Precise UV Nail Curing Method and System Based on AI Image Recognition

Abstract

The present invention relates to the field of image processing, and discloses an accurate UV nail curing method and system based on AI image recognition, including: calculating the irradiation uniformity of the UV lamp; adjusting the image acquisition parameters of the image acquisition module in the nail curing system to acquire the nail image of the cured nail in the nail curing system; filtering the nail image to obtain a filtered nail image, defining a nail area recognition algorithm for the filtered nail image, and extracting the nail application area image of the filtered nail image; analyzing the curing state of the cured nail through a trained AI nail curing analysis model, establishing a state-UV lamp relationship model for the cured nail, and defining a UV lamp control algorithm for the cured nail; using the UV lamp control algorithm to analyze the UV lamp irradiation optimization parameters of the UV lamp, analyzing the curing abnormality of the cured nail, analyzing the curing adaptive parameters of the nail curing system, and performing accurate curing of the cured nail based on the curing adaptive parameters. The present invention can improve the curing effect of nail curing.

Description

Technical Field

[0001] The present invention relates to an accurate UV nail curing method and system based on AI image recognition, belonging to the field of image processing. Background Art

[0002] Accurate UV nail curing refers to the process of irradiating UV-curable nail polish applied on nails with a UV (ultraviolet) lamp to achieve rapid curing. This process precisely controls the irradiation intensity, time, and angle of the UV lamp to ensure uniform and thorough curing of the nail polish, thereby achieving the best nail art effect.

[0003] Traditional accurate UV nail curing methods usually rely on the manual operation and empirical judgment of nail technicians. The nail polish is cured by visual observation and preset UV lamp curing time. The curing effect of this method is greatly affected by the personal skills and experience of nail technicians, and problems such as uneven curing or over-curing are likely to occur. There is a lack of real-time monitoring and adjustment of the curing process, resulting in obvious deficiencies in the accuracy, efficiency, personalized service, and quality control of the nail curing process. Summary of the Invention

[0004] The present invention provides an accurate UV nail curing method and system based on AI image recognition, and its main purpose is to improve the accuracy of security authentication on the premise of reducing the workload of path detection.

[0005] To achieve the above object, an accurate UV nail curing method based on AI image recognition provided by the present invention includes:

[0006] Obtain the nail curing area and its area environmental characteristics in the nail curing system, extract the UV lamp irradiation parameters of the UV lamp in the nail curing system, and calculate the irradiation uniformity of the UV lamp according to the UV lamp irradiation parameters;

[0007] When the irradiation uniformity meets the preset irradiation uniformity threshold, adjust the image acquisition parameters of the image acquisition module in the nail curing system according to the area environmental characteristics, and based on the image acquisition parameters, acquire the nail image of the cured nail in the nail curing system;

[0008] Filter the nail image to obtain a filtered nail image, define the nail area recognition algorithm of the filtered nail image, and extract the nail application area image of the filtered nail image based on the nail area recognition algorithm;

[0009] Based on the image of the nail art application area, analyze the curing state of the cured nail art through a trained AI nail art curing analysis model. Through the curing state, establish a state-UV lamp relationship model for the cured nail art. Based on the state-UV lamp relationship model, define the UV lamp control algorithm for the cured nail art.

[0010] According to the curing state, use the UV lamp control algorithm to analyze the optimized UV lamp irradiation parameters of the UV lamp. Based on the UV lamp irradiation optimized parameters, perform continuous curing of the cured nail art to obtain curing data. Based on the curing data, analyze the curing abnormality of the cured nail art. Through the curing abnormality, analyze the curing adaptive parameters of the nail art curing system. Based on the curing adaptive parameters, perform precise curing of the cured nail art.

[0011] Optionally, calculating the irradiation uniformity of the UV lamp according to the UV lamp irradiation parameters includes:

[0012] Determine the irradiation area of the UV lamp according to the UV lamp irradiation parameters;

[0013] Analyze the operating state of the UV lamp based on the UV lamp irradiation parameters;

[0014] When the operating state of the UV lamp meets the preset operating state standard, grid the irradiation area to obtain a gridded irradiation area;

[0015] Use a preset UV intensity meter to identify the UV intensity value of the corresponding area grid of the gridded irradiation area;

[0016] Calculate the irradiation uniformity of the UV lamp based on the UV intensity value.

[0017] Optionally, calculating the irradiation uniformity of the UV lamp based on the UV intensity value includes:

[0018] Calculate the average intensity of the UV lamp according to the UV intensity value;

[0019] Calculate the standard deviation of the UV lamp through the average intensity;

[0020] Based on the average intensity and the standard deviation, use the following formula to calculate the irradiation uniformity of the UV lamp:

[0021] ;

[0022] Wherein, represents the irradiation uniformity of the UV lamp, represents the average intensity of the UV lamp, represents the The UV intensity value of a regional grid, represents the standard deviation, and represents the number of regional grids.

[0023] Optionally, when the irradiation uniformity meets a preset irradiation uniformity threshold, according to the regional environmental characteristics, adjust the image acquisition parameters of the image acquisition module in the nail curing system, including:

[0024] When the irradiation uniformity meets the preset irradiation uniformity threshold, according to the regional environmental characteristics, determine the light characteristics, visual characteristics, and environmental characteristics of the irradiation area corresponding to the nail curing system;

[0025] Based on the light characteristics, analyze the light environment of the irradiation area;

[0026] Through the visual characteristics, determine the regional surface color and regional surface texture of the irradiation area;

[0027] According to the environmental characteristics, analyze the regional temperature and regional humidity of the irradiation area;

[0028] Define the image acquisition requirements for the irradiation area;

[0029] Identify the current image acquisition parameters of the image acquisition module;

[0030] Combining the light environment, the regional surface color, the regional surface texture, the regional temperature, the regional humidity, and the image acquisition requirements, analyze the image acquisition loss of the current image acquisition parameters;

[0031] Based on the image acquisition loss, define the image acquisition parameters of the image acquisition module.

