CN111105544A - Face recognition access control system of unmanned supermarket and control method thereof - Google Patents
Face recognition access control system of unmanned supermarket and control method thereof Download PDFInfo
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Abstract
The invention provides a face recognition access control system of an unmanned supermarket, which comprises a face recognition module and an access control terminal, wherein the face recognition module is used for acquiring face image data of a recognition area, recognizing the acquired face image data to obtain face recognition data, comparing the face recognition data with registered face information data in a database to obtain comparison result information, generating an access control signal according to the comparison result, and sending the access control signal to the access control terminal, and the access control terminal is used for controlling the opening or closing of a door lock according to the acquired access control signal. The invention has the beneficial effects that: the scene of combined use of the terminal management system working at the background and the front-end embedded equipment is provided, online management and general service function configuration can be conveniently carried out on the access control system of the unmanned supermarket store, and convenience and practicability are provided for the access control system of the current unmanned supermarket.
Description
Technical Field
The invention relates to the technical field of face recognition technology and unmanned entrance guard security, in particular to a face recognition entrance guard system of an unmanned supermarket and a control method thereof.
Background
With the development of technology and the advancement of technology, and the popularization of network technology, there is a new revolution in the traditional retail business, wherein the retail business of unmanned supermarkets as a new business is started to fall on the ground and be used in real life. However, most of the existing unmanned supermarket access control systems adopt a two-dimensional code reading mode, and management of supermarket access personnel is achieved by scanning a two-dimensional code by a user to complete identity verification. However, this method also has obvious disadvantages, and in places where the network environment is not good, the user cannot complete the identity authentication through the mobile network, and when the user forgets to carry mobile communication devices such as a mobile phone, the user can normally enter the supermarket to complete shopping. In addition, under the condition of large personnel mobility, a user cannot complete identity verification in a short time, inconvenience in actual use of an unmanned supermarket is caused, the two-dimensional code access control system only allows one user to complete door opening access at one time, online verification time is long, inconvenience in queuing and waiting of the user is caused in an access peak period, and a brand-new unmanned supermarket access control system is needed.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the defects of the prior art, the face recognition access control system capable of working off line and the control method thereof are provided.
In order to solve the technical problems, the invention adopts the technical scheme that: a face recognition entrance guard system of an unmanned supermarket comprises a face recognition module and an entrance guard terminal,
the face recognition module is used for acquiring face image data of a recognition area, recognizing the acquired face image data to obtain face recognition data, comparing the face recognition data with registered face information data in a database to obtain comparison result information, generating an access control signal according to the comparison result, and sending the access control signal to the access control terminal, wherein the database comprises an online database and a local database, and the access control signal comprises a door opening allowing signal and a door opening forbidding signal;
the access control terminal is used for controlling the door lock to be opened or closed according to the acquired access control signal.
Furthermore, the face recognition module is further used for carrying out living body detection on the users in the recognition area to obtain a detection result, and sending the detection result to the access control terminal, and the access control terminal generates prompt information according to the detection result and prompts the users in the recognition area.
The system further comprises a terminal management module, wherein the terminal management module is used for sending registration request information to the access control terminal, and the access control terminal prompts and guides users in an identification area to register according to the registration request information.
Further, the face recognition module is further configured to send the comparison result information to the terminal management module, and the terminal management module generates an access information record of the user according to the comparison result information.
Further, the terminal management module is further used for carrying out data docking with a data analysis center of the unmanned supermarket and pushing the access information record of the user to the data analysis center.
The invention also relates to a face recognition access control method of the unmanned supermarket, which is applied to the system and comprises the following steps:
acquiring face image data of a recognition area through a face recognition module, recognizing the acquired face image data to obtain face recognition data, comparing the face recognition data with registered face information data in a database to obtain comparison result information, generating an access control signal according to the comparison result, and sending the access control signal to an access control terminal, wherein the database comprises an online database and a local database, and the access control signal comprises a door opening allowing signal and a door opening forbidding signal;
and the door control terminal controls the door lock to be opened or closed according to the acquired door control signal.
Further, before the step of acquiring the face image data of the identification area through the face identification module, the method further comprises the step of performing living body detection on the user of the identification area to obtain a detection result, and sending the detection result to the entrance guard terminal, wherein if the detection result is not in line with the requirement, the entrance guard terminal generates prompt information and prompts the user of the identification area.
Furthermore, in the step of comparing the face recognition data with the registered face information data in the database by the face recognition module, if the face recognition data is not matched with the registered face information data in the database, the face recognition data sends unmatched information to the terminal management module, the terminal management module sends request registration information to the access control terminal according to the unmatched information, and the access control terminal prompts and guides the user in the recognition area to register according to the request registration information.
