Intelligent unlocking method and image processing system for a villa intelligent lock

Abstract

The present invention discloses an intelligent unlocking method and an image processing system for a villa intelligent lock, which relates to the technical field of intelligent lock management; the intelligent unlocking method of the villa intelligent lock collects, identifies and analyzes the user images within the unlocking range of the designated villa door, and then realizes automatic unlocking before the user arrives at the door; the image processing system analyzes the images of the target user each time when the target user is enabled within the specified period, and then automatically corrects the standard face model of the target user in the intelligent lock, solves the deficiencies existing in the current technology, realizes the intelligence and automation of face recognition unlocking of the intelligent lock, greatly reduces the waiting time of villa users when unlocking, and at the same time increases the frequency of villa users using face recognition unlocking, improves the experience of villa users when using face recognition unlocking, and is also conducive to increasing the reputation of intelligent lock manufacturers to a certain extent.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent lock management, and particularly to an intelligent unlocking method and an image processing system for a villa intelligent lock. Background Art

[0002] Intelligent locks are widely favored by users due to their advantages of convenience and security, especially by villa users. Intelligent locks have multiple unlocking methods, among which face recognition unlocking is a relatively commonly used unlocking method for villa users. Therefore, in order to ensure the safety and convenience of villa users when using face recognition to unlock the lock, it is necessary to analyze the face images when the intelligent lock unlocks.

[0003] In the current technology, when an intelligent lock uses face recognition to unlock, the intelligent lock first recognizes the face of the user in front of the door and then unlocks the lock. Obviously, this unlocking method has at least the following problems: 1. In the current technology, the user needs to reach in front of the door before the intelligent lock can collect the user's image. It does not collect and recognize the images of the people within the unlocking range outside the door. Therefore, when the user reaches the door, the intelligent lock cannot be unlocked in a timely manner, the face unlocking time of the user cannot be reduced, and the convenience and automation of the intelligent lock cannot be improved. On the other hand, there are no multiple cameras set to collect the user's images, so it is impossible to clearly collect the user's images when other cameras are damaged or in special weather conditions, further reducing the unlocking effect of the intelligent lock and also unable to improve the user experience when unlocking the intelligent lock.

[0004] 2. In the current technology, the standard face model of the user in the intelligent lock is fixed and cannot be automatically corrected according to the regular changes of the user's face. This reduces the accuracy of subsequent users when using face recognition to unlock, increases the face recognition time of the intelligent lock, resulting in a decline in the face recognition effect of the intelligent lock, and further reducing the frequency of users using face recognition to unlock. At the same time, the intelligence of the intelligent lock cannot be improved. Summary of the Invention

[0005] In order to solve the above problems, the purpose of the present invention is to provide an intelligent unlocking method and an image processing system for a villa intelligent lock.

[0006] To solve the above technical problems, the present invention adopts the following technical solutions: In the first aspect, the present invention provides an intelligent unlocking method for a villa intelligent lock, and the intelligent unlocking method for the villa intelligent lock includes:

[0007] Step 1: User image collection: When the target user reaches the first preset range of the specified villa, collect each image corresponding to the specified target user through the specified high-definition camera on the specified villa door;

[0008] Step 2. Smart lock opening analysis: Analyze the quality of each image corresponding to the target user. If the quality of all images of the target user is unqualified, execute Step 3. If the quality of a certain image of the target user is qualified, analyze the opening permission of the target user for the specified villa door. If the target user has no opening permission for the specified villa door, the smart lock in the specified villa door will not be opened. If the target user has an opening permission for the specified villa door, analyze the opening time of the smart lock in the specified villa door;

[0009] Step 3. User target image acquisition: When the target user reaches the second preset range of the specified villa door of the specified villa, collect each target image of the target user through the specified TOF camera installed in the specified villa door;

[0010] Step 4. User target image processing: Based on each target image of the target user, analyze the opening permission of the target user for the specified villa door. If it is determined that the target user has no opening permission for the specified villa door, the smart lock in the specified villa door will not be opened. If it is determined that the target user has an opening permission for the specified villa door, analyze the second opening time of the smart lock in the specified villa door;

[0011] Step 5. Villa door opening: When the target user has an opening permission, the specified villa door opens the villa door according to its corresponding opening time or the second opening time.

