used to acquire facial images of the target user; A facial skin feature extraction unit is used to perform image processing and feature extraction on the facial image to obtain facial skin feature data; The skin detection and analysis unit is used to acquire a pre-trained skin detection and analysis model, and to obtain the skin detection and analysis results of the target user based on the facial skin feature data and the skin detection and analysis model. The comprehensive skin scoring unit is used to obtain a preset multi-dimensional skin index ratio correspondence table, and to perform a comprehensive scoring calculation on the skin detection and analysis results based on the facial skin feature data, so as to obtain the comprehensive skin detection and analysis score result of the target user; The beauty mode matching unit is used to generate a beauty mode for the target user based on the comprehensive score result of the target user's skin detection analysis, and to receive user control instructions to control each home beauty device according to the target user's beauty mode.

[0043] The working process, working details and technical effects of the system provided in this embodiment can be found in the first aspect of the embodiment, and will not be repeated here.

[0044] like Figure 3As shown, the third aspect of this embodiment provides an electronic device, including: a memory, a processor, and a transceiver that are sequentially and communicatively connected, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the multi-device beauty mode fast matching method based on intelligent skin analysis as described in the first aspect of the embodiment.

[0045] For specific examples, the memory may include, but is not limited to, random access memory (RAM), read-only memory (ROM), flash memory, first-in-first-out (FIFO) memory, and / or first-in-last-out (FILO) memory, etc.; specifically, the processor may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor may be implemented using at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), PLA (Programmable Logic Array). The processor may also include a main processor and a coprocessor. The main processor, also known as the CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state.

[0046] In some embodiments, the processor may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. For example, the processor may not be limited to microprocessors of the STM32F105 series, reduced instruction set computer (RISC) microprocessors, x86 architecture processors, or processors with integrated neural network processing units (NPUs). The transceiver may be, but is not limited to, a Wi-Fi transceiver, a Bluetooth transceiver, a General Packet Radio Service (GPRS) transceiver, a ZigBee (a low-power LAN protocol based on the IEEE 802.15.4 standard) transceiver, a 3G transceiver, a 4G transceiver, and / or a 5G transceiver. Furthermore, the device may also include, but is not limited to, a power module, a display screen, and other necessary components.

[0047] The working process, working details and technical effects of the electronic device provided in this embodiment can be found in the first aspect of the embodiment, and will not be repeated here.

[0048] The fourth aspect of this embodiment provides a storage medium that stores instructions containing the multi-device beauty mode rapid matching method based on intelligent skin analysis as described in the first aspect of the embodiment. That is, the storage medium stores instructions that, when the instructions are run on a computer, execute the multi-device beauty mode rapid matching method based on intelligent skin analysis as described in the first aspect of the embodiment.

[0049] The storage medium refers to a carrier for storing data, which may include, but is not limited to, floppy disks, optical disks, hard disks, flash memory, USB flash drives and / or Memory Sticks, etc. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.

[0050] The working process, working details and technical effects of the storage medium provided in this embodiment can be found in the first aspect of the embodiment, and will not be repeated here.

[0051] The fifth aspect of this embodiment provides a computer program product containing instructions that, when executed on a computer, cause the computer to perform the multi-device beauty mode rapid matching method based on intelligent skin analysis as described in the first aspect of this embodiment, wherein the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0052] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for rapid matching of beauty modes across multiple devices based on intelligent skin analysis, characterized in that, include: Obtain the facial image of the target user; The facial image is processed and features are extracted to obtain facial skin feature data; A pre-trained skin detection and analysis model is obtained, and based on the facial skin feature data, the skin detection and analysis results of the target user are obtained through the skin detection and analysis model. Obtain a preset multi-dimensional skin index ratio correspondence table, and calculate a comprehensive score for the skin detection and analysis results based on the facial skin feature data to obtain the comprehensive skin detection and analysis score result for the target user; Based on the comprehensive score results of the target user's skin detection analysis, a beauty mode for the target user is generated, and user control instructions are received to control each home beauty device according to the target user's beauty mode.

2. The method for rapid matching of multi-device beauty modes based on intelligent skin analysis according to claim 1, characterized in that, Obtain facial images of the target user, including: Multiple initial facial images of the target user are obtained through the target user's terminal device; Select an initial facial image with a complete, unobstructed face and moderate brightness from multiple initial facial images as a pre-selected facial image; Obtain a preset facial angle standard, and determine the facial angle of the pre-selected facial image according to the facial angle standard, wherein the facial angle standard includes a frontal facial angle standard, a left facial angle standard, and a right facial angle standard; If the pre-selected facial image meets the frontal face angle standard, it is named the first frontal face image; if the pre-selected facial image meets the left face angle standard, it is named the second left face image; if the pre-selected facial image meets the right face angle standard, it is named the third right face image. The obtained first frontal image, second left facial image, and third right facial image are labeled according to the facial angle standard, and the labeled first frontal image, second left facial image, and third right facial image are integrated to form the facial image of the target user.