Further, before the step of comparing the face recognition data with the registered face information data in the database by the face recognition module, the method also comprises the step of judging the working mode of the face recognition module, and when the working mode of the face recognition module is an online mode, the database of the cloud server is accessed; otherwise, accessing the database of the intranet server.
The invention also relates to a computer readable storage medium, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the above-mentioned face recognition access control method for an unmanned supermarket.
The invention has the beneficial effects that:
1) the invention provides a scene of combined use of a terminal management system working at the background and a front-end embedded device, which can conveniently carry out on-line management and general service function configuration on an access control system of an unmanned supermarket store, and provides convenience and practicability for the access control system of the current unmanned supermarket;
2) the invention uses a Linux embedded core development board, provides a method for accelerating the face feature recognition of an equipment end by using an edge computing module, and successfully applies the method to the reality, thereby improving the speed of the face recognition of the equipment end.
3) The background equipment management system provides rich management functions for front-end equipment management, realizes a three-party docking interface, facilitates information statistics and quality upgrading of the current unmanned supermarket, and simultaneously provides a concept of private deployment that a user can deploy the system to a desktop computer of a store directly without depending on a public network, thereby reducing the use cost of the unmanned supermarket access control system.
Drawings
The specific structure of the invention is detailed below with reference to the accompanying drawings:
FIG. 1 is a schematic diagram of the structure of an embodiment of the present invention;
fig. 2 is a schematic structural diagram of another embodiment of the present invention.
Detailed Description
In order to explain technical contents, structural features, and objects and effects of the present invention in detail, the following detailed description is given with reference to the accompanying drawings in conjunction with the embodiments.
Example 1
A face recognition entrance guard system of an unmanned supermarket comprises a face recognition module and an entrance guard terminal,
the face recognition module is used for acquiring face image data of a recognition area, recognizing the acquired face image data to obtain face recognition data, comparing the face recognition data with registered face information data in a database to obtain comparison result information, generating an access control signal according to the comparison result, and sending the access control signal to the access control terminal, wherein the database comprises an online database and a local database, and the access control signal comprises a door opening allowing signal and a door opening forbidding signal;
the access control terminal is used for controlling the door lock to be opened or closed according to the acquired access control signal.
In this embodiment, face identification module is including handling chip, infrared camera and color camera, handle the chip respectively with infrared camera and color camera are connected, infrared camera and color camera are wide dynamic camera, can guarantee the reliability that the image acquireed, in addition, for the reduction consumption, it still is connected with human infrared inductor to handle the chip, whether there is personnel to exist in utilizing infrared human inductor to respond to the identification region within range, thereby triggering system awakens up from the low power consumption mode, trigger recognition function, if there is not personnel to exist in a certain time, face identification module then gets into dormancy low power consumption mode, effectively saved the consumption, the life of equipment has been prolonged again simultaneously. In order to further improve the identification efficiency, the processing chip is further connected with an infrared light supplement lamp and an LED light supplement lamp, and can supplement illumination for personnel in an identification area at a proper time.
The processing chip rapidly completes face detection, living body recognition and face recognition through a deep learning model algorithm stored in the storage chip and an edge calculation unit integrated in the processing chip. And then, matching index of the user face information is completed through a quick index algorithm, if the matching index is found, comparison result information which is successfully matched is sent, and visiting information of the current user is pushed to a terminal management module, so that the statistical management of the visiting information is facilitated, and the butt joint with a supermarket visiting system is realized.
The entrance guard terminal comprises an entrance guard power supply and an electromagnetic lock, the electromagnetic lock is used as equipment for directly controlling the opening and closing of the supermarket door, and the opening and closing states of the door lock pin are mainly realized by utilizing a relay. The working mode of the electromagnetic lock generally has two states of normally open and normally closed, and the access control system generally selects the normally closed state. For safety purposes, the present embodiment uses a large coil electromagnetic lock, and therefore requires a large current. The current that draws through entrance guard's terminal can't provide so big power, reduces entrance guard terminal equipment's consumption on the one hand, and on the other hand guarantees the stability of whole hardware system work, consequently receives the entrance guard signal that comes from entrance guard terminal through the entrance guard power and triggers, enlargies entrance guard signal, controls the open and close state of electromagnetic lock to the switch of control supermarket door.
Example 2
On the basis of the embodiment 1, the face recognition module is further configured to perform living body detection on the user in the recognition area to obtain a detection result, and send the detection result to the access control terminal, and the access control terminal generates prompt information according to the detection result and prompts the user in the recognition area.