[0012] Optionally, collect each image corresponding to the specified target user. The specific collection steps are as follows:

[0013] A1. Detect the first preset range of the specified villa through the infrared detector installed in the specified villa door of the specified villa. When the target person enters the first preset range of the specified villa, obtain the position corresponding to the target person, and at the same time wake up the target high-definition camera in the specified villa door;

[0014] A2. Adjust the shooting position of the target high-definition camera in the specified villa door according to the position corresponding to the target person, and then collect each image of the target user through the target high-definition camera in the specified villa door.

[0015] Optionally, analyze the quality of each image corresponding to the target user. The specific analysis process is as follows:

[0016] Obtain the pixel value and resolution corresponding to each image from each image corresponding to the target user, and mark them as X i and F i , where i represents the number corresponding to each image, i = 1, 2......n, and then substitute it into the calculation formula to obtain the clear evaluation coefficient of each image corresponding to the target user Where X and F are respectively the set standard pixel value and standard resolution of the image, and ε1 and ε2 are respectively the weight factors corresponding to the set pixel value and resolution;

[0017] Compare the clarity evaluation coefficients of each image corresponding to the target user with the set standard clarity evaluation coefficient of the image. If the clarity evaluation coefficients of each image corresponding to the target user are all less than the standard clarity evaluation coefficient of the image, it is determined that the quality of each image of the target user is unqualified. If the clarity evaluation coefficient of a certain image corresponding to the target user is greater than or equal to the standard clarity evaluation coefficient of the image, it is determined that the quality of this image of the target user is unqualified.

[0018] Optionally, analyze the opening time of the intelligent lock in the specified villa door. The specific analysis process is as follows:

[0019] Obtain the shooting time points of each image corresponding to the target user, and at the same time obtain the position of the target user in each image, and then analyze the speed of each image corresponding to the target user, and denote it as v i ;

[0020] Based on the position of the target user in each image, obtain the distance between the target user and the specified villa door in each image, and denote it as L i , and at the same time obtain the opening duration corresponding to the specified villa door, marked as ΔT;

[0021] Through the calculation formula Get the opening time of the intelligent lock in the specified villa door, where T i represents the shooting time point of the i-th image corresponding to the target user, L is the length of the second preset range of the specified villa door, n represents the number of images, a represents a natural number, and γ is the correction factor corresponding to the set user arrival duration.

[0022] The second aspect of the present invention provides a video image processing system for an intelligent lock, including: an image acquisition module for acquiring the face images and times of the target user corresponding to the intelligent lock in the specified villa door of the specified villa during each activation within a specified period;

[0023] An image analysis module for analyzing the face change evaluation coefficient of the target user within a specified period according to the face images and times of the target user during each activation;

[0024] A face model modification module for judging the face change situation of the target user within a specified period. If the face of the target user within the specified period is in a changing state, analyze the modification information of the standard face model corresponding to the target user within the specified period, and automatically modify the standard face model corresponding to the target user;

[0025] An intelligent lock management database is used to store the corresponding standard light intensity, standard light brightness, and standard light color temperature during image capture, store the face images and times of the target users corresponding to the intelligent lock in the specified villa door of the specified villa during each activation within a specified period, and store the standard face models of the target users.

[0026] Optionally, analyze the face change evaluation coefficient of the target user within a specified period. The specific analysis process is as follows:

[0027] Based on the time of each activation of the target user, extract the corresponding environmental information at each activation. The environmental information includes light intensity, weather condition, light brightness, and light color temperature. Then, analyze and obtain the environmental impact factors corresponding to the face images of the target user at each activation, and mark them as δ j , where j represents the number corresponding to each activation, j = 1, 2......m;

[0028] Divide the face of the target user into preset regions to obtain each sub-region. Then, set up monitoring points in each sub-region. Thus, obtain the RGB values of each monitoring point in each sub-region of the face image corresponding to the target user at each activation in the face image of the target user at each activation, and mark them as and where u represents the number corresponding to each sub-region, u = 1, 2......p, and f represents the number corresponding to each monitoring point, f = 1, 2......q;

[0029] Extract the standard face model of the target user from the intelligent lock management database. Then, obtain the standard RGB values of each monitoring point in each sub-region from the standard face model of the target user, and mark them as and

[0030] Through the calculation formula

[0031] Obtain the face change evaluation coefficient β of the target user within a specified period. Among them, ΔR, ΔG, and ΔB are the change values of the set user face permission R value, permission G value, and permission B value respectively, γ1, γ2, and γ3 are the weight factors corresponding to the set face R value, face G value, and face B value respectively, η is the set face color change correction factor, and e is the natural constant.