[0032] Optionally, the extraction of the nail application area image of the filtered nail image based on the nail area recognition algorithm includes:

[0033] Grayscale the filtered nail image to obtain a grayscale nail image;

[0034] Perform Gaussian blur on the grayscale nail image to obtain a Gaussian blurred image;

[0035] Use the nail area recognition algorithm to mark the nail contour of the Gaussian blurred image;

[0036] Define the maximum nail contour of the nail contour;

[0037] Establish a contour mask for the maximum nail contour, and extract the nail application contour of the Gaussian blurred image based on the contour mask;

[0038] Calculate the manicure integrity coefficient of the manicure application contour;

[0039] When the manicure integrity coefficient meets a preset manicure integrity threshold, extract the manicure application area image of the filtered manicure image according to the manicure application contour.

[0040] Optionally, the marking of the manicure contour of the Gaussian blurred image using the manicure area recognition algorithm includes:

[0041] Calculate the pixel gradient and pixel direction of the image pixel points corresponding to the Gaussian blurred image;

[0042] Determine the first adjacent pixel point and the second adjacent pixel point of the image pixel point according to the pixel direction;

[0043] According to the first adjacent pixel point and the second adjacent pixel point, calculate the suppression gradient of the image pixel point using the following formula:

[0044] ;

[0045] Wherein, represents the suppression gradient of the image pixel point , represents the first adjacent pixel point, represents the second adjacent pixel point, represents the pixel gradient of the first adjacent pixel point, represents the pixel gradient of the second adjacent pixel point, represents the pixel gradient of the image pixel point , represents sum, represents otherwise;

[0046] Determine the manicure contour of the Gaussian blurred image according to the suppression gradient.

[0047] Optionally, the analysis of the curing state of the cured manicure according to the manicure application area image by the trained AI manicure curing analysis model includes:

[0048] Extract the curing features of the cured manicure using the feature extraction layer in the AI manicure curing analysis model according to the manicure application area image;

[0049] Perform feature extraction on the curing features using the feature pooling layer in the AI manicure curing analysis model to obtain target curing features;

[0050] Based on the target curing features, analyze the curing state probability of the cured manicure using the probability analysis layer in the AI manicure curing analysis model;

[0051] Determine the curing state of the cured nail art according to the curing state probability.

[0052] Optionally, defining the UV lamp control algorithm for the cured nail art based on the state-UV lamp relationship model includes:

[0053] Determine the curing attenuation coefficient of the cured nail art;

[0054] Define the UV lamp control parameters for the cured nail art according to the state-UV lamp relationship model, where the UV lamp control parameters include irradiation intensity, irradiation angle, and irradiation time;

[0055] Based on the irradiation intensity, the irradiation angle, the irradiation time, and the curing attenuation coefficient, construct the UV lamp control algorithm for the cured nail art using the following formula; where the UV lamp control algorithm:

[0056] ;

[0057] Where represents the curing state at time ; represents the curing state at time ; represents the irradiation intensity at time ; represents the irradiation time at time ; represents the irradiation angle at time ; represents the curing attenuation coefficient, represents the time step.

[0058] Where the curing attenuation coefficient refers to the rate at which the curing state naturally decreases due to external factors (such as temperature, humidity, etc.) per unit time, the irradiation intensity refers to the energy output of the UV lamp per unit area, the irradiation angle refers to the angle between the light emitted by the UV lamp and the surface of the nail art, the irradiation time refers to the duration of the UV lamp irradiating the surface of the nail art, and the time step refers to the time interval between two consecutive time points in the simulation or control algorithm.

[0059] Optionally, analyzing the curing abnormality of the cured nail art based on the curing data includes:

[0060] Preprocess the curing data to obtain preprocessed curing data;

[0061] Establish an abnormality benchmark for the cured nail art;

[0062] Identify the curing abnormality pattern of the preprocessed curing data according to the abnormality benchmark;

[0063] Extract the abnormal pattern features of the curing abnormal pattern;

[0064] Analyze the curing abnormality of the cured nail art based on the abnormal pattern features.

[0065] To solve the above problems, the present invention also provides a precise UV nail art curing system based on AI image recognition, and the system includes:

[0066] An irradiation uniformity analysis module, configured to obtain the nail art curing area and its area environment features in the nail art curing system, extract the UV lamp irradiation parameters of the UV lamp in the nail art curing system, and calculate the irradiation uniformity of the UV lamp according to the UV lamp irradiation parameters;

[0067] A nail art image acquisition module, configured to adjust the image acquisition parameters of the image acquisition module in the nail art curing system according to the area environment features when the irradiation uniformity meets a preset irradiation uniformity threshold, and acquire a nail art image of the cured nail art in the nail art curing system based on the image acquisition parameters;

[0068] A nail art application area recognition module, configured to filter the nail art image to obtain a filtered nail art image, define a nail art area recognition algorithm for the filtered nail art image, and extract a nail art application area image of the filtered nail art image based on the nail art area recognition algorithm;

[0069] A UV lamp control algorithm construction module, configured to analyze the curing state of the cured nail art through a trained AI nail art curing analysis model according to the nail art application area image, establish a state-UV lamp relationship model of the cured nail art through the curing state, and define a UV lamp control algorithm for the cured nail art based on the state-UV lamp relationship model;

[0070] A curing parameter optimization module, configured to analyze the UV lamp irradiation optimization parameters of the UV lamp by using the UV lamp control algorithm according to the curing state, perform continuous curing of the cured nail art based on the UV lamp irradiation optimization parameters to obtain curing data, analyze the curing abnormality of the cured nail art based on the curing data, analyze the curing adaptive parameters of the nail art curing system through the curing abnormality, and perform precise curing of the cured nail art based on the curing adaptive parameters.