In this embodiment, in order to improve the security and reliability of the face recognition module, it is necessary to determine whether the detected object is a living individual, rather than an inanimate object such as a photo or a video, so as to prevent a malicious attacker from performing malicious spoofing by using recorded videos, shot photos, 3D face models, or forged masks, and the like.
Example 3
On the basis of the embodiment 2, the system further comprises a terminal management module, wherein the terminal management module is used for sending request registration information to the access control terminal, and the access control terminal prompts and guides the user in the identification area to register according to the request registration information.
In this embodiment, the access control terminal includes a touch display screen capable of interacting with a user, and after the system prompts a non-registered user, the user can scan the two-dimensional code displayed on the touch display screen by using a mobile terminal connected with the internet, such as a mobile phone, to access the background registration interface to complete registration. The entrance guard terminal provides the face feature extraction function simultaneously to can bind the characteristic with personnel's information and equipment.
The terminal management module is also provided with service functions such as personnel issuing and equipment terminal setting, and issues, deletes and updates instructions of face data of a user who is bound with the current equipment to open the door, so that the management function of the access control terminal on the user is completed. Meanwhile, the door opening action of the access control terminal, the personnel identification distance, the living body detection and other functional modules can be configured, the setting of the self-defined function is completed, a convenient setting interface is provided for the use of different supermarket stores, and the market adaptability is improved.
Example 4
On the basis of embodiment 3, the face recognition module is further configured to send the comparison result information to the terminal management module, and the terminal management module generates an access information record of the user according to the comparison result information.
In this embodiment, statistics of the access information of the user by the system is facilitated, and the terminal management module generates an access information record of the user according to the comparison result information.
Example 5
On the basis of the embodiment 4, the terminal management module is further configured to perform data docking with a data analysis center of an unmanned supermarket, and push access information records of a user to the data analysis center.
In this embodiment, the terminal management module may provide a three-party interface for external connection, so as to facilitate docking with other platforms. The background service system is used as a recording management center for face brushing visits of users, can record effective statistical data of face visits, and is in butt joint with interfaces such as a data analysis center of a current unmanned supermarket. The user access record information can be quickly forwarded to the data analysis center, the personnel visiting time, the visiting person flow distribution time, the visiting consumption record and the like of the unmanned supermarket can be conveniently counted to perform data analysis, and the product introduction and inventory time of the current unmanned supermarket store can be improved. Customized difference services can be provided according to regional requirements, and the like. The information cooperation capability of the product in the field of unmanned supermarket sales in the information era is enhanced.
Example 6
The invention also relates to a face recognition access control method of the unmanned supermarket, which is applied to the system and comprises the following steps:
acquiring face image data of a recognition area through a face recognition module, recognizing the acquired face image data to obtain face recognition data, comparing the face recognition data with registered face information data in a database to obtain comparison result information, generating an access control signal according to the comparison result, and sending the access control signal to an access control terminal, wherein the database comprises an online database and a local database, and the access control signal comprises a door opening allowing signal and a door opening forbidding signal;
and the door control terminal controls the door lock to be opened or closed according to the acquired door control signal.
In the embodiment, the face recognition module acquires face image data through the infrared camera and the color camera, recognizes the acquired face image data to obtain face recognition data, completes matching indexes of user face information in the database through a fast indexing algorithm, and pushes result information to the terminal management module if the matching indexes are found, the terminal management module sends an access control signal to the access control terminal according to the comparison result information, and the access control terminal controls opening or closing of a door lock according to the acquired access control signal.
In order to realize the purpose of accelerating the face recognition speed and carrying out algorithm optimization on the deep learning model, the face detection algorithm model adopted by the embodiment is a Retina face deep learning model, and the method adopts a multi-task learning strategy to simultaneously predict face scores, a face frame, five points and three-dimensional positions. This is achieved by using strongly supervised and auto-supervised multitask loss functions. By adopting the Priori-Anchors method, a face detection regression frame and face key points can be obtained by using One-Stage and adopting One-time operation. In the process, the built-in NNIE deep learning acceleration module of the processing chip is utilized, a CPU does not need to open up memory space for many times, and the process overhead of consuming time and the maximum in the deep learning model is reduced.
After the face detection, the processing chip extracts the face image data, so that the requirements of real-time performance and accuracy can be met, in the embodiment, mobileFaceNet is used for extracting model features, an ArcFace loss function is used for a loss function, a plurality of loss functions including the combination of triple-loss and L-Softmax are counted, similar samples are distinguished more effectively for enlarging the distance between feature classes, the generalization capability of feature extraction is improved, and a basic model structure of mobileNet-V2 is used, so that the calculation amount of forward transmission can be effectively reduced. After the overall recognition speed of model detection and model recognition is calculated by using NNIE edges, the overall flow speed is less than 50ms and exceeds the face recognition frame rate of 25fps, and the interactive experience sense in the recognition flow is fully met.
