Skin state monitoring method based on Bluetooth data transmission and AI intelligent glasses

Abstract

The invention discloses a skin state monitoring method based on Bluetooth data transmission and AI intelligent glasses, which are applied to the AI intelligent glasses, and the AI intelligent glasses comprise a sensor and a Bluetooth module. The method comprises the following steps: acquiring a skin state parameter of a target object through the sensor; determining a target skin health assessment parameter of the target object according to the skin state parameter; and transmitting the target skin health assessment parameter to an electronic device through the Bluetooth module so as to display the target skin health assessment parameter through a display screen of the electronic device. According to the embodiment of the invention, skin monitoring can be realized through the AI intelligent glasses, so that the intelligence of the AI intelligent glasses is improved.

Description

Technical Field

[0001] The present application relates to the technical field of AI smart glasses, or the technical field of wearable devices, and specifically to a skin condition monitoring method based on Bluetooth data transmission and AI smart glasses. Background Art

[0002] AI smart glasses are called AI glasses or smart mirrors or smart glasses. As a wearable device, AI smart glasses are similar to smart phones and have an independent operating system. Based on an independent operating system, they can install various application software by themselves to realize corresponding software functions.

[0003] At present, AI smart glasses are unable to monitor user skin. Therefore, the problem of how to achieve skin monitoring through AI smart glasses needs to be solved urgently. Summary of the invention

[0004] The embodiments of the present application provide a skin condition monitoring method based on Bluetooth data transmission and AI smart glasses, which can realize skin monitoring through AI smart glasses and thus improve the intelligence of AI smart glasses.

[0005] In a first aspect, an embodiment of the present application provides a skin condition monitoring method based on Bluetooth data transmission, which is applied to AI smart glasses, wherein the AI ​​smart glasses include a sensor and a Bluetooth module; the method includes:

[0006] Acquiring skin condition parameters of the target object through the sensor;

[0007] Determining a target skin health assessment parameter of the target object according to the skin condition parameter;

[0008] The target skin health assessment parameter is transmitted to the electronic device through the Bluetooth module, so that the target skin health assessment parameter is displayed on the display screen of the electronic device.

[0009] In a second aspect, an embodiment of the present application provides a skin condition monitoring device based on Bluetooth data transmission, which is applied to AI smart glasses, wherein the AI ​​smart glasses include a sensor and a Bluetooth module; the device includes: an acquisition unit, a determination unit and an interaction unit, wherein:

[0010] The acquisition unit is used to acquire the skin condition parameters of the target object through the sensor;

[0011] The determining unit is used to determine the target skin health assessment parameter of the target object according to the skin state parameter;

[0012] The interaction unit is used to transmit the target skin health assessment parameter to the electronic device through the Bluetooth module, so that the target skin health assessment parameter is displayed on the display screen of the electronic device.

[0013] In a third aspect, an embodiment of the present application provides an AI smart glasses, comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the first aspect of the embodiment of the present application.

[0014] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps described in the first aspect of the embodiment of the present application.

[0015] In a fifth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in the first aspect of the embodiment of the present application. The computer program product may be a software installation package.

[0016] The implementation of the embodiments of the present application has the following beneficial effects:

[0017] It can be seen that the skin condition monitoring method based on Bluetooth data transmission and AI smart glasses described in the embodiments of the present application are applied to AI smart glasses, and the AI ​​smart glasses include a sensor and a Bluetooth module; the skin condition parameters of the target object are obtained through the sensor; the target skin health assessment parameters of the target object are determined according to the skin condition parameters; the target skin health assessment parameters are transmitted to the electronic device through the Bluetooth module, so as to display the target skin health assessment parameters through the display screen of the electronic device, so that skin monitoring can be achieved through AI smart glasses, thereby improving the intelligence of AI smart glasses. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 It is a flowchart of a skin condition monitoring method based on Bluetooth data transmission provided in an embodiment of the present application;

[0020] Figure 2 It is a structural schematic diagram of an AI smart glasses provided in an embodiment of the present application;

[0021] Figure 3 is a structural schematic diagram of another AI smart glasses provided in an embodiment of the present application;

[0022] Figure 4 This is a block diagram of the functional units of a skin condition monitoring device based on Bluetooth data transmission provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0024] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0025] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0026] In the embodiments of the present application, electronic devices may include: smart phones (such as Android phones, iOS phones, Windows Phone phones, etc.), PDAs, tablet computers, Bluetooth speakers, smart TVs, smart refrigerators, smart robots, driving recorders, laptop computers, mobile Internet devices (Mobile Internet Devices, MID) or wearable devices (such as AI smart glasses, smart bracelets, smart watches, Bluetooth headsets), etc. The above are only examples and not exhaustive, including but not limited to the above electronic devices. The electronic devices may also include servers, for example, cloud servers.