[0071] Compared with the problems described in the background art, first, the system accurately obtains the manicure curing area and its environmental characteristics, extracts the irradiation parameters of the UV lamp, calculates the irradiation uniformity, ensures the uniform distribution of light during the curing process, thereby improving the curing quality. When the irradiation uniformity meets the preset threshold, the system automatically adjusts the parameters of the image acquisition module, ensuring that the captured manicure images are clear and accurate, providing a reliable data basis for subsequent analysis. Secondly, by filtering the manicure images and combining with the manicure area recognition algorithm, the system can accurately extract the image of the manicure application area, providing a targeted analysis object for the AI manicure curing analysis model and improving the accuracy of curing state analysis. Furthermore, the application of the AI manicure curing analysis model enables real-time monitoring of the curing state. Then, a relationship model between the curing state and the UV lamp irradiation parameters is established, and a UV lamp control algorithm is defined. These measures not only optimize the irradiation parameters of the UV lamp but also realize the intelligent control of the curing process. Finally, by analyzing the curing data, the system can timely detect curing abnormalities and make adjustments according to the curing adaptive parameters to perform precise curing. This not only improves the curing quality of manicure products but also reduces rework and material waste caused by uneven curing or insufficient curing, reduces production costs, and improves customer satisfaction. Therefore, the present invention can improve the curing effect of manicure curing. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 FIG. is a schematic flowchart of a precise UV manicure curing method based on AI image recognition provided by an embodiment of the present invention;

[0073] Figure 2 FIG. is a schematic diagram of a module for implementing the precise UV manicure curing method based on AI image recognition provided by an embodiment of the present invention.

[0074] The implementation, functional features, and advantages of the present invention will be further described in conjunction with the embodiments with reference to the accompanying drawings. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0075] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0076] An embodiment of the present application provides a precise UV manicure curing method based on AI image recognition. The execution subject of the precise UV manicure curing method based on AI image recognition includes, but is not limited to, at least one of electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided by the embodiment of the present application. In other words, the precise UV manicure curing method based on AI image recognition can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to: a single server, a server cluster, a cloud server, or a cloud server cluster, etc.

[0077] Example 1:

[0078] Refer to Figure 1 As shown, it is a schematic flowchart of an accurate UV nail curing method based on AI image recognition provided by an embodiment of the present invention. In this embodiment, the accurate UV nail curing method based on AI image recognition includes:

[0079] S1. Obtain the nail curing area and its area environmental characteristics in the nail curing system, extract the UV lamp irradiation parameters of the UV lamp in the nail curing system, and calculate the irradiation uniformity of the UV lamp according to the UV lamp irradiation parameters.

[0080] It should be explained that the nail curing system is a complete system integrating hardware and software for curing nail products such as nail polish and gel. The nail curing area refers to the specific part that needs to be cured, usually the fingernails or toenails of a customer. The area environmental characteristics refer to the environmental conditions around the nail curing area, which may affect the curing effect, including but not limited to the following aspects: lighting conditions, temperature, humidity, color and texture, surface flatness. The UV lamp refers to a lamp used to emit ultraviolet rays, which are usually used to cure nail products. The UV lamp irradiation parameters refer to a series of parameters used to control and optimize the UV lamp curing process.

[0081] The present invention can calculate the irradiation uniformity of the UV lamp according to the UV lamp irradiation parameters and optimize the irradiation effect according to the results.

[0082] Specifically, calculating the irradiation uniformity of the UV lamp according to the UV lamp irradiation parameters includes:

[0083] Determine the irradiation area of the UV lamp according to the UV lamp irradiation parameters;

[0084] Analyze the operating state of the UV lamp based on the UV lamp irradiation parameters;

[0085] When the operating state of the UV lamp meets the preset operating state standard, grid the irradiation area to obtain a gridded irradiation area;

[0086] Use a preset UV intensity meter to identify the UV intensity values of the area grids corresponding to the gridded irradiation area;

[0087] Calculate the irradiation uniformity of the UV lamp based on the UV intensity values.

[0088] Among them, the irradiation area refers to the spatial range that can be effectively irradiated by the UV lamp. The operating state of the UV lamp refers to various performance indicators when the UV lamp is operating, including but not limited to current, voltage, power, temperature, irradiation intensity, etc. The grid irradiation area refers to dividing the irradiation area into a series of small and evenly distributed grid units, and each unit represents a part of the irradiation area. The UV intensity meter is an instrument used to measure the intensity of ultraviolet light. The UV intensity value refers to the intensity of the UV light measured in each grid unit. The irradiation uniformity refers to the degree of uniformity of the UV intensity distribution in the entire irradiation area.

