Control method of epilating device, epilating device, computer readable storage medium and computer program product

Abstract

The application relates to a control method of an epilating device, the epilating device, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring a first image of an epilating area; identifying image information based on the first image, wherein the image information comprises hair density and hair curl degree; in the case that the image information comprises the hair curl degree, identifying the image information based on the first image, comprising: identifying a first distance and a first curvature of each hair based on the first image; the first distance is the distance between the hair root and the hair tip, and the first curvature is the curvature corresponding to the maximum arc of the hair; determining the hair curl degree based on the first distance and the first curvature; determining the light shielding area of the hair based on the image information; and determining a control parameter based on the light shielding area, wherein the control parameter is used for controlling the operation of the epilating device. The control parameter of the epilating device is determined through the light shielding area, so that the epilating effect can be improved within the scope of ensuring the safety of epilation.

Description

Technical Field

[0001] This application relates to the field of laser control technology, and in particular to a control method for a hair removal device, a hair removal device, a computer-readable storage medium, and a computer program product. Background Technology

[0002] Optical hair removal technology, especially hair removal devices based on the principle of selective photothermolysis using intense pulsed light (IPL) or lasers, has become one of the mainstream hair removal methods. This technology utilizes the selective absorption of light energy of specific wavelengths by melanin in the hair follicles, converting it into heat energy, thereby destroying the hair follicle structure and inhibiting hair regrowth.

[0003] Traditional hair removal devices typically require users to manually select an energy level or have the device set an energy level based on skin tone. The core logic behind skin tone-based energy level settings is to adjust the energy by identifying the melanin content on the skin's surface to prevent burns. While this skin tone-centric adjustment method ensures basic safety to some extent, it limits the effectiveness of hair removal. Summary of the Invention

[0004] Therefore, it is necessary to provide a control method, hair removal device, computer-readable storage medium, and computer program product for hair removal devices that can improve hair removal effect while ensuring safety, in response to the above-mentioned technical problems.

[0005] In a first aspect, this application provides a control method for a hair removal device, the method comprising:

[0006] Obtain the first image of the area to be hair removed;

[0007] Based on the first image, image information is identified, including hair density and hair curl level;

[0008] When the image information includes the degree of hair curl, the step of identifying image information based on the first image includes:

[0009] Based on the first image, the first distance and first curvature of each hair are identified; the first distance is the distance between the hair root and the hair tip, and the first curvature is the curvature corresponding to the maximum arc of the hair.

[0010] The degree of hair curl is determined based on the first distance and the first curvature;

[0011] Based on the image information, determine the light-blocking area of ​​the hair;

[0012] Based on the light-blocking area, control parameters are determined, which are used to control the operation of the hair removal device.

[0013] In one embodiment, the image information also includes hair diameter;

[0014] The step of identifying image information based on the first image includes:

[0015] Based on the first image, identify the diameter of the hair;

[0016] Determining the light-blocking area of ​​the hair based on the image information includes:

[0017] The light-blocking area of ​​the hair is determined based on the hair density, the degree of hair curl, and the hair diameter.

[0018] In one embodiment, determining the light-blocking area of ​​the hair based on the hair density, the degree of hair curl, and the hair diameter includes:

[0019] Substitute the hair density, the degree of hair curl, and the hair diameter into a preset coverage formula to output the light-blocking area of ​​the hair;

[0020] The preset coverage formula is obtained by fitting the known hair density, hair curliness and hair diameter with the corresponding known light-blocking area.

[0021] In one embodiment, the method further includes:

[0022] After controlling the hair removal device based on control parameters, a second image of the hair-removed area is acquired;

[0023] Based on the first and second images of the same region, hair removal information is determined;

[0024] Based on the hair removal information, the control parameters are optimized.

[0025] In one embodiment, the hair removal information includes hair removal effect and degree of skin damage; the control parameters include energy and pulse width;

[0026] The optimization of the control parameters based on the hair removal information includes:

[0027] If the degree of skin damage is less than or equal to a preset level, the energy and pulse width are optimized based on the hair removal effect;

[0028] If the degree of skin damage exceeds a preset level, the energy and pulse width are optimized based on the degree of skin damage.