[0032] Optionally, analyze the environmental impact factors corresponding to the face images of the target user at each activation. The specific analysis process is as follows:

[0033] Extract the corresponding standard light intensity, standard light brightness, and standard light color temperature at the time of image capture from the intelligent lock management database, and label them as Z, GD, and W. Compare the weather conditions of the target user at each activation with the color influence factors corresponding to the set weather conditions to obtain the color influence factors corresponding to the weather conditions of the target user at each activation, denoted as κ j ;

[0034] Through the calculation formula

[0035] Obtain the environmental influence factor δ corresponding to the face image of the target user at each activation j , where Z j , GD j , W j respectively represent the light intensity, light brightness, and light color temperature corresponding to the target user at the j-th activation. ΔZ, ΔGD, and ΔW are the set image permission light intensity, permission light brightness difference, and permission light color temperature difference respectively. μ1, μ2, μ3, and μ4 are the set weight factors corresponding to the light intensity, color influence factor of the weather condition, light brightness, and light color temperature respectively. e represents the natural constant.

[0036] Optionally, judge the change situation of the face corresponding to the target user within a specified period. The specific analysis process is as follows: Compare the face change evaluation coefficient of the target user within the specified period with the set standard face change evaluation coefficient. If the face change evaluation coefficient of the target user within the specified period is greater than or equal to the standard face change evaluation coefficient, it is judged that the face corresponding to the target user within the specified period is in a changing state; otherwise, it is judged that the face corresponding to the target user within the specified period is in a stable state.

[0037] Optionally, analyze the modification information of the standard face model corresponding to the target user within a specified period. The specific analysis process is as follows:

[0038] Substitute the RGB values of each monitoring point in each sub-region of the face image corresponding to the target user at each activation into the calculation formula

[0039] to obtain the RGB value change rate of each monitoring point in each sub-region of the face image corresponding to the target user at each activation where respectively represent the R value, G value, and B value of the f-th monitoring point in the u-th sub-region of the face image corresponding to the target user at the (j - 1)-th activation, is the set change rate correction factor, a2 represents a natural number, T j , T (j-1)respectively represent the time corresponding to the j-th and (j - 1)-th activations of the target user, and m represents the number of activations;

[0040] According to the duration corresponding to the specified period and the RGB value change rate of each monitoring point in each sub-region of the face image corresponding to the target user at each activation, obtain the RGB change value of each monitoring point in each sub-region of the face image corresponding to the target user within the specified period, and use it as the modification information of the standard face model corresponding to the target user within the specified period.

[0041] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0042] 1. The present invention provides an intelligent unlocking method and an image processing system for a villa intelligent lock. By collecting the user images within the unlocking range of the specified villa door, automatic unlocking is performed before the user arrives at the door; at the same time, the images of the target user at each activation within the specified period are analyzed, and the standard face model of the target user in the intelligent lock is automatically corrected, solving the deficiencies of the current technology, realizing the intelligence and automation of face recognition unlocking of the intelligent lock, greatly reducing the waiting time of villa users when unlocking, and at the same time increasing the frequency of villa users using face recognition unlocking, improving the experience of villa users when using face recognition unlocking, and to a certain extent, it is also beneficial to increase the reputation of the intelligent lock manufacturer.

[0043] 2. In an intelligent unlocking method of a villa intelligent lock, the present invention collects and identifies the images of people within the unlocking range outside the villa door, and at the same time sets multiple cameras to collect the user images, effectively avoiding the problems of damage to other cameras or low clarity of the user face images collected in special weather, greatly improving the efficiency and effect of face recognition unlocking of the intelligent lock, and at the same time effectively improving the convenience of face recognition unlocking of the intelligent lock.

[0044] 3. In a video image processing system of an intelligent lock, the present invention analyzes the face images of the target user corresponding to the intelligent lock in the specified villa door of the specified villa at each activation within the specified period, and then automatically corrects the standard face model of the target user, effectively improving the accuracy of the face recognition result when the subsequent user uses face recognition unlocking, and at the same time reflecting the flexibility of the intelligent lock, providing a comfortable life for villa users. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0046] Figure 1 Schematic diagram of the implementation steps of the method of the present invention;

[0047] Figure 2 Schematic diagram of the connection structure of the system modules of the present invention. Detailed implementation manners

[0048] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0049] As shown in an embodiment of the present invention Figure 1 A smart unlocking method for a villa smart lock, the method includes the following steps: Step 1, user image acquisition: When the target user reaches the first preset range of the specified villa, collect each image corresponding to the specified target user through the specified high-definition camera on the specified villa door;

[0050] It should be noted that the first preset range of the specified villa is the range from five meters to two meters outside the specified villa door.