[0089] Further, calculating the irradiation uniformity of the UV lamp based on the UV intensity value includes:

[0090] Calculating the average intensity of the UV lamp according to the UV intensity value;

[0091] Calculating the standard deviation of the UV lamp through the average intensity;

[0092] Based on the average intensity and the standard deviation, calculate the irradiation uniformity of the UV lamp using the following formula:

[0093] ;

[0094] Among them, represents the irradiation uniformity of the UV lamp, represents the average intensity of the UV lamp, represents the th area grid of the UV lamp's UV intensity value, represents the standard deviation, represents the number of area grids.

[0095] Among them, the average intensity refers to the arithmetic mean of the UV intensity values of all measured grid units. The standard deviation is a statistic that measures the deviation between the measured values and the mean, and it reflects the degree of dispersion of the UV intensity values in the irradiation area.

[0096] S2. When the irradiation uniformity meets the preset irradiation uniformity threshold, adjust the image acquisition parameters of the image acquisition module in the nail curing system according to the regional environmental characteristics, and based on the image acquisition parameters, acquire the nail image of the cured nail in the nail curing system.

[0097] In the present invention, when the irradiation uniformity meets the preset irradiation uniformity threshold, adjusting the image acquisition parameters of the image acquisition module in the nail curing system according to the regional environmental characteristics can ensure that the parameter settings of the image acquisition module can adapt to the irradiation effect of the UV lamp, thereby improving the overall performance of the nail curing system.

[0098] Specifically, when the irradiation uniformity meets the preset irradiation uniformity threshold, according to the regional environmental characteristics, adjusting the image acquisition parameters of the image acquisition module in the nail curing system includes:

[0099] When the irradiation uniformity meets the preset irradiation uniformity threshold, according to the regional environmental characteristics, determining the light characteristics, visual characteristics, and environmental characteristics of the irradiation area corresponding to the nail curing system;

[0100] Based on the light characteristics, analyzing the light environment of the irradiation area;

[0101] Through the visual characteristics, determining the regional surface color and regional surface texture of the irradiation area;

[0102] According to the environmental characteristics, analyzing the regional temperature and regional humidity of the irradiation area;

[0103] Defining the image acquisition requirements for the irradiation area;

[0104] Identifying the current image acquisition parameters of the image acquisition module;

[0105] Combining the light environment, the regional surface color, the regional surface texture, the regional temperature, the regional humidity, and the image acquisition requirements, analyzing the image acquisition loss of the current image acquisition parameters;

[0106] Based on the image acquisition loss, defining the image acquisition parameters of the image acquisition module.

[0107] Among them, the irradiation uniformity threshold refers to a preset standard value of irradiation uniformity, which is used to determine whether the irradiation effect of the UV lamp meets the expected uniformity requirements. The image acquisition module refers to the device in the nail curing system used to capture images of the irradiation area, usually including a camera, a sensor, and other related electronic components. The light environment refers to the lighting conditions in the irradiation area, including natural light, indoor lighting, the irradiation intensity of the UV lamp, etc. The surface color of the area refers to the color characteristics of the surface of the irradiation area. Different colors may absorb or reflect different amounts of light, thereby affecting the results of image acquisition. The surface texture of the area refers to the texture and pattern of the surface of the irradiation area. The temperature of the area refers to the temperature conditions in the irradiation area. Temperature changes may affect the performance of the image sensor and the image quality. The humidity of the area refers to the humidity level in the irradiation area. Humidity may affect the response of the image sensor and the clarity of the image. The image acquisition requirements refer to a series of conditions that the image acquisition module needs to meet in order to achieve the performance requirements of the nail curing system, such as resolution, exposure time, contrast, etc. The current image acquisition parameters refer to the parameter values currently set by the image acquisition module, including exposure time, contrast, white balance, resolution, etc. The image acquisition loss refers to the degradation of image quality caused by improper setting of the current image acquisition parameters, including overexposure, underexposure, color distortion, blurring, etc. The image acquisition parameters refer to the specific parameter values set to optimize the quality of image acquisition.

[0108] It should be explained that the nail art image refers to a picture showing the artistic design of fingernails or toenails.

[0109] S3. Filter the nail art image to obtain a filtered nail art image, define the nail area recognition algorithm for the filtered nail art image, and extract the nail application area image of the filtered nail art image based on the nail area recognition algorithm.

[0110] The present invention filters the nail art image to obtain a filtered nail art image, which can improve the image quality and provide a basis for subsequent image analysis. Among them, the filtered nail art image refers to the image obtained by filtering the nail art image. Specifically, the filtered nail art image can be processed by Adobe Photoshop.

[0111] It should be explained that the nail area recognition algorithm refers to the algorithm for recognizing the nail area in the filtered nail art image.

[0112] The present invention extracts the nail application area image of the filtered nail art image based on the nail area recognition algorithm, which can improve the efficiency of image analysis, thereby more accurately controlling the nail curing time.

[0113] Specifically, extracting the manicure application area image of the filtered manicure image based on the manicure area recognition algorithm includes:

[0114] Grayscale the filtered manicure image to obtain a grayscale manicure image;

[0115] Perform Gaussian blur on the grayscale manicure image to obtain a Gaussian blurred image;

[0116] Use the manicure area recognition algorithm to mark the manicure contour of the Gaussian blurred image;

[0117] Define the maximum manicure contour of the manicure contour;

[0118] Establish a contour mask for the maximum manicure contour and extract the manicure application contour of the Gaussian blurred image based on the contour mask;

[0119] Calculate the manicure integrity coefficient of the manicure application contour;

[0120] When the manicure integrity coefficient meets the preset manicure integrity threshold, extract the manicure application area image of the filtered manicure image according to the manicure application contour.