[0029] In one embodiment, the method further includes:

[0030] If the distance between the hair removal device and the area to be hair removed is within a preset distance range, proceed to the step of acquiring the first image / second image.

[0031] In one embodiment, the method further includes:

[0032] Obtain the skin tone of the area to be hair removed;

[0033] Based on the skin color, the control parameters are updated to limit the control parameters within the parameter threshold range corresponding to the skin color.

[0034] Secondly, this application also provides a hair removal device, including a memory and a processor, wherein the memory stores a computer program, and the processor is used to execute the computer program to implement the steps of the above-described method.

[0035] Thirdly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0036] Fourthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method.

[0037] The aforementioned hair removal device control method, hair removal device, computer-readable storage medium, and computer program product determine the control parameters of the hair removal device by using light-blocking information. This fully considers the uneven energy distribution caused by different degrees of shading, and then determines the control parameters based on the unevenly distributed energy. This can improve the hair removal effect within the range of ensuring hair removal safety. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is one of the flowcharts illustrating the control method of a hair removal device in one embodiment;

[0040] Figure 2 This is a second schematic flowchart of the control method for a hair removal device in one embodiment;

[0041] Figure 3 This is the third flowchart illustrating the control method of a hair removal device in one embodiment;

[0042] Figure 4This is a fourth flowchart illustrating the control method of a hair removal device in one embodiment;

[0043] Figure 5 This is the fifth flowchart illustrating the control method of a hair removal device in one embodiment;

[0044] Figure 6 This is a schematic flowchart of the control method for a hair removal device in one embodiment;

[0045] Figure 7 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0047] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0048] The inventors discovered that conventional methods for addressing the energy matching issue in hair removal primarily include: manual adjustment of the energy level and automatic energy level determination based on skin tone. Hair removal devices typically have multiple energy levels, which users can manually select based on skin feel. This adjustment method relies on the user's subjective judgment, lacks scientific rigor, and can easily lead to poor results or skin damage due to inappropriate selection. Automatic energy level determination based on skin tone usually uses sensors to detect the melanin index on the skin surface to determine skin tone. The hair removal device has a preset mapping table between skin tone and energy; based on the detected skin tone and the mapping table, the appropriate energy can be directly determined. While automatic energy level determination based on skin tone has a high degree of automation, it ignores the different effects of lasers on hair with different physical properties and varying degrees of concealment, which may lead to poor hair removal results or even skin burns.

[0049] In one embodiment, this application provides a control method for a hair removal device, see reference. Figure 1 The method includes steps S102 to S104, wherein:

[0050] Step S102: Obtain the light-blocking information of the hair in the area to be hair removed.

[0051] The area to be treated can be multiple. Before each treatment of the current area, the light-blocking information of the hair in that area can be obtained. For example, if a user needs to remove hair from their underarms, but the hair removal device cannot cover all the areas to be treated in one go, the underarms can be divided into N areas to be treated, and the area of ​​each area corresponds to the area treated by the hair removal device in one session.

[0052] Understandably, when using hair removal devices to treat the area, the hair shaft on the skin surface absorbs some of the laser light, while another portion is reflected or scattered by the hair shaft to varying degrees, disrupting the laser path and resulting in uneven energy distribution. This uneven energy distribution can lead to excessive energy in some areas, causing burns, or insufficient energy in others, resulting in poor hair removal.

[0053] Step S104: Based on the light-blocking information, determine the control parameters, which are used to control the operation of the hair removal device.

[0054] As mentioned earlier, by acquiring light-blocking information, the influence of hair on energy can be determined, thereby predicting the energy distribution at different intensities under a preset energy level. Based on the energy distribution at different preset intensities, control parameters can be determined to ensure that areas with excessive energy do not cause skin burns. In other words, this application is equivalent to inferring the settable energy range based on the influence of hair on energy.

[0055] The aforementioned control method for hair removal equipment determines the control parameters of the equipment based on light-blocking information. This method can fully consider the uneven energy distribution caused by different degrees of shading, and then determine the control parameters based on the uneven energy distribution. This can improve the hair removal effect while ensuring the safety of hair removal.