[0051] In a specific embodiment, to collect each image corresponding to the specified target user, the specific collection steps are as follows: A1. Detect the first preset range of the specified villa through the infrared detector installed in the specified villa door of the specified villa. When the target person enters the first preset range of the specified villa, obtain the position corresponding to the target person, and at the same time wake up the target high-definition camera in the specified villa door;

[0052] A2. Adjust the shooting position of the target high-definition camera in the specified villa door according to the position corresponding to the target person, and then collect each image of the target user through the target high-definition camera in the specified villa door.

[0053] The embodiment of the present invention detects the first preset range of the specified villa through the infrared detector, wakes up the target high-definition camera when a person is detected, effectively saves the working duration of the camera, increases the service life of the camera, and also saves the power consumption during the idle period of the camera.

[0054] Step 2. Smart lock opening analysis: Analyze the quality of each image corresponding to the target user. If the quality of all images of the target user is unqualified, then execute Step 3. If the quality of a certain image of the target user is qualified, then analyze the opening permission of the target user for the specified villa door. If the target user has no opening permission for the specified villa door, then the smart lock in the specified villa door will not be opened. If the target user has an opening permission for the specified villa door, then analyze the opening time of the smart lock in the specified villa door;

[0055] In a specific embodiment, the analysis of the quality of each image corresponding to the target user is as follows: Obtain the pixel values and resolutions corresponding to each image from each image corresponding to the target user, and mark them as X i and F i , where i represents the number corresponding to each image, i = 1, 2......n, and then substitute it into the calculation formula to obtain the clarity evaluation coefficient of each image corresponding to the target user where X and F are the set standard pixel value and standard resolution of the image respectively, and ε1 and ε2 are the weight factors corresponding to the set pixel value and resolution respectively;

[0056] Compare the clarity evaluation coefficient of each image corresponding to the target user with the set standard clarity evaluation coefficient of the image. If the clarity evaluation coefficient of each image corresponding to the target user is less than the standard clarity evaluation coefficient of the image, it is determined that the quality of all images of the target user is unqualified.

[0057] In another specific embodiment, the analysis of the opening permission of the target user for the specified villa door is as follows: Extract the face image of the target user from each image corresponding to the target user, and compare it with the standard face models corresponding to each user in the specified villa door in the smart lock management database within a specified period. If the face image of the target user is the same as the standard face model corresponding to a certain user, it is determined that the target user has an opening permission for the specified villa door. If the face image of the target user is different from the standard face models corresponding to each user, it is determined that the target user has no opening permission for the specified villa door.

[0058] In yet another specific embodiment, the analysis of the opening time of the smart lock in the specified villa door is as follows: Obtain the shooting time points of each image corresponding to the target user, and at the same time obtain the position of the target user in each image, and then analyze to obtain the speed of each image corresponding to the target user, and record it as v i ;

[0059] It should be noted that obtain the shooting time points of each image corresponding to the target user from the smart lock management background, and obtain the position of the target user in each image from each image corresponding to the target user.

[0060] Among the above, the speed of the target user corresponding to each image is analyzed. The specific analysis process is as follows: Based on the time of the target user in each image, the shooting interval between each image of the target user and the image taken at the adjacent shooting time is obtained. Then, according to the position of the target user in each image, the walking distance of the target user between each image and the image taken at the adjacent shooting time is obtained. Divide the walking distance of the target user between each image and the image taken at the adjacent shooting time by the corresponding shooting interval to obtain the speed of the target user corresponding to each image.

[0061] It should be noted that the number of images corresponding to the target user above is greater than 1. If the number of images corresponding to the target user is 1, the speed of the image corresponding to the target user is recorded as a, where a is a natural number.

[0062] Based on the position of the target user in each image, the distance between the target user and the specified villa door in each image is obtained and denoted as L i , and at the same time, the opening duration corresponding to the specified villa door is obtained and marked as ΔT;

[0063] Through the calculation formula the opening time of the intelligent lock in the specified villa door is obtained, where T i represents the shooting time point of the i-th image corresponding to the target user, L is the length of the second preset range of the specified villa door, n represents the number of images, a represents a natural number, and γ is a correction factor corresponding to the set user arrival duration.