[0121] Among them, the grayscale manicure image refers to an image obtained by converting the original color manicure image to grayscale scale. The Gaussian blurred image refers to an image processed by applying a Gaussian blur filter. The manicure contour refers to the boundary of the nail edge or the application area identified by edge detection or other image segmentation techniques in the grayscale manicure image. The maximum manicure contour refers to the contour with the largest area among all the identified contours in the image. The contour mask refers to a binary image in which the area corresponding to the maximum manicure contour is marked as white (or 255), while other areas are marked as black (or 0). The manicure application contour refers to the boundary representing the manicure application area extracted by the contour mask. The manicure integrity coefficient refers to an index quantifying the integrity of the manicure application contour. The manicure integrity threshold refers to a preset standard for judging whether the manicure integrity coefficient is high enough. The manicure application area image refers to an image extracted from the original filtered manicure image that only contains the manicure application area.

[0122] Further, the using the manicure area recognition algorithm to mark the manicure contour of the Gaussian blurred image includes:

[0123] Calculate the pixel gradient and pixel direction of the image pixel points corresponding to the Gaussian blurred image;

[0124] Determine the first adjacent pixel point and the second adjacent pixel point of the image pixel point according to the pixel direction;

[0125] Calculate the suppression gradient of the image pixel based on the first adjacent pixel and the second adjacent pixel using the following formula:

[0126] ;

[0127] where, represents the suppression gradient of the image pixel , represents the first adjacent pixel represents the second adjacent pixel represents the pixel gradient of the first adjacent pixel represents the pixel gradient of the second adjacent pixel represents the pixel gradient of the image pixel , represents sum, represents otherwise;

[0128] Determine the nail art contour of the Gaussian blurred image according to the suppression gradient.

[0129] wherein, the pixel gradient refers to the intensity change rate of each pixel in the horizontal and vertical directions of the image, the pixel direction refers to the direction of the pixel gradient, usually obtained by calculating the arctangent of Gx and Gy, the first adjacent pixel and the second adjacent pixel refer to two pixels adjacent along the gradient direction according to the direction of the pixel gradient during non-maximum suppression, and the suppression gradient refers to the gradient value calculated during non-maximum suppression.

[0130] S4. Analyze the curing state of the cured nail art according to the nail art application area image through a trained AI nail art curing analysis model, establish a state-UV lamp relationship model of the cured nail art based on the curing state, and define a UV lamp control algorithm for the cured nail art based on the state-UV lamp relationship model.

[0131] According to the nail art application area image of the present invention, analyzing the curing state of the cured nail art through a trained AI nail art curing analysis model can accurately identify the current curing degree of the nail art, thereby serving as a basis for later curing optimization.

[0132] Specifically, analyzing the curing state of the cured nail art according to the nail art application area image through a trained AI nail art curing analysis model includes:

[0133] Extract the curing features of the cured nail art from the nail art application area image by using the feature extraction layer in the AI nail art curing analysis model;

[0134] Extract the physical signs of the curing features using the feature pooling layer in the AI nail curing analysis model to obtain the target curing features;

[0135] Based on the target curing features, analyze the curing state probability of the cured nail using the probability analysis layer in the AI nail curing analysis model;

[0136] Determine the curing state of the cured nail according to the curing state probability.

[0137] Among them, the AI nail curing analysis model refers to a deep learning model used to analyze the curing state of nails, the feature extraction layer refers to the layer specifically used to extract useful features from the input image, the curing features refer to the features related to the curing state extracted from the image of the nail application area, the feature pooling layer refers to the layer used to reduce the spatial dimension of the features while retaining the most important information, the target curing features refer to the curing features processed by the feature pooling layer, the curing state probability refers to a probability distribution output by the model, indicating the probability that the input image belongs to each possible curing state, and the curing state refers to the final curing state classification determined according to the curing state probability output by the model, such as "fully cured", "partially cured" or "uncured".

[0138] It should be explained that the state-UV lamp relationship model refers to a mathematical or computational model that can describe and predict the relationship between the state of the cured nail (such as fully cured, partially cured, uncured) and the irradiation parameters of the UV lamp (such as irradiation time, irradiation intensity, irradiation distance, etc.).

[0139] The present invention can achieve precise control of the cured nail by defining the UV lamp control algorithm for the cured nail. Among them, the UV lamp control algorithm refers to the algorithm for controlling the UV lamp.

[0140] Specifically, defining the UV lamp control algorithm for the cured nail based on the state-UV lamp relationship model includes:

[0141] Determine the curing attenuation coefficient of the cured nail;

[0142] According to the state-UV lamp relationship model, define the UV lamp control parameters for the cured nail, where the UV lamp control parameters include irradiation intensity, irradiation angle, and irradiation time;

[0143] Based on the irradiation intensity, the irradiation angle, the irradiation time, and the curing attenuation coefficient, construct the UV lamp control algorithm for the cured nail using the following formula; where the UV lamp control algorithm:

[0144] ;

[0145] Among them, represents the curing state at time ; represents the curing state at time ; represents the irradiation intensity at time ; represents the irradiation time at time ; represents the irradiation angle at time ; represents the curing attenuation coefficient, represents the time step.

[0146] Among them, the curing attenuation coefficient refers to the rate at which the curing state naturally decreases due to external factors (such as temperature, humidity, etc.) per unit time. The irradiation intensity refers to the energy output of the UV lamp per unit area. The irradiation angle refers to the angle between the light emitted by the UV lamp and the nail art surface. The irradiation time refers to the duration of the UV lamp irradiating the nail art surface. The time step refers to the time interval between two consecutive time points in the simulation or control algorithm.