[0027] The following is a detailed description of the embodiments of the present application.

[0028] See also Figure 1 , Figure 1 1 is a flow chart of a skin condition monitoring method based on Bluetooth data transmission provided in an embodiment of the present application, which is applied to AI smart glasses, wherein the AI ​​smart glasses include a sensor and a Bluetooth module; as shown in the figure, the skin condition monitoring method based on Bluetooth data transmission includes:

[0029] 101. Obtain skin condition parameters of a target object through the sensor.

[0030] In the embodiment of the present application, the sensor may include one or more sensors, and the sensor may include at least one of the following: a camera, a temperature sensor, a humidity sensor, a material detection sensor, etc., which is not limited here.

[0031] The target object may include a user wearing AI smart glasses. In a specific implementation, Figure 2 As shown, the AI ​​smart glasses may include a sensor and a Bluetooth module, wherein the sensor may be used to detect the skin condition parameters of the target object, and the Bluetooth module may be used to communicate with the electronic device, for example, to transmit data. The AI ​​smart glasses may also include a prompt module and a display module.

[0032] In a specific implementation, the skin condition parameters of the target object may be acquired through sensors, and the skin condition parameters reflect the skin condition of the target object to a certain extent.

[0033] Optionally, the skin state parameter includes at least one of the following: skin temperature, skin humidity, skin roughness, skin nutrient components, skin refractive index, pore state parameter, blackhead state parameter.

[0034] In the embodiment of the present application, the skin state parameter includes at least one of the following: skin temperature, skin humidity, skin roughness, skin nutrients, skin refractive index, pore state parameter, blackhead state parameter, etc., which are not limited here. The pore state parameter may include at least one of the following: pore size, number of pores, pore depth, etc., which are not limited here. The blackhead state parameter may include at least one of the following: blackhead size, number of blackheads, blackhead color depth, etc., which are not limited here.

[0035] 102. Determine a target skin health assessment parameter of the target object according to the skin condition parameter.

[0036] In an embodiment of the present application, the skin state parameters reflect the skin condition of the target object to a certain extent. In a specific implementation, the mapping relationship between the preset skin state parameters and the skin health assessment parameters can be pre-stored, and then, the target skin health assessment parameters corresponding to the skin state parameters of the target object can be determined based on the mapping relationship. The target skin health assessment parameters reflect the skin health level to a certain extent.

[0037] Optionally, when the skin condition parameters include m parameters, m is an integer greater than 1; the above step 102, determining the target skin health assessment parameters of the target object according to the skin condition parameters, may include the following steps:

[0038] Acquire the first identity information of the target object;

[0039] Determine a first weight set corresponding to the first identity information, the first weight set including m weights, and the m weights correspond one-to-one to the m parameters;

[0040] The target skin health assessment parameter is determined according to the m parameters and the first weight set.

[0041] The first identity information may include at least one of the following: age, race, height, weight, physical condition, occupation, etc., which are not limited here.

[0042] In a specific implementation, when the skin state parameter includes m parameters, m is an integer greater than 1. Specifically, the first identity information of the target object can be obtained, and the mapping relationship between the preset identity information and the weight set can be pre-stored. The weight set can include m weights, and the m weights correspond to the m parameters one by one. Furthermore, the first weight set corresponding to the first identity information can be determined based on the mapping relationship. The first weight set includes m weights, and the m weights correspond to the m parameters one by one. The sum of the m weights is 1. A weighted operation is performed based on the m parameters and the first weight set to obtain the target skin health assessment parameters. The skin state parameters reflect the skin condition of the target object to a certain extent, that is, the skin condition of the target object can be deeply evaluated based on the identity information of the target object, which helps to improve the intelligence of AI smart glasses.

[0043] 103. Transmit the target skin health assessment parameter to an electronic device through the Bluetooth module, so that the target skin health assessment parameter is displayed on a display screen of the electronic device.

[0044] In an embodiment of the present application, Bluetooth communication can be performed between the AI ​​smart glasses and the electronic device. The target skin health assessment parameters can be transmitted to the electronic device through the Bluetooth module, so that the target skin health assessment parameters can be displayed through the display screen of the electronic device. In this way, the skin health status of the target object can be displayed to the target object.