[0064] Step 3: User target image acquisition: When the target user reaches the second preset range of the specified villa door of the specified villa, each target image of the target user is collected through the specified TOF camera installed in the specified villa door;

[0065] It should be noted that the second preset range of the specified villa is the range within two meters outside the specified villa door and including two meters.

[0066] Among the above, the specific process of Step 3: User target image acquisition is as follows: When each image corresponding to the target user is unqualified, the second preset range of the specified villa is detected through the infrared detector installed in the specified villa door of the specified villa. When the target person enters the second preset range of the specified villa, the position corresponding to the target person is obtained, and at the same time, the specified TOF camera in the specified villa door is awakened;

[0067] According to the position corresponding to the target person, the shooting position of the specified TOF camera in the specified villa door is adjusted, and then each target image of the target user is collected through the specified TOF camera in the specified villa door.

[0068] Step 4. Target user image processing: Based on the target images of the target user, analyze the opening permission of the target user for the specified villa door. If it is determined that the target user has no opening permission for the specified villa door, the smart lock in the specified villa door will not be opened. If it is determined that the target user has an opening permission for the specified villa door, analyze the second opening time of the smart lock in the specified villa door.

[0069] In a specific embodiment, the analysis of the opening permission of the target user for the specified villa door is as follows: Obtain the target face image of the target user from each target image corresponding to the target user, and then compare it with the standard face models corresponding to each user in the specified villa door within a specified period in the smart lock management database. If the target face image of the target user is the same as the standard face model corresponding to a certain user, it is determined that the target user has an opening permission for the specified villa door. If the target face image of the target user is different from all the standard face models corresponding to the users, it is determined that the target user has no opening permission for the specified villa door.

[0070] In another specific embodiment, the analysis of the second opening time of the smart lock in the specified villa door is as follows: Analyze and obtain the second opening time of the smart lock in the specified villa door according to the analysis method of the opening time of the smart lock in the specified villa door.

[0071] Step 5. Villa door opening: When the target user has an opening permission, the specified villa door opens according to its corresponding opening time or the second opening time.

[0072] In the intelligent unlocking method of a villa smart lock of the present invention, by collecting and identifying the images of the personnel within the unlocking range outside the villa door, and setting multiple cameras to collect the images of the users, the problem that the user face images collected when other cameras are damaged or in special weather are not clear is effectively avoided, the efficiency and effect of face recognition unlocking of the smart lock are greatly improved, and the convenience of face recognition unlocking of the smart lock is also effectively improved.

[0073] As shown in an embodiment of the present invention Figure 2 A video image processing system of a smart lock includes an image acquisition module, an image analysis module, a face model modification module, and a smart lock management database.

[0074] The smart lock management database is respectively connected to the image acquisition module, the image analysis module, and the face model modification module, and the image analysis module is also respectively connected to the image acquisition module and the face model modification module.

[0075] The image acquisition module is used to acquire the face images and times of the target user corresponding to the smart lock in the specified villa door of the specified villa during each activation within a specified period.

[0076] Among the above, obtain the face images and times of the target users corresponding to the intelligent locks in the specified villa doors of the specified villa within the specified period from the intelligent lock management database.

[0077] An image analysis module, configured to analyze the face change evaluation coefficient of the target user within the specified period according to the face images and times of the target user at each activation;

[0078] In a specific embodiment, to analyze the face change evaluation coefficient of the target user within the specified period, the specific analysis process is as follows: Based on the times of the target user at each activation, extract the corresponding environmental information at each activation, where the environmental information includes light intensity, weather condition, light brightness, and light color temperature, and then analyze to obtain the environmental impact factor corresponding to the face image of the target user at each activation, and mark it as δ j , where j represents the number corresponding to each activation, j = 1, 2......m;

[0079] Divide the face of the target user according to a preset area to obtain each sub-area, and then arrange each monitoring point in each sub-area. Thus, obtain the RGB values of each monitoring point in each sub-area of the face image corresponding to the target user at each activation in the face image of the target user at each activation, and mark them respectively as and where u represents the number corresponding to each sub-area, u = 1, 2......p, and f represents the number corresponding to each monitoring point, f = 1, 2......q;

[0080] Extract the standard face model of the target user from the intelligent lock management database, and then obtain the standard RGB values of each monitoring point in each sub-area from the standard face model of the target user, and mark them respectively as and

[0081] Through the calculation formula

[0082] Obtain the face change evaluation coefficient β of the target user within the specified period, where ΔR, ΔG, and ΔB are the change values of the set permitted R value, permitted G value, and permitted B value of the user's face respectively, γ1, γ2, and γ3 are the weight factors corresponding to the set face R value, face G value, and face B value respectively, η is the set face color change correction factor, and e is the natural constant.