[0147] S5. According to the curing state, use the UV lamp control algorithm to analyze the UV lamp irradiation optimization parameters of the UV lamp, perform continuous curing of the cured nail art based on the UV lamp irradiation optimization parameters to obtain curing data, analyze the curing abnormality of the cured nail art based on the curing data, analyze the curing adaptive parameters of the nail art curing system through the curing abnormality, and perform precise curing of the cured nail art based on the curing adaptive parameters.

[0148] According to the curing state of the present invention, using the UV lamp control algorithm to analyze the UV lamp irradiation optimization parameters of the UV lamp can automatically optimize the irradiation parameters of the UV lamp to achieve the best curing effect. Specifically, the UV lamp irradiation optimization parameters refer to the parameter values for adjusting the UV lamp. The curing data refers to the data involved in the curing process of the cured nail art by the adjusted UV lamp control parameters.

[0149] Based on the curing data of the present invention, analyzing the curing abnormality of the cured nail art can find the abnormality of the cured nail art, thereby realizing parameter optimization in a timely manner, and thus improving the curing effect of the cured nail art.

[0150] Specifically, the analysis of the curing abnormality of the cured nail art based on the curing data includes:

[0151] Perform preprocessing on the curing data to obtain preprocessed curing data;

[0152] Establish the abnormality benchmark for the cured nail art;

[0153] Identify the curing abnormality patterns of the preprocessed curing data according to the abnormality benchmark;

[0154] Extract the abnormal pattern features of the curing abnormality patterns;

[0155] Analyze the curing abnormality of the cured nail art based on the abnormal pattern features.

[0156] Among them, the preprocessed curing data refers to the curing-related data processed through cleaning, standardization, normalization or other conversion steps. The abnormality benchmark is a set of rules or standards used to distinguish normal curing behavior from abnormal curing behavior. The curing abnormality pattern refers to the patterns or behaviors in the curing data that are inconsistent with the normal curing process. The abnormal pattern features refer to the key features extracted from the curing abnormality patterns, and these features can represent the essential attributes of the abnormality, such as the length of the curing time, the fluctuation of the curing degree, the temperature change, etc. The curing abnormality refers to any behavior that does not meet the expectations or standards during the curing process.

[0157] Optionally, the identification of the curing abnormality patterns of the preprocessed curing data according to the abnormality benchmark can be performed through data mining techniques.

[0158] Optionally, the present invention analyzes the curing adaptive parameters of the nail art curing system through the curing abnormality to ensure that the curing system can automatically adjust the parameters according to real-time data to achieve the best curing effect. Among them, the curing adaptive parameters refer to the parameters involved in the process of curing nail art by the nail art curing system, such as camera parameters, humidity of the nail art area, etc.

[0159] Compared with the problems described in the background art, firstly, the system accurately obtains the nail art curing area and its environmental characteristics, extracts the irradiation parameters of the UV lamp, calculates the irradiation uniformity, ensures the uniform distribution of light during the curing process, thereby improving the curing quality. When the irradiation uniformity meets the preset threshold, the system automatically adjusts the parameters of the image acquisition module to ensure that the captured nail art images are clear and accurate, providing a reliable data basis for subsequent analysis. Secondly, by filtering the nail art images and combining with the nail art area recognition algorithm, the system can accurately extract the nail art application area images, providing a targeted analysis object for the AI nail art curing analysis model and improving the accuracy of curing state analysis. Furthermore, the application of the AI nail art curing analysis model enables the real-time monitoring of the curing state. Then, a relationship model between the curing state and the UV lamp irradiation parameters is established, and a UV lamp control algorithm is defined. These measures not only optimize the irradiation parameters of the UV lamp but also achieve the intelligent control of the curing process. Finally, by analyzing the curing data, the system can promptly detect curing anomalies and make adjustments according to the curing adaptive parameters to perform precise curing. This not only improves the curing quality of nail art products but also reduces rework and material waste caused by uneven curing or insufficient curing, lowers production costs, and improves customer satisfaction. Therefore, the present invention can improve the curing effect of nail art curing.

[0160] Embodiment 2:

[0161] As Figure 2 shown, it is a functional module diagram of a precise UV nail art curing system based on AI image recognition according to the present invention.

[0162] The precise UV nail art curing system 200 based on AI image recognition according to the present invention can be installed in an electronic device. According to the functions achieved, the precise UV nail art curing system based on AI image recognition can include an irradiation uniformity analysis module 201, a nail art image acquisition module 202, a nail art application area recognition module 203, a UV lamp control algorithm construction module 204, and a curing parameter optimization module 205. The modules in the present invention can also be referred to as units, which refer to a series of computer program segments that can be executed by the processor of an electronic device and can complete fixed functions, and are stored in the memory of the electronic device.