[0045] For example, in the embodiment of the present application, AI smart glasses can be applied to the field of cosmetic instruments. By implanting sensors in AI smart glasses, the skin condition can be dynamically monitored. Specifically, the skin condition may include at least one of the following: temperature and humidity, roughness, nutrients, refractive index, pores, blackheads, etc. Next, after regular sampling and analysis by the algorithm, it is converted into skin health assessment parameters. Through wireless transmission, the skin health assessment parameters can be directly displayed on the mobile phone app. At the same time, the skin health assessment parameters are displayed on the screen of the AI ​​smart glasses, and sound and light reminders are set on the glasses to remind users of their skin health.

[0046] Optionally, the AI ​​smart glasses further include a display module, and may further include the following steps:

[0047] The target skin health assessment parameter is displayed through the display module.

[0048] In the embodiment of the present application, the AI ​​smart glasses may further include a display module, and the display module may include at least one of the following: a display screen, a projection module, etc., which is not limited here.

[0049] In the specific implementation, the target skin health assessment parameters are displayed through the display module, that is, the skin health status of the target object can be displayed through the display module of the AI ​​smart glasses, which helps to improve the intelligence of the AI ​​smart glasses.

[0050] Optionally, the AI ​​smart glasses further include a prompt module, and may further include the following steps:

[0051] When the target skin health assessment parameter does not meet the preset conditions, the prompt module is used to prompt the target object to perform skin care.

[0052] Among them, the AI ​​smart glasses may also include a prompt module, which may include at least one of the following: a display module, a voice module, an audio-visual module, a vibration module, etc., which are not limited here.

[0053] The preset condition may be preset or set by the system by default. For example, when the target skin health assessment parameter is within the preset range, it means that the target skin health assessment parameter does not meet the preset condition. Conversely, when the target skin health assessment parameter is not within the preset range, it means that the target skin health assessment parameter meets the preset condition.

[0054] In a specific implementation, the preset range may be preset or set by system default. The preset range may be related to at least one of the following factors, which may include at least one of the following: weather, geographical location, ambient light brightness, etc., which are not limited here.

[0055] Optionally, when the skin condition parameter includes skin roughness and the sensor includes an imaging device, the above step 102 of acquiring the skin condition parameter of the target object through the sensor may include the following steps:

[0056] photographing the target object by means of the imaging device to obtain a first image;

[0057] Extracting a skin area image of a preset size from the first image to obtain a second image;

[0058] performing image enhancement on the second image to obtain a third image;

[0059] Performing multi-scale decomposition on the third image to obtain a high-frequency component;

[0060] Determining a first energy value of the high frequency component portion;

[0061] determining a second energy value of the third image;

[0062] Perform feature extraction on the high-frequency component according to the first energy value and the second energy value to obtain target feature parameters;

[0063] The skin roughness is determined according to the target characteristic parameter.

[0064] The imaging device may include at least one of the following: an ultrasonic sensor, a camera, etc., which are not limited here.

[0065] The preset size may be preset or set by system default.

[0066] In a specific implementation, when the skin condition parameters include skin roughness and the sensor includes an imaging device, the target object can be photographed by the imaging device to obtain a first image, and then a skin area image of a preset size in the first image is extracted to obtain a second image. The preset size can ensure that the skin area is large enough, thereby ensuring the accuracy of skin roughness detection.

[0067] The target feature parameters may include at least one of the following: feature points, feature textures, feature vectors, etc., which are not limited here.

[0068] Further, the second image can be enhanced to obtain a third image, so that the quality of the skin area image can be improved, thereby ensuring the accuracy of skin roughness detection. Multi-scale decomposition can include at least one of the following: contourlet transform, wavelet transform, Gaussian pyramid transform, ridgelet transform, etc., which are not limited here. Since the high-frequency component part reflects the detailed features of the image, and the detailed features of the image are closely related to the skin roughness, the third image can be multi-scale decomposed to obtain the high-frequency component part, and then the first energy value of the high-frequency component part is determined, and the second energy value of the third image is determined. The high-frequency component part is feature extracted according to the first energy value and the second energy value to obtain the target feature parameter. Since the image includes a low-frequency component part and a high-frequency component part, the low-frequency component part reflects the main body of the image, and the first energy value and the second energy value reflect the correlation between the main body of the image and the detailed features of the image. Therefore, the high-frequency component part can be feature extracted based on the correlation between the main body of the image and the detailed features of the image to obtain the target feature parameter. In this way, it can be ensured that the feature parameter depth conforms to the characteristics of the image itself, so that the target feature parameter can accurately determine the skin roughness.