[0083] In another specific embodiment, the environmental impact factors corresponding to the face images of the target user at each activation are used for analysis. The specific analysis process is as follows: Extract the corresponding standard light intensity, standard light brightness, and standard light color temperature at the time of image shooting from the intelligent lock management database, and mark them as Z, GD, and W. Compare the weather conditions of the target user at each activation with the corresponding color impact factors of each set weather condition to obtain the color impact factors corresponding to the weather conditions of the target user at each activation, denoted as κ. j ;

[0084] Through the calculation formula

[0085] Obtain the environmental impact factor δ corresponding to the face image of the target user at each activation. j , where Z j , GD j , W j respectively represent the light intensity, light brightness, and light color temperature corresponding to the target user at the j-th activation. ΔZ, ΔGD, and ΔW are the set image permission light intensity, permission light brightness difference, and permission light color temperature difference respectively. μ1, μ2, μ3, and μ4 are the set weight factors corresponding to the light intensity, color impact factor of the weather condition, light brightness, and light color temperature respectively. e represents the natural constant.

[0086] In the embodiment of the present invention, by analyzing the environmental impact factors corresponding to the face images of the target user at each activation, the changes in the face in the image caused by environmental factors are effectively eliminated, and the reliability and authenticity of the analysis results of the face change evaluation coefficient are increased.

[0087] The face model modification module is used to judge the face change situation of the target user within a specified period. If the face of the target user within the specified period is in a changing state, analyze the modification information of the standard face model corresponding to the target user within the specified period, and automatically modify the standard face model corresponding to the target user.

[0088] In a specific embodiment, to judge the face change situation of the target user within a specified period, the specific analysis process is as follows: Compare the face change evaluation coefficient of the target user within the specified period with the set standard face change evaluation coefficient. If the face change evaluation coefficient of the target user within the specified period is greater than or equal to the standard face change evaluation coefficient, it is judged that the face of the target user within the specified period is in a changing state; otherwise, it is judged that the face of the target user within the specified period is in a stable state.

[0089] In another specific embodiment, the change information of the standard face model corresponding to the target user within a specified period is analyzed. The specific analysis process is as follows: Substitute the RGB values of each monitoring point in each sub-region of the face image corresponding to the target user at each activation into the calculation formula to obtain the RGB value change rate of each monitoring point in each sub-region of the face image corresponding to the target user at each activation where respectively represent the R value, G value, and B value of the f-th monitoring point in the u-th sub-region of the face image corresponding to the target user at the (j - 1)-th activation, is the set change rate correction factor, a2 represents a natural number, T j 、T (j-1) respectively represent the time corresponding to the target user at the j-th and (j - 1)-th activations, and m represents the number of activations;

[0090] According to the duration corresponding to the specified period and the RGB value change rate of each monitoring point in each sub-region of the face image corresponding to the target user at each activation, obtain the RGB change value of each monitoring point in each sub-region of the face image corresponding to the target user within the specified period, and use it as the change information of the standard face model corresponding to the target user within the specified period.

[0091] In the above, the RGB value change rate of each monitoring point in each sub-region of the face image corresponding to the target user at each activation is calculated by averaging to obtain the average RGB value change rate of each monitoring point in each sub-region of the face image corresponding to the target user, and then multiply it by the duration corresponding to the specified period to obtain the RGB change value of each monitoring point in each sub-region of the face image corresponding to the target user within the specified period.

[0092] The intelligent lock management database is used to store the corresponding standard light intensity, standard light brightness, and standard light color temperature during image capture, store the face images and times of the intelligent lock corresponding to the target user at each activation in the specified villa door of the specified villa within the specified period, and store the standard face model of the target user.

[0093] In the video image processing system of an intelligent lock, the present invention analyzes the face images of the intelligent lock corresponding to the target user at each activation in the specified villa door of the specified villa within the specified period, and then automatically corrects the standard face model used by the target user, effectively improving the accuracy of the face recognition result when the subsequent user uses face recognition to unlock the lock. At the same time, it also reflects the flexibility of the intelligent lock and provides a comfortable life for villa users.