[0163] In the embodiments of the present invention, the functions of each module / unit are as follows:

[0164] The irradiation uniformity analysis module 201 is used to obtain the nail art curing area and its area environmental characteristics in the nail art curing system, extract the UV lamp irradiation parameters of the UV lamp in the nail art curing system, and calculate the irradiation uniformity of the UV lamp according to the UV lamp irradiation parameters;

[0165] The manicure image acquisition module 202 is configured to, when the irradiation uniformity meets a preset irradiation uniformity threshold, adjust the image acquisition parameters of the image acquisition module in the manicure curing system according to the regional environmental characteristics, and based on the image acquisition parameters, acquire a manicure image of the cured manicure in the manicure curing system;

[0166] The manicure application area recognition module 203 is configured to filter the manicure image to obtain a filtered manicure image, define a manicure area recognition algorithm for the filtered manicure image, and extract a manicure application area image of the filtered manicure image based on the manicure area recognition algorithm;

[0167] The UV lamp control algorithm construction module 204 is configured to analyze the curing state of the cured manicure through a trained AI manicure curing analysis model according to the manicure application area image, establish a state-UV lamp relationship model of the cured manicure through the curing state, and define a UV lamp control algorithm for the cured manicure based on the state-UV lamp relationship model;

[0168] The curing parameter optimization module 205 is configured to analyze the UV lamp irradiation optimization parameters of the UV lamp through the UV lamp control algorithm according to the curing state, perform continuous curing of the cured manicure based on the UV lamp irradiation optimization parameters to obtain curing data, analyze the curing abnormality of the cured manicure based on the curing data, analyze the curing adaptive parameters of the manicure curing system through the curing abnormality, and perform precise curing of the cured manicure based on the curing adaptive parameters.

[0169] Specifically, each module in the precise UV manicure curing system 200 based on AI image recognition in the embodiments of the present invention adopts the same technical means as those Figure 1 described in the precise UV manicure curing method based on AI image recognition above, and can produce the same technical effects, which will not be elaborated here.

[0170] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms.

[0171] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A precise UV nail curing method based on AI image recognition, characterized in that: The method comprises: Acquire nail curing areas and regional environmental characteristics in the nail curing system, extract UV lamp irradiation parameters of the UV lamp in the nail curing system, and calculate the irradiation uniformity of the UV lamp according to the UV lamp irradiation parameters; When the illumination uniformity meets a preset illumination uniformity threshold, adjusting the image acquisition parameters of the image acquisition module in the nail curing system according to the regional environmental characteristics, and acquiring a nail image of the nail curing system based on the image acquisition parameters; Filtering the nail art image to obtain a filtered nail art image, defining a nail art region recognition algorithm for the filtered nail art image, and extracting a nail art smear region image of the filtered nail art image based on the nail art region recognition algorithm; According to the nail art smear area image, the curing state of the cured nail art is analyzed by a trained AI nail art curing analysis model, and a state-UV lamp relationship model of the cured nail art is established through the curing state. Based on the state-UV lamp relationship model, a UV lamp control algorithm for the cured nail art is defined. The UV lamp control algorithm for the cured nail art based on the state-UV lamp relationship model includes: determining a curing attenuation coefficient of the cured nail art, and defining UV lamp control parameters for the cured nail art according to the state-UV lamp relationship model, wherein the UV lamp control parameters include irradiation intensity, irradiation angle, and irradiation time. Based on the irradiation intensity, the irradiation angle, the irradiation time, and the curing attenuation coefficient, the UV lamp control algorithm for the cured nail art is constructed using the following formula; wherein the UV lamp control algorithm: ； in, Indicates time The solidification state, Indicates time The solidification state, Indicates time The irradiation intensity at Indicates time The exposure time is Indicates time The irradiation angle is represents the curing attenuation coefficient, represents the time step; According to the curing state, the UV lamp control algorithm is used to analyze the UV lamp irradiation optimization parameters of the UV lamp, and the continuous curing of the cured nail art is performed based on the UV lamp irradiation optimization parameters to obtain curing data. Based on the curing data, the curing abnormality of the cured nail art is analyzed, and through the curing abnormality, the curing adaptive parameters of the nail art curing system are analyzed, and the precise curing of the cured nail art is performed based on the curing adaptive parameters.

2. The precise UV nail curing method based on AI image recognition according to claim 1, characterized in that: The step of calculating the irradiation uniformity of the UV lamp according to the UV lamp irradiation parameters includes: Determining an irradiation area of ​​the UV lamp according to the UV lamp irradiation parameters; Analyzing a UV lamp operating state of the UV lamp based on the UV lamp irradiation parameters; When the operating state of the UV lamp meets the preset operating state standard, the irradiation area is gridded to obtain a gridded irradiation area; Using a preset UV intensity meter to identify the UV intensity value of the regional grid corresponding to the gridded irradiation area; Based on the UV intensity value, the irradiation uniformity of the UV lamp is calculated.

3. The precise UV nail curing method based on AI image recognition as claimed in claim 2, characterized in that: The step of calculating the irradiation uniformity of the UV lamp based on the UV intensity value includes: Calculating the average intensity of the UV lamp according to the UV intensity value; Calculate the standard deviation of the UV lamp by the average intensity; Based on the average intensity and the standard deviation, the irradiation uniformity of the UV lamp is calculated using the following formula: ； in, Indicates the uniformity of UV light irradiation. Indicates the average intensity of UV light, Indicates UV lamp UV intensity value of the area grid, represents the standard deviation, Indicates the number of regional grids.

4. The precise UV nail curing method based on AI image recognition according to claim 1, characterized in that: When the illumination uniformity meets the preset illumination uniformity threshold, adjusting the image acquisition parameters of the image acquisition module in the nail curing system according to the regional environmental characteristics includes: When the irradiation uniformity meets a preset irradiation uniformity threshold, determining the light characteristics, visual characteristics and environmental characteristics of the irradiation area corresponding to the nail curing system according to the regional environmental characteristics; Analyzing the light environment of the illumination area based on the light characteristics; Determining the regional surface color and regional surface texture of the irradiated area through the visual features; Analyzing the regional temperature and regional humidity of the irradiated area according to the environmental characteristics; Defining image acquisition requirements for the irradiation area; Identify current image acquisition parameters of the image acquisition module; Analyze the image acquisition loss of the current acquisition parameters of the image in combination with the light environment, the surface color of the area, the surface texture of the area, the temperature of the area, the humidity of the area, and the image acquisition requirements; Based on the image acquisition loss, image acquisition parameters of the image acquisition module are defined.