3. The method for rapid matching of multi-device beauty modes based on intelligent skin analysis according to claim 2, characterized in that, The facial image is processed and features are extracted to obtain facial skin feature data, including: The facial images are subjected to illumination equalization processing, and the first frontal image, the second left facial image, and the third right facial image are uniformly mapped to the standard frontal coordinate system by the facial key point detection method to obtain a three-dimensional facial model, wherein the three-dimensional facial model includes various facial key points. Based on the three-dimensional facial model, SIFT technology is used to align each facial key point, and the aligned facial key points are projected onto a two-dimensional plane to form a complete facial texture map of the target user. From the facial texture map of the target user, the texture map of the cheek area is extracted, and the saturation and brightness features of the texture map of the cheek area are identified to obtain the skin type parameters of the target user, wherein the skin type parameters of the target user include average skin saturation and average skin brightness. Obtain a preset skin type parameter threshold, compare the target user's skin type parameter with the skin type parameter threshold, determine the target user's skin type based on the comparison result, and use the target user's skin type as skin type data; From the facial texture map of the target user, the texture map of the wrinkle area is extracted, and the wrinkle density and wrinkle depth of the texture map of the wrinkle area are identified to obtain the wrinkle features of the target user, and the wrinkle features of the target user are used as wrinkle feature data. The target user's facial texture map is subjected to circular dark spot recognition to obtain multiple circular dark spots. Based on the diameter of each circular dark spot, the target user's pore density is calculated and used as pore feature data. Flaw identification is performed on the facial texture map of the target user to obtain multiple flaw feature points. Each flaw feature point is analyzed to obtain the flaw type and flaw location of each flaw feature point, and the flaw type and flaw location of each flaw feature point are used as flaw feature data. The skin type data, wrinkle feature data, pore feature data, and blemish feature data are integrated to form facial skin feature data.

4. The method for rapid matching of multi-device beauty modes based on intelligent skin analysis according to claim 1, characterized in that, The training process of the skin detection and analysis model includes: Acquire historical user facial skin feature data and historical user facial skin rating records. The historical user facial skin feature data includes historical user skin type data, historical user wrinkle feature data, historical user pore feature data, and historical user blemish feature data. The historical user facial skin rating records are percentage-based real scores for wrinkle features and blemish features of historical users for each different skin type. The historical user facial skin feature data is divided into historical user dry skin feature data, historical user oily skin feature data, and historical user combination skin feature data according to the historical user skin type data; Using the historical user dry skin feature data, the historical user oily skin feature data, and the historical user combination skin feature data as inputs, and the historical user facial skin score records as outputs, sub-models are trained to obtain dry skin detection and analysis sub-models, oily skin detection and analysis sub-models, and combination skin detection and analysis sub-models. The dry skin detection and analysis sub-model, the oily skin detection and analysis sub-model, and the combination skin detection and analysis sub-model are integrated into a skin detection and analysis model.

5. The method for rapid matching of multi-device beauty modes based on intelligent skin analysis according to claim 4, characterized in that, Based on the facial skin feature data, the skin detection and analysis results of the target user are obtained through the skin detection and analysis model, including: The facial skin feature data is input into the skin detection and analysis model, and the skin type data in the facial skin feature data is used to determine the target user's skin type, wherein the target user's skin type is dry skin, oily skin, or combination skin. Based on the target user's skin type, the dry skin detection and analysis sub-model, the oily skin detection and analysis sub-model, or the combination skin detection and analysis sub-model are selected as the target user's skin detection and analysis sub-model in the skin detection and analysis model. The facial skin feature data is input into the target user skin detection and analysis sub-model to obtain the target user's wrinkle score, target user's pore score, and target user's various types of blemish scores. The target user's skin type, wrinkle score, pore score, and blemish scores are then integrated to obtain the target user's skin detection and analysis results.

