CN113034769A - Access control system and method based on face recognition - Google Patents
Access control system and method based on face recognition Download PDFInfo
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- CN113034769A CN113034769A CN202110234926.7A CN202110234926A CN113034769A CN 113034769 A CN113034769 A CN 113034769A CN 202110234926 A CN202110234926 A CN 202110234926A CN 113034769 A CN113034769 A CN 113034769A
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
- G07C9/30—Individual registration on entry or exit not involving the use of a pass
- G07C9/32—Individual registration on entry or exit not involving the use of a pass in combination with an identity check
- G07C9/37—Individual registration on entry or exit not involving the use of a pass in combination with an identity check using biometric data, e.g. fingerprints, iris scans or voice recognition
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
- G07C9/30—Individual registration on entry or exit not involving the use of a pass
- G07C9/38—Individual registration on entry or exit not involving the use of a pass with central registration
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Abstract
The invention discloses an entrance guard control system and method based on face recognition, which comprises the following steps: after a first session key between the camera and the intelligent gateway is obtained, sending a face image; calculating a face characteristic value based on the face image, and comparing the face characteristic value with a characteristic value in a preset face database to obtain a face recognition result; obtaining an access control operation command according to the face recognition result, and sending the access control operation command to an intelligent access control; and after the second session key is obtained, receiving the entrance guard operation command, and decrypting the received entrance guard operation by using the second session key. By adopting the technical scheme of the invention, the method has the characteristics of higher safety and better experience.
Description
Technical Field
The invention belongs to the technical field of entrance guard, and particularly relates to an entrance guard control system and method based on face recognition.
Background
The entrance guard unblock mode is constantly changing, develops electronic trick lock by the key unblock of mechanical type, and fingerprint entrance guard appears again at present, and the back that the unblock mode was evolved is the progress of technique on the one hand, and on the other hand is that people have higher and higher demands to the security of lock and the user experience of lock. The entrance guard in the form of keys and passwords is more traditional, the safety is lower, and the experience is general; fingerprint entrance guard unlocks through the user fingerprint, and the user need not to carry the key, also need not to remember the password, and security and experience are higher than traditional lock slightly, but can face some problems equally, for example the misconception rate is high, and the user finger desquamation, have water etc. to make the unblock unsuccessful, also can't the unblock when both hands are occupied, lead to present fingerprint intelligence lock to be difficult to popularize.
Disclosure of Invention
The invention aims to provide an entrance guard control system and method based on face recognition, which have higher safety and better experience.
In order to achieve the purpose, the invention adopts the following technical scheme:
the utility model provides an access control system based on face identification, includes: intelligent gateway, camera and intelligent entrance guard, intelligent gateway contains: a recognition device and a micro-control device, wherein,
the camera is used for sending a face image after acquiring a first session key between the camera and the intelligent gateway;
the recognition device is used for receiving the face image sent by the camera, calculating a face characteristic value based on the face image, and comparing the face characteristic value with a characteristic value in a preset face database to obtain a face recognition result;
the micro-control device obtains an access control operation command according to the face recognition result and sends the access control operation command to the intelligent access control; the access control operation command is obtained by encrypting the face recognition result by using a second session key; the second session key is a session key between the intelligent gateway and the intelligent access control;
and the intelligent access control is used for receiving the access control operation command after the second session key is obtained, decrypting the received access control operation command by using the second session key to obtain a face recognition result, and performing access control operation according to the face recognition result.
Preferably, the identification means comprises:
the model establishing module is used for establishing a face recognition model comprising a preset weighted convolution structure;
the data training module is used for inputting data to be trained to the face recognition model for training so as to obtain a characteristic value of the data to be trained, and storing the characteristic value in a database;
the characteristic identification module is used for inputting the collected face image into the face identification model so as to obtain the characteristics of the collected face image;
and the face recognition module is used for calculating the similarity between the characteristics of the acquired face image and the characteristic value of each image in the database based on the characteristic values stored in the database, and obtaining a face recognition result according to the similarity.