5. The precise UV nail curing method based on AI image recognition according to claim 1, characterized in that: The step of extracting the nail art smearing area image of the filtered nail art image based on the nail art area recognition algorithm comprises: Gray-scale the filtered nail art image to obtain a gray-scale nail art image; Performing Gaussian blur on the grayscale nail art image to obtain a Gaussian blurred image; Marking the nail contour of the Gaussian blurred image using the nail region recognition algorithm; a maximum contour of a nail defining the contour of the nail; Establishing a contour mask of the maximum contour of the nail art, and extracting the nail art smear contour of the Gaussian blurred image based on the contour mask; Calculating a nail art completeness coefficient of the nail art smearing contour; When the nail art integrity coefficient meets a preset nail art integrity threshold, a nail art smearing area image of the filtered nail art image is extracted according to the nail art smearing contour.

6. The precise UV nail curing method based on AI image recognition according to claim 5, characterized in that: The step of marking the nail contour of the Gaussian blurred image by using the nail region recognition algorithm includes: Calculate the pixel gradient and pixel direction of the pixel point corresponding to the Gaussian blurred image; Determine a first adjacent pixel point and a second adjacent pixel point of the image pixel point according to the pixel direction; According to the first adjacent pixel point and the second adjacent pixel point, the suppression gradient of the image pixel point is calculated using the following formula: ； in, Represents image pixels The inhibition gradient, represents the first adjacent pixel, represents the second adjacent pixel, represents the pixel gradient of the first adjacent pixel, represents the pixel gradient of the second adjacent pixel, Represents image pixels The pixel gradient of Indicates and, To indicate otherwise; The nail contour of the Gaussian blurred image is determined according to the suppressed gradient.

7. The precise UV nail curing method based on AI image recognition according to claim 1, characterized in that: The step of analyzing the curing state of the cured nail art by using a trained AI nail art curing analysis model according to the nail art application area image includes: According to the nail art application area image, the curing features of the cured nail art are extracted using the feature extraction layer in the AI ​​nail art curing analysis model; Using the feature pooling layer in the AI ​​nail art curing analysis model to extract physical signs of the curing features, and obtain target curing features; Based on the target curing feature, the probability analysis layer in the AI ​​nail art curing analysis model is used to analyze the curing state probability of the curing nail art; The curing state of the cured nail art is determined according to the curing state probability.

8. The precise UV nail curing method based on AI image recognition according to claim 1, characterized in that: The step of analyzing the curing abnormality of the cured nail art based on the curing data includes: Preprocessing the solidified data to obtain preprocessed solidified data; Establishing an abnormality baseline for the cured nail art; According to the abnormality benchmark, identifying a curing abnormality pattern of the pre-processed curing data; extracting abnormal pattern features of the solidification abnormal pattern; Based on the abnormal pattern characteristics, the curing abnormality of the cured nail art is analyzed.

9. A precise UV nail curing system based on AI image recognition, characterized in that: The system comprises: An irradiation uniformity analysis module is used to obtain the nail curing area and its regional environmental characteristics in the nail curing system, extract the UV lamp irradiation parameters of the UV lamp in the nail curing system, and calculate the irradiation uniformity of the UV lamp according to the UV lamp irradiation parameters; A nail image acquisition module, configured to adjust image acquisition parameters of an image acquisition module in the nail curing system according to the regional environmental characteristics when the illumination uniformity meets a preset illumination uniformity threshold, and to acquire a nail image of the nails being cured in the nail curing system based on the image acquisition parameters; A nail art smear area recognition module, used for filtering the nail art image to obtain a filtered nail art image, defining a nail art area recognition algorithm for the filtered nail art image, and extracting a nail art smear area image of the filtered nail art image based on the nail art area recognition algorithm; A UV lamp control algorithm construction module is used to analyze the curing state of the curing nail art through the trained AI nail art curing analysis model according to the nail art smearing area image, establish the state-UV lamp relationship model of the curing nail art through the curing state, and define the UV lamp control algorithm of the curing nail art based on the state-UV lamp relationship model. The definition of the UV lamp control algorithm of the curing nail art based on the state-UV lamp relationship model includes: determining the curing attenuation coefficient of the curing nail art, and defining the UV lamp control parameters of the curing nail art according to the state-UV lamp relationship model, wherein the UV lamp control parameters include irradiation intensity, irradiation angle and irradiation time, and based on the irradiation intensity, the irradiation angle, the irradiation time and the curing attenuation coefficient, the UV lamp control algorithm of the curing nail art is constructed using the following formula; wherein the UV lamp control algorithm: ； in, Indicates time The solidification state, Indicates time The solidification state, Indicates time The irradiation intensity at Indicates time The exposure time is Indicates time The irradiation angle is represents the curing attenuation coefficient, represents the time step; A curing parameter optimization module is used to analyze the UV lamp irradiation optimization parameters of the UV lamp according to the curing state by using the UV lamp control algorithm, perform continuous curing of the cured nail art based on the UV lamp irradiation optimization parameters, obtain curing data, analyze the curing anomaly of the cured nail art based on the curing data, analyze the curing adaptive parameters of the nail art curing system through the curing anomaly, and perform precise curing of the cured nail art based on the curing adaptive parameters.

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