[0056] In one embodiment, the shading information includes the shading area.

[0057] To obtain the light-blocking information of the hair in the area to be treated, please refer to [link / reference]. Figure 2 The process includes steps S202 to S206, wherein:

[0058] Step S202: Obtain the first image of the area to be hair removed.

[0059] The first image of the area to be hair removed is obtained using the image acquisition module in the hair removal device. The image acquisition module can be a miniature complementary metal-oxide-semiconductor (CMOS) image sensor with a resolution of 2 million pixels or higher and an autofocus function, and a macro lens with a focal length of 2mm-5mm. It can also be a miniature camera with higher resolution. No restrictions are placed on the image acquisition module here.

[0060] Step S204: Based on the first image, identify image information, including hair density and hair curliness.

[0061] That is, to identify the hair density and the degree of hair curl in the first image.

[0062] For example, an image recognition algorithm is used to identify the outline of the hair, and the number of hairs is determined based on the identified hair outline. The hair density is determined by the area captured by the first image and the number of hairs. For example, if the first image can clearly capture the hair image within a unit area, the number of hairs determined based on the first image is the number of hairs per unit area, i.e., the hair density.

[0063] For example, the degree of hair curl can also be determined using image recognition algorithms, and no limitations are imposed on the image recognition algorithms here. Based on the recognized hair contour, the curvature of a single hair is determined, thus obtaining the degree of hair curl. It is understood that the curvature determined by the image recognition algorithm is the curvature of multiple hairs in the first image, not the average curvature of the first image. For example, the curvature is divided into M ranges, and the number of curvatures in different ranges is counted. The curvature corresponding to the median or mode of the range with the most curvatures is selected as the degree of hair curl in the first image. The basis for dividing the curvature range can be the degree of influence on the laser path, that is, curvatures with the same or similar degree of influence are divided into one range. The specific determination can be based on experimental test data, and no limitations are imposed here.

[0064] For example, the curvature corresponding to the median or mode in different ranges can be weighted and summed to obtain the degree of hair curl in the first image. The more curvatures in different ranges, the greater the weight.

[0065] The aforementioned methods can all determine the degree of hair curl that best represents the first image, obtain hair density, determine the degree of energy absorption by the hair shaft, obtain the degree of hair curl, determine the degree of influence of the hair shaft on the laser path, and thus determine the energy distribution.

[0066] Step S206: Determine the light-blocking area of ​​the hair based on the image information.

[0067] In this embodiment, the light-blocking area refers to the area within which the laser cannot reach the hair follicle within a distance threshold, and the light-blocking area is less than or equal to the area corresponding to the first image. The larger the light-blocking area, the more laser energy the hair shaft can absorb, and the less energy reaches the hair follicle.

[0068] It is understandable that hair density is the basic data that determines the area of ​​light blocking, and it can directly determine the basic coverage of the hair. The degree of hair curl is a correction data for the basic coverage. Under the same hair density, the higher the degree of hair curl, the larger the corresponding area of ​​light blocking is usually.

[0069] In one embodiment, where the image information includes the degree of hair curl, the image information is identified based on the first image, see [reference]. Figure 3 The process includes steps S302 to S304, wherein:

[0070] Step S302: Based on the first image, identify the first distance and first curvature of each hair; the first distance is the distance between the hair root and the hair tip, and the first curvature is the curvature corresponding to the maximum arc of the hair.

[0071] It is understandable that hair may be composed of multiple arcs or a single arc, with the largest arc having the greatest impact on the light-blocking area. Therefore, the curvature corresponding to the largest arc is chosen as the first curvature.

[0072] Step S304: Determine the degree of hair curl based on the first distance and the first curvature.

[0073] It's understandable that some hairs may be relatively straight overall, but have a small curve, resulting in a larger curl (smaller first curvature value). Other hairs may have multiple curves with a small first distance, meaning that after curling, the hair tip is closer to the root, but the curl of each curve is smaller, resulting in a larger first curvature value (the greater the curvature, the curlier the hair). Directly determining the degree of hair curl based solely on the first curvature is not comprehensive enough. For example, a correction factor can be determined based on the ratio of hair length to the first distance, and the first curvature can be corrected based on this correction factor.