Preferably, the preset weighted convolution structure includes: the convolution layer processing system comprises at least two convolution layers, wherein the at least two convolution layers operate in parallel, and the output result of the parallel operation of the at least two convolution layers is the para-position addition of the results of the at least two parallel convolution characteristic graphs.
Preferably, the model building module is specifically configured to: and replacing the common convolutional layer or the depth separable convolutional layer in the convolutional neural network model by the preset weighted convolutional structure.
Preferably, the camera is specifically configured to obtain the first session key with the smart gateway by:
generating a camera random number, and sending a gateway identity authentication command to the micro-control device, wherein the gateway identity authentication command comprises the camera random number;
receiving a response command returned by the micro-control device, and performing identity verification on the intelligent gateway by using response data in the response command;
if the intelligent gateway is confirmed to pass the identity authentication, sending a camera identity authentication command to the micro control device, so that the micro control device obtains a first session key encrypted by a camera public key after confirming that the camera passes the identity authentication, and sending the encrypted first session key to the camera; the camera identity authentication command comprises a camera public key;
and decrypting the received encrypted first session key by using a prestored camera private key to obtain the first session key.
Preferably, the intelligent access control is further configured to encrypt an access control operation result with the second session key after the access control operation is performed, so as to obtain an access control operation response command; sending the access control operation response command to the micro-control device;
and the micro-control device is also used for receiving the access control operation response command, and decrypting the access control operation response command by using the second session key through the security element to obtain an access control decryption result.
The invention also provides an access control method based on face recognition, which comprises the following steps:
step 1, sending a face image after a first session key between a camera and an intelligent gateway is obtained;
step 2, calculating a face characteristic value based on the face image, and comparing the face characteristic value with a characteristic value in a preset face database to obtain a face recognition result;
step 3, obtaining an access control operation command according to the face recognition result, and sending the access control operation command to an intelligent access control; the access control operation command is obtained by encrypting the face recognition result by using a second session key; the second session key is a session key between the intelligent gateway and the intelligent entrance guard;
and 4, after the second session key is obtained, receiving the access control operation command, decrypting the received access control operation command by using the second session key to obtain a face recognition result, and performing access control operation according to the face recognition result.
Preferably, step 2 specifically comprises:
establishing a face recognition model comprising a preset weighted convolution structure;
inputting data to be trained to the face recognition model for training to obtain a characteristic value of the data to be trained, and storing the characteristic value in a database;
inputting the collected face image into the face recognition model to obtain the characteristics of the collected face image;
and calculating the similarity between the characteristics of the acquired face image and the characteristic value of each image in the database based on the characteristic values stored in the database, and obtaining a face recognition result according to the similarity.
The technical scheme of the invention can carry out characteristic value comparison in the intelligent gateway to obtain the face recognition result, thereby improving the safety of the face recognition result, and the camera and the intelligent access control communicate with the intelligent gateway after obtaining the session key between the intelligent gateways, thereby improving the safety of the whole face recognition and access control operation process.
Furthermore, the invention carries out face recognition based on the face recognition model with the preset weighted convolution structure, thereby obviously improving the precision of the model on the basis of increasing less calculation amount.
Drawings
Fig. 1 is a schematic structural diagram of an access control system based on face recognition according to the present invention;
fig. 2 is a flowchart of the access control method based on face recognition according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to the following detailed description and accompanying drawings.
As shown in fig. 1, the present invention provides a door access control system based on face recognition, including: intelligent gateway, camera and intelligent entrance guard, intelligent gateway contains: a recognition device and a micro-control device, wherein,
the camera is used for sending a face image after acquiring a first session key between the camera and the intelligent gateway;
the recognition device is used for receiving the face image sent by the camera, calculating a face characteristic value based on the face image, and comparing the face characteristic value with a characteristic value in a preset face database to obtain a face recognition result;
the micro-control device obtains an access control operation command according to the face recognition result and sends the access control operation command to the intelligent access control; the access control operation command is obtained by encrypting the face recognition result by using a second session key; the second session key is a session key between the intelligent gateway and the intelligent access control;
and the intelligent access control is used for receiving the access control operation command after the second session key is obtained, decrypting the received access control operation command by using the second session key to obtain a face recognition result, and performing access control operation according to the face recognition result.