[0069] In a specific implementation, the mapping relationship between the preset feature parameters and the skin roughness can be pre-stored, and then the skin roughness corresponding to the target feature parameters can be determined based on the mapping relationship. In this way, since the feature parameter depth is guaranteed to conform to the characteristics of the image itself, the target feature parameter can accurately determine the skin roughness.

[0070] Optionally, the above step of extracting features of the high-frequency component according to the first energy value and the second energy value to obtain target feature parameters may include the following steps:

[0071] determining a first energy ratio between the first energy value and the second energy value;

[0072] determining a first image feature extraction algorithm corresponding to the first energy ratio;

[0073] Obtaining initial algorithm control parameters corresponding to the first image feature extraction algorithm;

[0074] Determining a first signal-to-noise ratio of the high frequency component portion;

[0075] determining a first adjustment parameter corresponding to the first signal-to-noise ratio;

[0076] Determine a first algorithm control parameter according to the initial algorithm control parameter and the first adjustment parameter;

[0077] The high frequency component is subjected to feature extraction according to the first algorithm control parameter and the first image feature extraction algorithm to obtain the target feature parameter.

[0078] In a specific implementation, a first energy ratio between the first energy value and the second energy value may be determined, where the first energy ratio=first energy value / second energy value. The first energy ratio reflects the correlation between the image subject and the detail features of the image.

[0079] Specifically, the mapping relationship between the preset energy ratio and the image feature extraction algorithm can be pre-stored, and then the first image feature extraction algorithm corresponding to the first energy ratio can be determined based on the mapping relationship, wherein the image feature extraction algorithm can be understood as an algorithm for implementing feature extraction. The initial algorithm control parameters corresponding to the first image feature extraction algorithm can also be obtained, and the initial algorithm control parameters can be used to implement at least one of the following functions: controlling the algorithm speed of the first image feature extraction algorithm, controlling the number of feature extractions of the first image feature extraction algorithm, controlling the degree of feature extraction of the first image feature extraction algorithm, controlling the number of feature extraction layers of the first image feature extraction algorithm, controlling the feature type of feature extraction of the first image feature extraction algorithm, etc., which are not limited here.

[0080] In an embodiment of the present application, a first signal-to-noise ratio of the high-frequency component part can be determined, and the first signal-to-noise ratio reflects the degree of high interference of the high-frequency component part, that is, a mapping relationship between a preset signal-to-noise ratio and an adjustment parameter can be pre-stored, and then, a first adjustment parameter corresponding to the first signal-to-noise ratio can be determined based on the mapping relationship, that is, an adjustment parameter corresponding to the interference of the high-frequency component part can be obtained, which helps to improve the anti-interference performance of the first image feature extraction algorithm and improve the accuracy of feature extraction.

[0081] In a specific implementation, the first algorithm control parameter can be determined according to the initial algorithm control parameter and the first adjustment parameter, that is, the first algorithm control parameter = (1 + first adjustment parameter) * initial algorithm control parameter. Next, the high-frequency component is feature extracted according to the first algorithm control parameter and the first image feature extraction algorithm to obtain the target feature parameter. This can not only adapt the corresponding image feature extraction algorithm based on the correlation between the image subject and the detailed features of the image, but also improve the anti-interference performance of the first image feature extraction algorithm and the accuracy of feature extraction. Furthermore, the accuracy of the skin state parameters can be guaranteed, thereby ensuring the intelligence of the AI ​​smart glasses.

[0082] Optionally, the above step of performing image enhancement on the second image to obtain the third image may include the following steps:

[0083] identifying a first skin color parameter of the target object according to the second image;

[0084] determining a first image enhancement algorithm corresponding to the first skin color parameter;

[0085] dividing the second image into a plurality of regions;

[0086] Determine the number of feature points in each of the multiple regions to obtain multiple numbers of feature points;

[0087] Determine the feature point distribution density of each of the multiple regions according to the number of the multiple feature points to obtain multiple feature point distribution densities;

[0088] Determine a first standard deviation and a first mean of the distribution density of the plurality of feature points;

[0089] determining an initial control parameter of the first image enhancement algorithm corresponding to the first mean value;

[0090] determining a first feedback adjustment parameter corresponding to the first standard deviation;

[0091] Determining a target control parameter according to the initial control parameter and the first feedback adjustment parameter;

[0092] The second image is enhanced according to the first image enhancement algorithm and the target control parameter to obtain the third image.