[0074] By obtaining the first distance, the overall actual situation of each hair can be determined. The first curvature is then corrected using the first distance, and the degree of curl of the hair in the first image can be determined more accurately using the corrected first curvature. The process of determining the degree of curl of the hair based on the corrected first curvature is similar to the process of determining the degree of curl of hair based on curvature, and will not be elaborated here.

[0075] In one embodiment, the image information also includes hair diameter.

[0076] Based on the first image, image information is identified, including:

[0077] Based on the first image, the diameter of the hair is identified.

[0078] Based on image recognition algorithms, the outline of hair can be obtained. Based on the hair outline, the hair edge can be fitted, and then the diameter can be directly calculated. No restrictions are placed on the algorithm for obtaining the diameter.

[0079] Based on image information, determine the light-blocking area of ​​the hair, including:

[0080] The area of ​​light blocking by the hair is determined based on hair density, hair curliness, and hair diameter.

[0081] It is understandable that the larger the hair diameter, the wider the shading area. When the hairs do not completely overlap, the larger the hair diameter, the larger the area of ​​light blocking.

[0082] Based on the fact that hair density can be used to determine the basic shading area, by fully considering the influence of hair curliness and hair diameter on the shading area, the shading area can be obtained more accurately, thus providing a basis for assessing energy distribution and determining control parameters.

[0083] In one embodiment, the light-blocking area of ​​the hair is determined based on hair density, hair curl, and hair diameter, including:

[0084] Substitute hair density, hair curl degree, and hair diameter into the preset coverage formula to output the light-blocking area of ​​the hair.

[0085] The preset coverage formula is obtained by fitting the known hair density, hair curliness and hair diameter with the corresponding known shading area.

[0086] Based on the aforementioned method, hair density, hair curl degree, and hair diameter are obtained for multiple sets of different regions. Each region is then divided into smaller units, and the light-blocking sub-area of ​​each unit is obtained. The light-blocking sub-areas of all units within the same region are added together to obtain the light-blocking area of ​​each region. Based on the hair density, hair curl degree, and hair diameter of multiple sets of different regions, and the corresponding light-blocking areas, a preset coverage formula is fitted. No restrictions are placed on the preset coverage formula here. The light-blocking area can be obtained by taking the hair density, hair curl degree, and hair diameter corresponding to the first image.

[0087] Understandably, if an image recognition algorithm is used directly to identify the shading area of ​​the first image, it may be difficult to identify the uncovered parts in the middle of the curly hair due to the small curvature and high degree of hair curling. This would lead to inaccurate identification of the shading area and consequently, an inability to accurately analyze the subsequent energy distribution.

[0088] By determining the shading area based on hair density, hair curl, and hair diameter, the influence of hair curl and hair diameter on the shading area can be considered from multiple dimensions, improving the accuracy of the determined shading area.

[0089] In another embodiment, when the image information only includes hair density and hair curl degree, but not hair diameter, a corresponding preset coverage formula is fitted based on hair density and hair curl degree. The process of fitting the preset coverage formula based on hair density, hair curl degree and hair diameter will not be described in detail here.

[0090] In another embodiment, multiple sets of hair density, hair curl degree, and hair diameter in different regions, as well as the corresponding shading area, are obtained as a sample dataset. The sample dataset is input into a neural network model for training to obtain a trained neural network model. The hair density, hair curl degree, and hair diameter are input into the trained neural network model to output the shading area. No restrictions are placed on the neural network model here.

[0091] In one embodiment, see [reference] Figure 4 The method further includes steps S402 to S404, wherein:

[0092] Step S402: Obtain the skin color of the area to be hair removed.

[0093] For example, the first image can be preprocessed to remove noise, and the preprocessed first image can be color-converted to a specific color space, which can better separate brightness and color information. Within the specific color space, the skin is segmented to determine the corresponding skin parts in the first image. Color features are extracted from the skin to identify skin color; specific techniques can be employed, which will not be elaborated here.

[0094] Step S404: Based on skin color, update the control parameters to limit the control parameters within the parameter threshold range corresponding to the skin color.