The technical scheme of the invention can carry out characteristic value comparison in the intelligent gateway to obtain the face recognition result, thereby improving the safety of the face recognition result, and the camera and the intelligent access control communicate with the intelligent gateway after obtaining the session key between the intelligent gateways, thereby improving the safety of the whole face recognition and access control operation process.
The camera and the intelligent access control can be regarded as external equipment except the intelligent gateway, the system can also comprise other external equipment such as an internet of things terminal, a mobile terminal and a cloud platform, the external equipment and a Micro Control Unit (MCU) can mutually transmit commands, the Micro control unit and an identification device can mutually transmit commands, the commands can comprise a command head and data, and data in the commands can be encrypted data or unencrypted data; the format of the command header may be set in advance according to requirements, for example, the command header may contain information such as a command type, a command parameter, a command counter, and a command length, where the command length is used to specify the length of data contained in the command. The command counter can be maintained by a command sender, the count value returns to zero after the bidirectional authentication is successful, and then the count value is accumulated every time an encryption command is sent, so that the replay attack is prevented.
In order to improve the security of communication, before sending data or a command to the intelligent gateway, the external device may first obtain a session key with the intelligent gateway, where the session key between the camera and the intelligent gateway may be referred to as a first session key; the session key between the intelligent gateway and the intelligent entrance guard can be called a second session key; and so on.
Further, the camera is specifically configured to obtain the first session key with the smart gateway in the following manner:
generating a camera random number, and sending a gateway identity authentication command to the micro-control device, wherein the gateway identity authentication command comprises the camera random number;
receiving a response command returned by the micro-control device, and performing identity verification on the intelligent gateway by using response data in the response command, wherein the response data can comprise a gateway certificate, a gateway random number and a camera random number signature value generated based on the camera random number;
if the intelligent gateway is confirmed to pass the identity authentication, sending a camera identity authentication command to the micro control device, so that the micro control device obtains a first session key encrypted by a camera public key after confirming that the camera passes the identity authentication, and sending the encrypted first session key to the camera; the camera identity authentication command comprises a camera public key;
and decrypting the received encrypted first session key by using a prestored camera private key to obtain the first session key.
The camera random number may be generated by the camera using a random function or a hash function. The length of the camera random number may be preset, and may be 16 bytes, 32 bytes, and the like, for example.
Further, similarly, before the intelligent entrance guard communicates with the intelligent gateway, both the intelligent entrance guard and the intelligent gateway can pass the authentication of the other party, so that both the intelligent entrance guard and the intelligent gateway can obtain the same second session key, the second session key can be used for communication between the intelligent entrance guard and the intelligent gateway, and unencrypted communication or encrypted communication with MAC can be performed according to the requirement.
After the intelligent entrance guard and the intelligent gateway both pass the identity authentication of the other party, the two parties can have the same second session key, and further can carry out encryption communication by using the second session key, so that the intelligent gateway can obtain the entrance guard operation result of the intelligent entrance guard conveniently and strengthen the management and control of the intelligent entrance guard; sending the access control operation response command to the micro-control device;
and the micro-control device is also used for receiving the access control operation response command, and decrypting the access control operation response command by using the second session key through the security element to obtain an access control decryption result.
In other implementation manners, the micro-control device may also decrypt the access control operation response command by using the second session key by itself, so as to obtain an access control decryption result.
Access operations include, but are not limited to, opening an access door, closing an access door, and the like. The access control operation result comprises whether the access control operation is successful. The access control operation response command is encrypted by using the second session key, and the access control operation result can be checked only by decrypting the access control operation response command by using the second session key, so that the safe transmission of the access control operation result is ensured, and the communication safety is improved.
Further, the identification device includes:
the model establishing module is used for establishing a face recognition model comprising a preset weighted convolution structure;
the data training module is used for inputting data to be trained to the face recognition model for training so as to obtain a characteristic value of the data to be trained, and storing the characteristic value in a database;
the characteristic identification module is used for inputting the collected face image into the face identification model so as to obtain the characteristics of the collected face image;
and the face recognition module is used for calculating the similarity between the characteristics of the acquired face image and the characteristic value of each image in the database based on the characteristic values stored in the database, and obtaining a face recognition result according to the similarity.