[0093] In a specific implementation, since images can identify skin color to a certain extent, the first skin color parameters of the target object can be identified based on the second image. Different skin colors are adapted to different image enhancement algorithms. The mapping relationship between preset skin color parameters and image enhancement algorithms can be pre-stored, and then, the first image enhancement algorithm corresponding to the first skin color parameters can be determined based on the mapping relationship. In this way, an image enhancement algorithm adapted to the skin color of the target object can be obtained.

[0094] Next, due to the individuality of different regions and the certain correlation between regions, on the basis of considering the regional individuality and regional correlation of image enhancement, in order to ensure the overall and smooth image enhancement effect, the second image can also be divided into multiple regions, and the number of feature points in each of the multiple regions is determined to obtain multiple numbers of feature points, and then the feature point distribution density of each region in the multiple regions is determined based on the multiple numbers of feature points to obtain multiple feature point distribution densities, and the feature point distribution density of each region is the ratio between the number of feature points in the region and the regional area.

[0095] Next, the standard deviation operation can be performed on the distribution densities of multiple feature points to obtain a first standard deviation. Accordingly, the distribution densities of multiple feature points can be averaged to obtain a first mean. The first standard deviation reflects the degree of fluctuation between regions, and the first mean reflects the overall details of the region. Therefore, the mapping relationship between the preset mean and the initial control parameters of the first image enhancement algorithm can be pre-stored, and then, the initial control parameters of the first image enhancement algorithm corresponding to the first mean can be determined based on the mapping relationship. In this way, the control parameters corresponding to the overall details of the region can be obtained.

[0096] Among them, the control parameters of the first image enhancement algorithm can be used to achieve at least one of the following functions: controlling the algorithm speed of the first image enhancement algorithm, controlling the image enhancement degree of the first image enhancement algorithm, controlling the area of ​​the first image enhancement algorithm, etc., which are not limited here.

[0097] In a specific implementation, a mapping relationship between a preset standard deviation and a feedback adjustment parameter can be pre-stored, and then a first feedback adjustment parameter corresponding to the first standard deviation can be determined based on the mapping relationship, and then a target control parameter can be determined according to the initial control parameter and the first feedback adjustment parameter, the target control parameter = initial control parameter * (1 + first feedback adjustment parameter), and then the second image is enhanced according to the first image enhancement algorithm and the target control parameter to obtain a third image. On the one hand, an image enhancement algorithm adapted to the skin color of the target object can be obtained, and on the other hand, considering the regional individuality and regional correlation of the image enhancement, in order to ensure the overall and smooth image enhancement effect, control parameters corresponding to the overall details of the region can be obtained, and control parameters can be dynamically optimized based on the degree of fluctuation between regions, so that the final control parameters ensure smooth image enhancement, which helps to ensure the accuracy of subsequent feature extraction, and then the accuracy of the skin state parameters can be guaranteed, thereby ensuring the intelligence of the AI ​​smart glasses.

[0098] It can be seen that the skin condition monitoring method based on Bluetooth data transmission described in the embodiment of the present application is applied to AI smart glasses, and the AI ​​smart glasses include a sensor and a Bluetooth module; the skin condition parameters of the target object are obtained through the sensor; the target skin health assessment parameters of the target object are determined according to the skin condition parameters; the target skin health assessment parameters are transmitted to the electronic device through the Bluetooth module, so as to display the target skin health assessment parameters through the display screen of the electronic device, so that skin monitoring can be realized through AI smart glasses, thereby improving the intelligence of AI smart glasses.

[0099] In accordance with the above embodiment, please refer to Figure 3 , Figure 3 : is a structural schematic diagram of another AI smart glasses provided in an embodiment of the present application. As shown in the figure, the AI ​​smart glasses include a processor, a memory, a communication interface and one or more programs. The one or more programs are stored in the memory and are configured to be executed by the processor. In the embodiment of the present application, the AI ​​smart glasses also include a sensor and a Bluetooth module; the program includes instructions for executing the following steps:

[0100] Acquiring skin condition parameters of the target object through the sensor;

[0101] Determining a target skin health assessment parameter of the target object according to the skin condition parameter;

[0102] The target skin health assessment parameter is transmitted to the electronic device through the Bluetooth module, so that the target skin health assessment parameter is displayed on the display screen of the electronic device.

[0103] Optionally, the skin state parameter includes at least one of the following: skin temperature, skin humidity, skin roughness, skin nutrient components, skin refractive index, pore state parameter, blackhead state parameter.

[0104] Optionally, the AI ​​smart glasses further include a display module, and the above program further includes instructions for executing the following steps:

[0105] The target skin health assessment parameter is displayed through the display module.