[0095] If the control parameter is within the threshold range corresponding to the skin tone, the control parameter remains unchanged. If the control parameter exceeds the threshold range corresponding to the skin tone, the control parameter is updated to the corresponding maximum value. If the control parameter is less than the threshold range corresponding to the skin tone, the control parameter is updated to the corresponding minimum value.

[0096] For example, the control parameter is energy. The energy range determined based on skin color is 40J / cm²-50J / cm². If the control parameter determined based on the shading area is 35J / cm², then the control parameter can be updated to 40J / cm². If the control parameter determined based on the shading area is 55J / cm², then the control parameter can be updated to 50J / cm², and so on for other control parameters, which will not be elaborated here.

[0097] It's understandable that hair removal devices work by using energy absorbed by the melanin in the hair follicle, thus destroying it. However, the skin surface also contains melanin; the darker the skin, the more melanin is present. If the energy is too high, the melanin on the skin surface may over-absorb the energy, leading to skin damage. If the energy is too low, the hair follicle may not absorb enough energy, thus failing to destroy it. By controlling the parameters based on skin tone, the safety and effectiveness of the hair removal device can be ensured.

[0098] In one embodiment, see [reference] Figure 5 The method further includes steps S502 to S506, wherein:

[0099] Step S502: After controlling the hair removal device to work based on the control parameters, acquire a second image of the hair-removed area.

[0100] The method for obtaining the second image is the same as that for obtaining the first image, and will not be repeated here.

[0101] Step S504: Determine hair removal information based on the first and second images of the same region.

[0102] The hair removal information includes the hair removal effect and the degree of skin damage. Both information are derived from a comparison of a first image and a second image of the same area. For example, if the hair in the first image is longer and more abundant, and the hair in the second image is shorter and less abundant, the hair removal effect can be determined to be good. Conversely, if the hair in the first image is shorter and less abundant, and some hair remains in the second image, the hair removal effect can be determined to be poor. Specifically, this can be determined based on hair density and the relative hair length in the first and second images, without limitation. The degree of skin damage can be determined based on the degree of redness and swelling compared to the first and second images, and can be determined based on a preset mapping table, without limitation.

[0103] Step S506: Optimize the control parameters based on the hair removal information.

[0104] By acquiring hair removal information, feedback can be provided on the degree of skin damage and hair removal effect based on control parameters determined by the shaded area. Based on the degree of skin damage and hair removal effect, the control parameters can be optimized to maximize the hair removal effect while minimizing damage, thus improving the hair removal effect while ensuring safety.

[0105] Understandably, the control parameters determined based on light-blocking information are applicable to most users. However, some users may have more sensitive skin and lower energy tolerance. By acquiring hair removal information and optimizing the control parameters based on that information, personalized optimization can be achieved, thus improving the safety of hair removal.

[0106] In one embodiment, the hair removal information includes the hair removal effect and the degree of skin damage; the control parameters include energy and pulse width.

[0107] Based on hair removal information, the control parameters were optimized. (See attached document.) Figure 6 The process includes steps S602 to S604, wherein:

[0108] Step S602: If the degree of skin damage is less than or equal to the preset degree, optimize the energy and pulse width based on the hair removal effect.

[0109] It is understandable that the preset level is not a critical value for skin damage, but a value that is less than the critical value. When the level of skin damage is less than or equal to the preset level, it means that there is still some room before skin damage occurs. The energy and pulse width can be adjusted, such as increasing the energy and appropriately shortening the pulse width, to enhance the hair removal effect.

[0110] Step S604: If the degree of skin damage is greater than the preset degree, optimize the energy and pulse width based on the degree of skin damage.

[0111] If the degree of skin damage exceeds the preset level, caution should be exercised when adjusting the energy. Although there is room to further increase the energy, doing so may lead to further skin damage, or the skin may already be damaged. A further assessment based on the degree of skin damage is necessary. If the skin is not yet damaged, the energy and pulse width can be increased, but the increased energy should be less than the energy increased based on step S602. If the skin is already damaged, the energy should be decreased and the pulse width increased, or hair removal should be stopped.

[0112] By optimizing the control parameters based on the user's actual hair removal information, more personalized control parameters can be obtained, thereby maximizing the hair removal effect within a safe range.