In the present invention, the preset weighted convolution structure is a scheme for superimposing different convolution results. The preset weighted convolution structure includes: the convolution layer processing system comprises at least two convolution layers, wherein the at least two convolution layers operate in parallel, and the output result of the parallel operation of the at least two convolution layers is the para-position addition of the results of the at least two parallel convolution characteristic graphs. The at least two convolution layers may be different convolution kernels, for example, may be at least two of 1 × 1, 3 × 3, 5 × 5, 7 × 7, and the like. And performing convolution operation on the at least two convolution layers respectively to obtain respective characteristic graphs, and finally adding the characteristic graphs by using superposition.
The preset weighted convolution structure is composed of two parallel convolution layers, and the output results of the two parallel convolution layers are the counterpoint addition of the results of the two parallel convolution characteristic graphs. For example, the preset weighted convolution is composed of 3 × 3 depth separable convolution kernels and 5 × 5 depth separable convolution kernels, and after performing convolution operations in parallel, the results are superimposed, for example, the convolution with 3 × 64 outputs 64 feature maps, the convolution with 5 × 64 also outputs 64 feature maps, then the feature maps are added, and finally the 64 feature maps are output.
It should be noted that the preset weighted convolution structure may also be composed of three parallel convolution layers or more parallel convolution layers, and finally, the feature maps corresponding to the output results of all the parallel convolution layers are subjected to superposition operation. The convolutional layer in which several parallel convolutional layers are arranged can be determined according to the size of the established model and the accuracy of the model to be considered.
In the invention, the weighted convolution structure is different from the way of splicing convolution results in the related art, the weighted convolution structure of the invention directly adds the feature maps by using superposition, so that for the same receptive field, when the feature maps retain information of a certain part, the information of a circle of pixels at the periphery of the part is retained, and particularly, the information of the peripheral part of the part is important. For example, when the preset weighted convolution structure is composed of 3 × 3 depth separable convolution kernels and 5 × 5 depth separable convolution kernels, the convolution result of 3 × 3 and the convolution result of 5 × 5 are superimposed, so that for the same receptive field, the feature map retains the information of one circle of pixels around the 3 × 3 region while retaining the information of the 3 × 3 region part. Meanwhile, since the 5 × 5 convolution kernel also covers the region covered by the 3 × 3 convolution kernel, and thus the 3 × 3 convolution kernel overlaps with the central region of the 5 × 5 convolution kernel, it can be understood that the region of 3 × 3 is weighted and the information of the 3 × 3 edge is considered but is not in a significant position. In face recognition, the principle of distinguishing important features can be achieved through the preset weighted convolution structure, that is, the edge of a region where a certain important feature is located should have certain importance, and this part should be given a weaker weight and considered by the model.
Wherein, the establishing of the face recognition model comprising the preset weighted convolution structure comprises: and replacing the common convolutional layer or the depth separable convolutional layer in the convolutional neural network model by the preset weighted convolutional structure.
The preset weighted convolution structure may be set in a convolution neural network model of the current mainstream, for example, MobileNet, MobileFaceNet, ResNet, or the like. When the preset weighted convolution structure is added to the convolutional neural network model, the preset weighted convolution structure is specifically replaced by a common convolutional layer or a depth separable convolutional layer in the convolutional neural network model.
If the convolutional neural network model comprises a plurality of normal convolutional layers and/or a plurality of depth separable convolutional layers, only a part of the normal convolutional layers or a part of the depth separable convolutional layers in the convolutional neural network model may be replaced in the operation process of replacing the preset weighted convolutional structure, and the number of the part may be one, two, and the like. In some embodiments, the predetermined weighted convolution structure may replace a normal convolution layer or a depth separable convolution layer located at a later position of the network in the convolutional neural network model. Therefore, the model precision is improved on the basis of increasing less computation, and the convolution of the later position of the replacement network has less influence on the time complexity and the space complexity of the algorithm.
Of course, if only the accuracy of the model is considered, the preset weighted convolution structure may replace all of the normal convolutional layers or all of the depth separable convolutional layers in the convolutional neural network model for maximum accuracy.