6. The method for rapid matching of multi-device beauty modes based on intelligent skin analysis according to claim 5, characterized in that, Obtain a preset multi-dimensional skin index ratio correspondence table, and calculate a comprehensive score for the skin detection and analysis results based on the facial skin feature data to obtain the target user's comprehensive skin detection and analysis score result, including: Obtain a preset multi-dimensional skin index ratio correspondence table, wherein the multi-dimensional skin index ratio correspondence table includes the index ratios of wrinkles, pores and various types of blemishes in each skin type, and the various types of blemishes include blackheads, acne and pigmentation. Based on the multi-dimensional skin index ratio correspondence table, the weights of wrinkles, pores and various types of blemishes in each skin type are calculated to obtain a multi-dimensional weight analysis table. Using the multi-dimensional weight analysis table, the skin detection analysis results of the target user are weighted to obtain the target user's wrinkle weight score, target user's pore weight score, and target user's weight score for each type of blemish. The target user's wrinkle-weighted score, pore-weighted score, and various types of blemish-weighted scores are summed to obtain the target user's comprehensive skin detection and analysis score. Correspondingly, after obtaining the comprehensive score result of the target user's skin detection and analysis, it also includes: Based on the target user's wrinkle weighted score, the target user's pore weighted score, the target user's weighted scores for each type of blemish, and the target user's comprehensive skin detection and analysis score, a target user skin detection and analysis report is generated. The target user's skin detection and analysis report is sent to the target user's terminal device for visualization.

7. The method for rapid matching of multi-device beauty modes based on intelligent skin analysis according to claim 1, characterized in that, Based on the comprehensive skin detection and analysis results of the target user, a beauty mode for the target user is generated, and user control commands are received to control various home beauty devices according to the target user's beauty mode, including: Obtain a preset beauty mode library, wherein the beauty mode library is used to record the correspondence between various beauty modes and the comprehensive score results of skin detection and analysis for each user; Based on the beauty mode library, a beauty mode corresponding to the comprehensive skin detection and analysis score of the target user is matched and used as the beauty mode for the target user. At least one home beauty device is selected as the target beauty device based on the target user's beauty mode. The home beauty device includes a radio frequency beauty device, an LED light therapy beauty mask, a microcurrent beauty device, an electroporation beauty device, an ultrasonic beauty device, and an iontophoresis device. Using the target user's terminal device, the target user's beauty mode is sent to each target beauty device via wireless communication, wherein the wireless communication includes Bluetooth communication and WiFi communication; Using the target user's terminal device, a beauty mode activation command is sent to each target beauty device. Based on the beauty mode activation command, each target beauty device is controlled to start, so as to execute the target user's beauty mode accordingly.

8. The method for rapid matching of multi-device beauty modes based on intelligent skin analysis according to claim 7, characterized in that, The target user beauty mode includes a target beauty device identification code and a target beauty device control priority. Furthermore, at least one home beauty device is selected as the target beauty device based on the target user beauty mode, including: By using the target user's terminal device, obtain the ID number of each home beauty device that is wirelessly connected to the target user's terminal device, and select the home beauty device whose ID number matches the target beauty device identification code in the target user's beauty mode as the target beauty device; Correspondingly, the execution of the target user's beauty mode includes: Upon receiving the beauty mode activation command, each target beauty device enters a pre-start state and sequentially starts up according to the target beauty device control priority in the target user beauty mode to execute the target user beauty mode.

9. A multi-device beauty mode rapid matching system based on intelligent skin analysis, used to implement the multi-device beauty mode rapid matching method based on intelligent skin analysis as described in any one of claims 1 to 8, characterized in that, include: A facial image acquisition unit is used to acquire facial images of the target user; A facial skin feature extraction unit is used to perform image processing and feature extraction on the facial image to obtain facial skin feature data; The skin detection and analysis unit is used to acquire a pre-trained skin detection and analysis model, and to obtain the skin detection and analysis results of the target user based on the facial skin feature data and the skin detection and analysis model. The comprehensive skin scoring unit is used to obtain a preset multi-dimensional skin index ratio correspondence table, and to perform a comprehensive scoring calculation on the skin detection and analysis results based on the facial skin feature data, so as to obtain the comprehensive skin detection and analysis score result of the target user; The beauty mode matching unit is used to generate a beauty mode for the target user based on the comprehensive score result of the target user's skin detection analysis, and to receive user control instructions to control each home beauty device according to the target user's beauty mode.

10. An electronic device, characterized in that, The device includes a memory, a processor, and a transceiver that are sequentially and communicatively connected. The memory is used to store computer programs, the transceiver is used to send and receive messages, and the processor is used to read the computer programs and execute the multi-device beauty mode fast matching method based on intelligent skin analysis as described in any one of claims 1 to 8.

Images