[0113] In one embodiment, the method further includes:

[0114] If the distance between the hair removal device and the area to be hair removed is within a preset distance range, proceed to the step of acquiring the first image / second image.

[0115] More specifically, this can be achieved by ensuring that the distance between the image acquisition module in the hair removal device and the area to be treated is within a preset distance range. By limiting the distance to within the preset range, it can be ensured that the image acquisition module maintains a standard distance from the skin during imaging, such as being close to the skin without squeezing it, thereby preventing distortion of the acquired image.

[0116] In this embodiment, before acquiring the first image, a razor or other tools can be used to remove longer hairs from the surface of the area to be hair removed, thereby improving the clarity of the acquired image. Although removing longer hairs significantly reduces the degree of light occlusion by the hairs on the laser, the curly hairs can still affect the laser's optical path. Furthermore, a single hair follicle typically contains multiple hairs, and these hairs grow in different directions, thus affecting the laser's optical path differently. Therefore, even after removing longer hairs, the impact of light occlusion on the laser still needs to be considered.

[0117] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0118] Based on the same inventive concept, this application also provides a hair removal device for implementing the control method of the hair removal device described above. The solution provided by this hair removal device is similar to the solution described in the above method. Therefore, the specific limitations of one or more hair removal device embodiments provided below can be found in the limitations of the control method of the hair removal device above, and will not be repeated here.

[0119] In an exemplary embodiment, a hair removal device is provided. The device includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of the method described above. The hair removal device also includes an input / output interface (I / O) and a communication interface. The processor, memory, and I / O interface are connected via a system bus, and the communication interface is connected to the system bus via the I / O interface. The processor of the hair removal device provides computing and control capabilities. The memory of the hair removal device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the hair removal device stores control data for the hair removal device. The I / O interface of the hair removal device is used for exchanging information between the processor and external devices. The communication interface of the hair removal device is used for communicating with an external terminal via a network connection. When the computer program is executed by the processor, it implements a control method for the hair removal device.

[0120] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the hair removal device to which the present application is applied. A specific hair removal device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0121] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps described above.

[0122] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps described above.

[0123] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0124] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0125] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0126] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A control method for a hair removal device, characterized in that, The method includes: Obtain the first image of the area to be hair removed; Based on the first image, image information is identified, including hair density, hair curliness, and hair diameter. When the image information includes the degree of hair curl, the step of identifying image information based on the first image includes: Based on the first image, the first distance and first curvature of each hair are identified; the first distance is the distance between the hair root and the hair tip, and the first curvature is the curvature corresponding to the maximum arc of the hair. The degree of hair curl is determined based on the first distance and the first curvature; The hair density, hair curl degree, and hair diameter are substituted into a preset coverage formula to output the light-blocking area of ​​the hair; the preset coverage formula is obtained by fitting the known hair density, hair curl degree, and hair diameter with the corresponding known light-blocking area. Based on the light-blocking area, control parameters are determined, which are used to control the operation of the hair removal device.

2. The method according to claim 1, characterized in that, The method further includes: After controlling the hair removal device based on control parameters, a second image of the hair-removed area is acquired; Based on the first and second images of the same region, hair removal information is determined; Based on the hair removal information, the control parameters are optimized.

3. The method according to claim 2, characterized in that, The hair removal information includes the hair removal effect and the degree of skin damage; the control parameters include energy and pulse width; The optimization of the control parameters based on the hair removal information includes: If the degree of skin damage is less than or equal to a preset level, the energy and pulse width are optimized based on the hair removal effect; If the degree of skin damage exceeds a preset level, the energy and pulse width are optimized based on the degree of skin damage.

4. The method according to claim 2, characterized in that, The method further includes: If the distance between the hair removal device and the area to be hair removed is within a preset distance range, proceed to the step of acquiring the first image / second image.

5. The method according to claim 1, characterized in that, The method further includes: Obtain the skin tone of the area to be hair removed; Based on the skin color, the control parameters are updated to limit the control parameters within the parameter threshold range corresponding to the skin color.

6. A hair removal device, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 5.

8. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 5.

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