After the preset weighted convolution structure replaces a common convolution layer or a depth separable convolution layer in the convolutional neural network model, the input of the preset weighted convolution structure is a feature map transmitted from the upper layer, the feature map runs and operates on different convolution layers in parallel in the preset weighted convolution structure, and the result of the parallel operation is transmitted to the next layer after the feature map is aligned and added.
The technical scheme of the invention carries out face recognition based on the face recognition model with the preset weighted convolution structure, thereby obviously improving the precision of the model on the basis of increasing less calculation amount.
The access control system based on face recognition also comprises a mobile terminal, a micro control unit and a control unit, wherein the mobile terminal is used for sending a device management command to the micro control unit after obtaining a third session key between the mobile terminal and the micro control unit; and after receiving the equipment management command, the micro control unit manages the camera and/or the intelligent access control based on the equipment management command. The mobile terminal comprises a mobile phone, a tablet, a computer and the like, the mobile terminal can also communicate with the cloud platform in a wireless mode, the intelligent gateway is remotely accessed through the cloud platform, the state of the camera and/or the intelligent access control can be checked, the camera and/or the intelligent access control can be added or deleted, the parameters of the camera and/or the intelligent access control can be set, data can be transmitted to the intelligent security gateway, and the like through the identity authentication and the mobile terminal obtaining the corresponding authority.
As shown in fig. 2, the present invention further provides a door access control method based on face recognition, including:
step 1, sending a face image after a first session key between a camera and an intelligent gateway is obtained;
step 2, calculating a face characteristic value based on the face image, and comparing the face characteristic value with a characteristic value in a preset face database to obtain a face recognition result;
step 3, obtaining an access control operation command according to the face recognition result, and sending the access control operation command to an intelligent access control; the access control operation command is obtained by encrypting the face recognition result by using a second session key; the second session key is a session key between the intelligent gateway and the intelligent entrance guard;
and 4, after the second session key is obtained, receiving the access control operation command, decrypting the received access control operation command by using the second session key to obtain a face recognition result, and performing access control operation according to the face recognition result.
Further, step 2 specifically includes:
establishing a face recognition model comprising a preset weighted convolution structure;
inputting data to be trained to the face recognition model for training to obtain a characteristic value of the data to be trained, and storing the characteristic value in a database;
inputting the collected face image into the face recognition model to obtain the characteristics of the collected face image;
and calculating the similarity between the characteristics of the acquired face image and the characteristic value of each image in the database based on the characteristic values stored in the database, and obtaining a face recognition result according to the similarity.
The technical scheme of the invention can carry out characteristic value comparison in the intelligent gateway to obtain the face recognition result, thereby improving the safety of the face recognition result, and the camera and the intelligent access control communicate with the intelligent gateway after obtaining the session key between the intelligent gateways, thereby improving the safety of the whole face recognition and access control operation process.
Furthermore, the invention carries out face recognition based on the face recognition model with the preset weighted convolution structure, thereby obviously improving the precision of the model on the basis of increasing less calculation amount.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed by a computer, cause the computer to perform, in whole or in part, the procedures or functions described in accordance with the embodiments of the application. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable medium or transmitted from one computer readable medium to another, for example, from one website, computer, server, or data center to another website, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer readable medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
Those of skill would further appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It will be understood by those skilled in the art that all or part of the steps in the method for implementing the above embodiments may be implemented by a program, and the program may be stored in a computer-readable medium, where the storage medium is a non-transitory medium, such as a random access memory, a read only memory, a flash memory, a hard disk, a solid state disk, a magnetic tape (magnetic tape), a floppy disk (floppy disk), an optical disk (optical disk) and any combination thereof.