[0106] Optionally, the AI ​​smart glasses further include a prompt module, and the above program further includes instructions for executing the following steps:

[0107] When the target skin health assessment parameter does not meet the preset conditions, the prompt module is used to prompt the target object to perform skin care.

[0108] Optionally, when the skin condition parameters include m parameters, m is an integer greater than 1; in determining the target skin health assessment parameters of the target object according to the skin condition parameters, the program includes instructions for performing the following steps:

[0109] Acquire the first identity information of the target object;

[0110] Determine a first weight set corresponding to the first identity information, the first weight set including m weights, and the m weights correspond one-to-one to the m parameters;

[0111] The target skin health assessment parameter is determined according to the m parameters and the first weight set.

[0112] Optionally, when the skin condition parameter includes skin roughness and the sensor includes an imaging device, in acquiring the skin condition parameter of the target object through the sensor, the program includes instructions for performing the following steps:

[0113] photographing the target object by means of the imaging device to obtain a first image;

[0114] Extracting a skin area image of a preset size from the first image to obtain a second image;

[0115] performing image enhancement on the second image to obtain a third image;

[0116] Performing multi-scale decomposition on the third image to obtain a high-frequency component;

[0117] Determining a first energy value of the high frequency component portion;

[0118] determining a second energy value of the third image;

[0119] Perform feature extraction on the high-frequency component according to the first energy value and the second energy value to obtain target feature parameters;

[0120] The skin roughness is determined according to the target characteristic parameter.

[0121] Optionally, in the aspect of extracting features of the high-frequency component according to the first energy value and the second energy value to obtain target feature parameters, the program includes instructions for executing the following steps:

[0122] determining a first energy ratio between the first energy value and the second energy value;

[0123] determining a first image feature extraction algorithm corresponding to the first energy ratio;

[0124] Obtaining initial algorithm control parameters corresponding to the first image feature extraction algorithm;

[0125] Determining a first signal-to-noise ratio of the high frequency component portion;

[0126] determining a first adjustment parameter corresponding to the first signal-to-noise ratio;

[0127] Determine a first algorithm control parameter according to the initial algorithm control parameter and the first adjustment parameter;

[0128] The high frequency component is subjected to feature extraction according to the first algorithm control parameter and the first image feature extraction algorithm to obtain the target feature parameter.

[0129] Optionally, in terms of performing image enhancement on the second image to obtain a third image, the program includes instructions for executing the following steps:

[0130] identifying a first skin color parameter of the target object according to the second image;

[0131] determining a first image enhancement algorithm corresponding to the first skin color parameter;

[0132] dividing the second image into a plurality of regions;

[0133] Determine the number of feature points in each of the multiple regions to obtain multiple numbers of feature points;

[0134] Determine the feature point distribution density of each of the multiple regions according to the number of the multiple feature points to obtain multiple feature point distribution densities;

[0135] Determine a first standard deviation and a first mean of the distribution density of the plurality of feature points;

[0136] determining an initial control parameter of the first image enhancement algorithm corresponding to the first mean value;

[0137] determining a first feedback adjustment parameter corresponding to the first standard deviation;

[0138] Determining a target control parameter according to the initial control parameter and the first feedback adjustment parameter;

[0139] The second image is enhanced according to the first image enhancement algorithm and the target control parameter to obtain the third image.

[0140] It can be seen that the AI ​​smart glasses described in the embodiments of the present application include a sensor and a Bluetooth module; the skin state parameters of the target object are obtained through the sensor; the target skin health assessment parameters of the target object are determined according to the skin state parameters; the target skin health assessment parameters are transmitted to the electronic device through the Bluetooth module, so as to display the target skin health assessment parameters through the display screen of the electronic device. Skin monitoring can be achieved through AI smart glasses, thereby improving the intelligence of AI smart glasses.

[0141] Figure 4 This is a functional unit block diagram of a skin condition monitoring device 400 based on Bluetooth data transmission involved in an embodiment of the present application. The skin condition monitoring device 400 based on Bluetooth data transmission is applied to AI smart glasses, and the AI ​​smart glasses include a sensor and a Bluetooth module; the skin condition monitoring device 400 based on Bluetooth data transmission includes: an acquisition unit 401, a determination unit 402 and an interaction unit 403, wherein:

[0142] The acquisition unit 401 is used to acquire the skin condition parameters of the target object through the sensor;

[0143] The determining unit 402 is used to determine the target skin health assessment parameter of the target object according to the skin state parameter;

[0144] The interaction unit 403 is used to transmit the target skin health assessment parameter to the electronic device through the Bluetooth module, so that the target skin health assessment parameter is displayed on the display screen of the electronic device.