[0094] In the embodiment of the present invention, by collecting the user images within the unlocking range of the specified villa door, automatic unlocking is performed before the user arrives at the door; at the same time, the images of the target user each time when enabled within the specified period are analyzed, and then the standard face model of the target user in the intelligent lock is automatically corrected, which solves the deficiencies of the current technology, realizes the intelligence and automation of face recognition unlocking of the intelligent lock, greatly reduces the waiting time of villa users when unlocking, increases the frequency of villa users using face recognition unlocking, improves the experience of villa users when using face recognition unlocking, and is also conducive to enhancing the reputation of intelligent lock manufacturers to a certain extent.

[0095] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these changes and modifications.

Claims

1. An intelligent unlocking method for a villa intelligent lock, characterized in that The method includes the following steps: Step 1, user image acquisition: When the target user reaches the first preset range of the specified villa, capture each image corresponding to the specified target user through the specified high-definition camera on the door of the specified villa; Step 2, intelligent lock opening analysis: Analyze the quality of each image corresponding to the target user. If the quality of each image of the target user is unqualified, then execute Step 3. If the quality of a certain image of the target user is qualified, then analyze the opening permission of the target user for the specified villa door. If the target user has no opening permission for the specified villa door, the intelligent lock in the specified villa door will not open. If the target user has an opening permission for the specified villa door, then analyze the opening time of the intelligent lock in the specified villa door; The analysis of the opening time of the intelligent lock in the specified villa door is specifically as follows: Obtain the shooting time points of each image corresponding to the target user, and at the same time obtain the position of the target user in each image, and then analyze and obtain the speed of the target user corresponding to each image, denoted as v i , where i represents the number corresponding to each image, i = 1, 2......n; Based on the position of the target user in each image, obtain the distance between the target user and the specified villa door in each image, and denote it as L i , and at the same time obtain the opening duration corresponding to the specified villa door, marked as ΔT; By using the calculation formula the opening time of the intelligent lock in the specified villa door is obtained, where T i represents the shooting time point of the i-th image corresponding to the target user, L is the length of the second preset range of the specified villa door, n represents the number of images, a represents a natural number, and γ is a correction factor corresponding to the set user arrival duration; Step 3, user target image acquisition: When the target user reaches the second preset range of the specified villa door of the specified villa, capture each target image of the target user through the specified TOF camera installed in the specified villa door; Step 4, user target image processing: Based on each target image of the target user, analyze the opening permission of the target user for the specified villa door. If it is determined that the target user has no opening permission for the specified villa door, the intelligent lock in the specified villa door will not open. If it is determined that the target user has an opening permission for the specified villa door, then analyze the second opening time of the intelligent lock in the specified villa door; Step 5, villa door opening: When the target user has an opening permission, the specified villa door opens the villa door according to its corresponding opening time or the second opening time.

2. The intelligent unlocking method of a villa intelligent lock according to claim 1, characterized in that, The specific steps for capturing each image corresponding to the specified target user are as follows: A1. Detect the first preset range of the specified villa through the infrared detector installed in the specified villa door of the specified villa. When the target person enters the first preset range of the specified villa, obtain the position corresponding to the target person, and at the same time wake up the target high-definition camera in the specified villa door; A2. Adjust the shooting position of the target high-definition camera in the specified villa door according to the position corresponding to the target person, and then capture each image of the target user through the target high-definition camera in the specified villa door.

3. The intelligent unlocking method of a villa intelligent lock according to claim 2, characterized in that, The analysis of the quality of each image corresponding to the target user is specifically as follows: Obtain the pixel values and resolutions corresponding to each image of the target user, and label them as X i and F i , and then substitute them into the calculation formula to obtain the clarity evaluation coefficients of each image corresponding to the target user where X and F are the set standard pixel value and standard resolution of the image respectively, and ε1 and ε2 are the weight factors corresponding to the set pixel value and resolution respectively; Compare the clarity evaluation coefficient of each image corresponding to the target user with the set image standard clarity evaluation coefficient. If the clarity evaluation coefficient of each image corresponding to the target user is less than the image standard clarity evaluation coefficient, it is determined that the quality of each image of the target user is unqualified. If the clarity evaluation coefficient of a certain image corresponding to the target user is greater than or equal to the image standard clarity evaluation coefficient, it is determined that the quality of this image of the target user is qualified.

Images