Method for intelligently identifying hair removal success rate of hair removal instrument

Abstract

This invention relates to the field of intelligent hair removal rate recognition, specifically to a method for intelligently recognizing the success rate of hair removal devices. The real-time monitoring component includes an image scanning module and an image display module. The image scanning module can transmit scanned image information to the image display module. It also includes an image capturing module and an image processing module. The image capturing module can take multiple photos of the area scanned by the image scanning module. The image processing module can classify the photos of the same area recorded by the image capturing module at different times. This method for intelligently recognizing the success rate of hair removal devices has the advantages of being able to monitor the hair removal area in real time for easy observation by the user and being able to classify and label areas that have not been thoroughly cleaned.

Description

Technical Field

[0001] This invention relates to the field of intelligent hair removal rate recognition, specifically to a method for intelligently recognizing the success rate of hair removal devices. Background Technology

[0002] Users can only visually assess the hair removal effect when using a hair removal device. However, the human eye cannot detect fine hairs or hair follicles with residual hair roots. Furthermore, the human eye is limited by the body and cannot observe hair in certain special areas of the body, making it impossible to see the hair removal effect clearly. This can lead to repeated hair growth in areas that have not been thoroughly cleaned, resulting in poor hair removal results. Summary of the Invention

[0003] (I) Technical problems to be solved To overcome the shortcomings of existing technologies, a method for intelligently identifying the success rate of hair removal devices is proposed. This method has the function of real-time monitoring of the hair removal area for easy observation by the user, and can classify and label areas that have not been thoroughly cleaned, which can greatly improve the hair removal effect.

[0004] (II) Technical Solution This invention is achieved through the following technical solution: This invention proposes a method for intelligently identifying the success rate of hair removal devices, including a real-time monitoring component for real-time monitoring of hair removal effects and a laser hair removal module for performing hair removal on the user. The real-time monitoring component includes an image scanning module for scanning images of the user's skin surface while the hair removal process is underway, and an image display module for displaying the images scanned by the image scanning module in real time. The image scanning module can transmit the scanned image information to the image display module while scanning the user's skin. The image capturing module can take multiple photos of the area scanned by the image scanning module to facilitate the user's later observation and comparison of the hair removal effect of the laser hair removal module. The image processing module can classify the photos of the same area at different times recorded by the image capturing module.

[0005] Furthermore, it also includes an intelligent recognition module for dividing multiple sets of photos captured by the image capturing module into regions and judging the hair removal effect based on the color depth of each region. The intelligent recognition module can divide the photos recorded by the image capturing module into multiple regions and judge the image color of each region.

[0006] Furthermore, it also includes a classification and labeling module for classifying and labeling different regions after the intelligent recognition module has completed the color determination of each region. The classification and labeling module can classify and label different determination regions after the intelligent recognition module has completed the color determination of the image.

[0007] Furthermore, the classification and labeling module can label different areas with different indicator colors, making it easier for users to identify them visually.

[0008] Furthermore, the image scanning module is mounted on one side of the laser hair removal module, which allows the laser hair removal module to scan and obtain real-time image information of the hair removal effect while performing hair removal.

[0009] (III) Beneficial Effects Compared with the prior art, the present invention has the following advantages: The present invention mentions a method for intelligently identifying the success rate of hair removal devices. By setting up an image scanning module and an image display module, the laser hair removal module can monitor the hair removal area in real time during the laser hair removal process, making it easier to observe the actual hair removal effect. By setting up intelligent recognition and classification labeling modules, areas that have not been thoroughly cleaned can be classified and labeled, making the secondary hair removal operation more targeted and improving the hair removal effect. Attached Figure Description

[0010] Figure 1 This is a schematic diagram of the operating logic of the present invention.

[0011] Figure 2 This is a schematic diagram of hair density scanning according to the present invention. Detailed Implementation

[0012] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0013] like Figure 1 The method shown is a smart method for recognizing the success rate of hair removal devices, such as... Figure 1 As shown, the real-time monitoring component includes an image scanning module and an image display module. The image scanning module can transmit the scanned image information to the image display module. The image capturing module can take multiple photos of the area scanned by the image scanning module. The image processing module can classify the photos of the same area at different times recorded by the image capturing module.

[0014] In some embodiments, the intelligent recognition module can divide the photo recorded by the image capturing module into multiple regions, and perform image color determination on each region to determine the hair removal effect of different regions.

[0015] In some embodiments, the classification and labeling module can perform classification and labeling after the intelligent recognition module completes the image color determination, and label the hair removal effect in different areas separately.

[0016] In some embodiments, the classification and labeling module can label different areas with different prompt colors to facilitate visual identification by users.

[0017] In some embodiments, the image scanning module is mounted on one side of the laser hair removal module, so that while the laser hair removal module is working, the image scanning module can scan real-time images of the user's skin.

[0018] The present invention mentions a method for intelligently identifying the success rate of hair removal devices, which, in practical use, such as... Figure 1 As shown, firstly, the image scanning module and image display module in the real-time monitoring component are opened respectively. Then, while the laser hair removal module is performing hair removal, the scanning function of the image scanning module is used to transmit the image to the image display module. In this way, the operator can observe the hair removal process and the hair removal effect in real time during the hair removal operation. The image capturing module will take pictures before and after the laser hair removal module performs hair removal to facilitate comparison of the actual effect before and after the hair removal operation. The photos captured by the image capture module for before-and-after comparison can be divided into multiple regions for more detailed comparison through the intelligent recognition module. The effect of hair removal can be determined based on the color depth of each region. After the intelligent recognition module completes the image color determination, it can also be classified and labeled again through the classification and labeling module, so that users can perform secondary hair removal operations in a targeted manner according to the actual situation. The classification and labeling module can label different areas with different prompt colors, and different prompt colors indicate different hair removal effects, making it easy for users to identify.

[0019] It should be noted that after a systematic study, such as Figure 1 In addition to the hair removal procedure shown, there is another set of procedures, such as... Figure 2 The hair density scan shown can identify and classify hair in the skin before hair removal, making it easier to perform targeted hair removal later. It can also scan again after a hair removal operation to find hair that has not been removed, making it easier to perform targeted secondary hair removal in that area later.

[0020] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the concept and scope of the present invention. Various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the inventive concept should fall within the protection scope of the present invention. All technical contents for which protection is sought in this invention are fully described in the claims.

Claims

1. A method for intelligently identifying the success rate of hair removal using a hair removal device, comprising a real-time monitoring component and a laser hair removal module, characterized in that, The real-time monitoring component includes an image scanning module and an image display module. The image scanning module can transmit scanned image information to the image display module. It also includes an image capturing module and an image processing module. The image capturing module can take multiple photos of the area scanned by the image scanning module. The image processing module can classify the photos of the same area recorded by the image capturing module at different times.

2. The method for intelligently identifying the success rate of hair removal using a hair removal device according to claim 1, characterized in that: It also includes an intelligent recognition module, which can divide the photo recorded by the image capturing module into multiple regions and determine the image color of each region.

3. The method for intelligently identifying the success rate of hair removal using a hair removal device according to claim 2, characterized in that: It also includes a classification and labeling module, which can perform classification and labeling after the intelligent recognition module completes the image color determination.

4. The method for intelligently identifying the success rate of hair removal using a hair removal device according to claim 3, characterized in that: The classification and labeling module can label different areas with different prompt colors.

5. The method for intelligently identifying the success rate of hair removal using a hair removal device according to claim 1, characterized in that: The image scanning module is mounted on one side of the laser hair removal module.

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