[0145] Optionally, the skin state parameter includes at least one of the following: skin temperature, skin humidity, skin roughness, skin nutrient components, skin refractive index, pore state parameter, blackhead state parameter.

[0146] Optionally, the AI ​​smart glasses further include a display module, and the above program further includes instructions for executing the following steps:

[0147] The target skin health assessment parameter is displayed through the display module.

[0148] Optionally, the AI ​​smart glasses further include a prompt module, and the skin condition monitoring device 400 based on Bluetooth data transmission is specifically used for:

[0149] When the target skin health assessment parameter does not meet the preset conditions, the prompt module is used to prompt the target object to perform skin care.

[0150] Optionally, when the skin state parameter includes m parameters, m is an integer greater than 1; in determining the target skin health assessment parameter of the target object according to the skin state parameter, the determining unit 402 is specifically used to:

[0151] Acquire the first identity information of the target object;

[0152] Determine a first weight set corresponding to the first identity information, the first weight set including m weights, and the m weights correspond one-to-one to the m parameters;

[0153] The target skin health assessment parameter is determined according to the m parameters and the first weight set.

[0154] Optionally, when the skin condition parameter includes skin roughness and the sensor includes an imaging device, in acquiring the skin condition parameter of the target object through the sensor, the acquiring unit 401 is specifically configured to:

[0155] photographing the target object by means of the imaging device to obtain a first image;

[0156] Extracting a skin area image of a preset size from the first image to obtain a second image;

[0157] performing image enhancement on the second image to obtain a third image;

[0158] Performing multi-scale decomposition on the third image to obtain a high-frequency component;

[0159] Determining a first energy value of the high frequency component portion;

[0160] determining a second energy value of the third image;

[0161] Perform feature extraction on the high-frequency component according to the first energy value and the second energy value to obtain target feature parameters;

[0162] The skin roughness is determined according to the target characteristic parameter.

[0163] Optionally, in the aspect of extracting features of the high-frequency component according to the first energy value and the second energy value to obtain target feature parameters, the acquiring unit 401 is specifically used to:

[0164] determining a first energy ratio between the first energy value and the second energy value;

[0165] determining a first image feature extraction algorithm corresponding to the first energy ratio;

[0166] Obtaining initial algorithm control parameters corresponding to the first image feature extraction algorithm;

[0167] Determining a first signal-to-noise ratio of the high frequency component portion;

[0168] determining a first adjustment parameter corresponding to the first signal-to-noise ratio;

[0169] Determine a first algorithm control parameter according to the initial algorithm control parameter and the first adjustment parameter;

[0170] The high frequency component is subjected to feature extraction according to the first algorithm control parameter and the first image feature extraction algorithm to obtain the target feature parameter.

[0171] Optionally, in terms of performing image enhancement on the second image to obtain the third image, the acquisition unit 401 is specifically configured to:

[0172] identifying a first skin color parameter of the target object according to the second image;

[0173] determining a first image enhancement algorithm corresponding to the first skin color parameter;

[0174] dividing the second image into a plurality of regions;

[0175] Determine the number of feature points in each of the multiple regions to obtain multiple numbers of feature points;

[0176] Determine the feature point distribution density of each of the multiple regions according to the number of the multiple feature points to obtain multiple feature point distribution densities;

[0177] Determine a first standard deviation and a first mean of the distribution density of the plurality of feature points;

[0178] determining an initial control parameter of the first image enhancement algorithm corresponding to the first mean value;

[0179] determining a first feedback adjustment parameter corresponding to the first standard deviation;

[0180] Determining a target control parameter according to the initial control parameter and the first feedback adjustment parameter;

[0181] The second image is enhanced according to the first image enhancement algorithm and the target control parameter to obtain the third image.

[0182] It can be seen that the skin condition monitoring device based on Bluetooth data transmission described in the embodiment of the present application is applied to AI smart glasses, and the AI ​​smart glasses include a sensor and a Bluetooth module; the skin condition parameters of the target object are obtained through the sensor; the target skin health assessment parameters of the target object are determined according to the skin condition parameters; the target skin health assessment parameters are transmitted to the electronic device through the Bluetooth module, so as to display the target skin health assessment parameters through the display screen of the electronic device, so that skin monitoring can be achieved through AI smart glasses, thereby improving the intelligence of AI smart glasses.

[0183] It can be understood that the functions of each program module of the skin condition monitoring device based on Bluetooth data transmission in this embodiment can be specifically implemented according to the method in the above method embodiment, and its specific implementation process can refer to the relevant description of the above method embodiment, which will not be repeated here.