The above description is only for the preferred embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (8)
1. The utility model provides an access control system based on face identification which characterized in that includes: intelligent gateway, camera and intelligent entrance guard, intelligent gateway contains: a recognition device and a micro-control device, wherein,
the camera is used for sending a face image after acquiring a first session key between the camera and the intelligent gateway;
the recognition device is used for receiving the face image sent by the camera, calculating a face characteristic value based on the face image, and comparing the face characteristic value with a characteristic value in a preset face database to obtain a face recognition result;
the micro-control device obtains an access control operation command according to the face recognition result and sends the access control operation command to the intelligent access control; the access control operation command is obtained by encrypting the face recognition result by using a second session key; the second session key is a session key between the intelligent gateway and the intelligent access control;
and the intelligent access control is used for receiving the access control operation command after the second session key is obtained, decrypting the received access control operation command by using the second session key to obtain a face recognition result, and performing access control operation according to the face recognition result.
2. The door access control system based on face recognition as set forth in claim 1, wherein the recognition means comprises:
the model establishing module is used for establishing a face recognition model comprising a preset weighted convolution structure;
the data training module is used for inputting data to be trained to the face recognition model for training so as to obtain a characteristic value of the data to be trained, and storing the characteristic value in a database;
the characteristic identification module is used for inputting the collected face image into the face identification model so as to obtain the characteristics of the collected face image;
and the face recognition module is used for calculating the similarity between the characteristics of the acquired face image and the characteristic value of each image in the database based on the characteristic values stored in the database, and obtaining a face recognition result according to the similarity.
3. The door access control system based on face recognition as claimed in claim 2, wherein the preset weighted convolution structure comprises: the convolution layer processing system comprises at least two convolution layers, wherein the at least two convolution layers operate in parallel, and the output result of the parallel operation of the at least two convolution layers is the para-position addition of the results of the at least two parallel convolution characteristic graphs.
4. The door access control system based on face recognition as claimed in claim 3, wherein the model building module is specifically configured to: and replacing the common convolutional layer or the depth separable convolutional layer in the convolutional neural network model by the preset weighted convolutional structure.
5. The door access control system based on human face recognition as claimed in any one of claims 1-4, wherein the camera is specifically configured to obtain the first session key with the smart gateway by:
generating a camera random number, and sending a gateway identity authentication command to the micro-control device, wherein the gateway identity authentication command comprises the camera random number;
receiving a response command returned by the micro-control device, and performing identity verification on the intelligent gateway by using response data in the response command;
if the intelligent gateway is confirmed to pass the identity authentication, sending a camera identity authentication command to the micro control device, so that the micro control device obtains a first session key encrypted by a camera public key after confirming that the camera passes the identity authentication, and sending the encrypted first session key to the camera; the camera identity authentication command comprises a camera public key;
and decrypting the received encrypted first session key by using a prestored camera private key to obtain the first session key.
6. The access control system based on face recognition of any one of claims 1-4, wherein the intelligent access control is further configured to encrypt an access operation result with the second session key after performing an access operation to obtain an access operation response command; sending the access control operation response command to the micro-control device;
and the micro-control device is also used for receiving the access control operation response command, and decrypting the access control operation response command by using the second session key through the security element to obtain an access control decryption result.
7. The access control method based on face recognition is characterized by comprising the following steps:
step 1, sending a face image after a first session key between a camera and an intelligent gateway is obtained;
step 2, calculating a face characteristic value based on the face image, and comparing the face characteristic value with a characteristic value in a preset face database to obtain a face recognition result;
step 3, obtaining an access control operation command according to the face recognition result, and sending the access control operation command to an intelligent access control; the access control operation command is obtained by encrypting the face recognition result by using a second session key; the second session key is a session key between the intelligent gateway and the intelligent entrance guard;
and 4, after the second session key is obtained, receiving the access control operation command, decrypting the received access control operation command by using the second session key to obtain a face recognition result, and performing access control operation according to the face recognition result.
8. The door access control method based on face recognition according to claim 7, wherein the step 2 specifically comprises:
establishing a face recognition model comprising a preset weighted convolution structure;
inputting data to be trained to the face recognition model for training to obtain a characteristic value of the data to be trained, and storing the characteristic value in a database;
inputting the collected face image into the face recognition model to obtain the characteristics of the collected face image;
and calculating the similarity between the characteristics of the acquired face image and the characteristic value of each image in the database based on the characteristic values stored in the database, and obtaining a face recognition result according to the similarity.
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Application publication date: 20210625 |