[0184] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any method recorded in the above method embodiments.

[0185] The present application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps of any method described in the above method embodiment. The computer program product may be a software installation package.

[0186] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0187] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0188] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the above-mentioned units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0189] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0190] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0191] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the above-mentioned methods of each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or CD-ROM and other media that can store program codes.

[0192] A person skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (English: Read-Only Memory, abbreviated as: ROM), a random access memory (English: Random Access Memory, abbreviated as: RAM), a magnetic disk or an optical disk, etc.

[0193] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A skin condition monitoring method based on Bluetooth data transmission, characterized in that: Applied to AI smart glasses, the AI ​​smart glasses include a sensor and a Bluetooth module; the method includes: Acquiring skin condition parameters of the target object through the sensor; Determining a target skin health assessment parameter of the target object according to the skin condition parameter; The target skin health assessment parameter is transmitted to the electronic device through the Bluetooth module, so that the target skin health assessment parameter is displayed on the display screen of the electronic device.

2. The method according to claim 1, characterized in that The skin condition parameters include at least one of the following: skin temperature, skin humidity, skin roughness, skin nutrient components, skin refractive index, pore condition parameters, and blackhead condition parameters.

3. The method according to claim 1 or 2, characterized in that: The AI ​​smart glasses further include a display module, and the method further includes: The target skin health assessment parameter is displayed through the display module.

4. The method according to claim 1 or 2, characterized in that: The AI ​​smart glasses further include a prompt module, and the method further includes: When the target skin health assessment parameter does not meet the preset conditions, the prompt module is used to give a prompt to prompt the target object to perform skin care.

5. The method according to claim 1 or 2, characterized in that: When the skin state parameters include m parameters, m is an integer greater than 1; determining the target skin health assessment parameters of the target object according to the skin state parameters includes: Acquire the first identity information of the target object; Determine a first weight set corresponding to the first identity information, the first weight set including m weights, and the m weights correspond one-to-one to the m parameters; The target skin health assessment parameter is determined according to the m parameters and the first weight set.

6. The method according to claim 2, characterized in that When the skin condition parameter includes skin roughness and the sensor includes an imaging device, acquiring the skin condition parameter of the target object through the sensor includes: photographing the target object by means of the imaging device to obtain a first image; Extracting a skin area image of a preset size from the first image to obtain a second image; performing image enhancement on the second image to obtain a third image; Performing multi-scale decomposition on the third image to obtain a high-frequency component; Determining a first energy value of the high frequency component portion; determining a second energy value of the third image; Perform feature extraction on the high-frequency component according to the first energy value and the second energy value to obtain target feature parameters; The skin roughness is determined according to the target characteristic parameter.

7. The method according to claim 6, characterized in that The step of extracting features from the high frequency component according to the first energy value and the second energy value to obtain target feature parameters includes: determining a first energy ratio between the first energy value and the second energy value; determining a first image feature extraction algorithm corresponding to the first energy ratio; Obtaining initial algorithm control parameters corresponding to the first image feature extraction algorithm; Determining a first signal-to-noise ratio of the high frequency component portion; determining a first adjustment parameter corresponding to the first signal-to-noise ratio; Determine a first algorithm control parameter according to the initial algorithm control parameter and the first adjustment parameter; The high frequency component is subjected to feature extraction according to the first algorithm control parameter and the first image feature extraction algorithm to obtain the target feature parameter.

8. A skin condition monitoring device based on Bluetooth data transmission, characterized in that: Applied to AI smart glasses, the AI ​​smart glasses include a sensor and a Bluetooth module; the device includes: an acquisition unit, a determination unit and an interaction unit, wherein: The acquisition unit is used to acquire the skin condition parameters of the target object through the sensor; The determining unit is used to determine the target skin health assessment parameter of the target object according to the skin state parameter; The interaction unit is used to transmit the target skin health assessment parameter to the electronic device through the Bluetooth module, so that the target skin health assessment parameter is displayed on the display screen of the electronic device.

9. The device according to claim 8, characterized in that The skin condition parameters include at least one of the following: skin temperature, skin humidity, skin roughness, skin nutrient components, skin refractive index, pore condition parameters, and blackhead condition parameters.

10. An AI smart glasses, characterized in that: The method comprises a processor and a memory, wherein the memory is used to store one or more programs and is configured to be executed by the processor, wherein the programs include instructions for executing the steps in the method according to any one of claims 1 to 7.

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