Example 7
On the basis of the embodiment 6, before the step of acquiring the face image data of the identification area through the face recognition module, the method further comprises the steps of performing living body detection on the user of the identification area to obtain a detection result, and sending the detection result to the entrance guard terminal, wherein if the detection result does not meet the requirement, the entrance guard terminal generates prompt information and prompts the user of the identification area.
In this embodiment, in order to improve the security and reliability of the face recognition module, it is necessary to determine whether the detected object is a living individual, rather than an inanimate object such as a photo or a video, so as to prevent a malicious attacker from performing malicious spoofing by using a recorded video, a shot photo, a 3D face model, or a forged mask, and the like, and the face image data of the recognition area is acquired by using a dual-path wide dynamic infrared camera and a color camera, and living body recognition is rapidly completed by using a deep learning model algorithm and an edge calculation scheme.
Example 8
On the basis of embodiment 7, in the step of comparing the face recognition data with the registered face information data in the database by the face recognition module, if the face recognition data is not matched with the registered face information data in the database, the face recognition data sends out unmatched information to the terminal management module, the terminal management module sends out request registration information to the access control terminal according to the unmatched information, and the access control terminal prompts and guides the user in the recognition area to register according to the request registration information.
In the embodiment, a user can scan the two-dimensional code of the access control terminal by using a mobile terminal connected with the internet, such as a mobile phone, and the like through a camera provided with the user, so as to access the background registration interface to complete registration, the access control terminal can extract human face features while registering, and the features are bound with personnel information and equipment, wherein the personnel information comprises a user name, a mobile phone number and human face information data.
Example 9
On the basis of the embodiment 8, before the step of comparing the face recognition data with the registered face information data in the database by the terminal management module, the method further comprises the step of judging the working mode of the face recognition module, and when the working mode of the face recognition module is an online mode, the database of the cloud server is accessed; otherwise, accessing the database of the intranet server.
In the embodiment, an online working mode or an offline working mode can be selected according to the needs of a user, if the online working mode is adopted, a cloud server can be adopted for deployment, and then a router is used for connecting a public network to realize the control of terminal equipment; if the off-line mode is adopted, the local PC is connected with the router, the router is connected with the equipment in an intranet, and terminal management software capable of realizing the functions of the terminal management module is preinstalled in the local PC. The router and the wireless repeater are used as media of network signals, so that the access control terminal equipment is connected with the management platform, and data synchronization and real-time management control of the access control terminal are realized.
The invention also relates to a computer readable storage medium, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the above-mentioned face recognition access control method for an unmanned supermarket.
Working example 1
Please refer to fig. 1, in this embodiment, the face recognition access control system of the unmanned supermarket includes a cloud server installed with software capable of implementing functions of a terminal management module, a public network router, a wireless router, an access terminal and an electromagnetic access lock, wherein the cloud server is connected with the public network router through the Internet, the public network router is wirelessly connected with the face access terminal, user face data is sent to the wireless router through the configured cloud server by using the public network router, and then sent to the access terminal by the wireless router, the user interacts with the access terminal, the access terminal controls the electromagnetic access lock after finishing face recognition, and the door opening action is completed.
Working example 2
Referring to fig. 2, in this embodiment, a face recognition access control system of an unmanned supermarket includes a local PC installed with software capable of implementing a terminal management module function, a wireless router, an access control terminal and an electromagnetic access control lock, wherein the local PC is wirelessly connected with the face access control terminal through the wireless router, user face data is sent to the access control terminal through a local area network, and a user interacts with the access control terminal to control the electromagnetic access control lock by the access control terminal after face recognition is completed, so as to complete a door opening operation.
In the above two implementation examples, in order to enhance the coverage of the wireless network, a wireless repeater may be additionally provided.
The entrance guard terminal machine adopts an embedded development board as a core board card, and simultaneously expands external equipment interfaces suitable for entrance guard, such as an external IO port, an RS232 serial port, a usb interface and the like, so as to realize communication with external equipment. And the access terminal adopts an embedded Linux system, so that the communication with a background human face access control equipment management system is effectively realized, a deep learning model can be carried, and the drive expansion of external expansion equipment is facilitated.
In order to realize real-time multi-face recognition and detection and realize the purpose that a plurality of people can not queue up and pass through the face access control of an unmanned supermarket, the access control terminal adopts a Hais chip. The chip is provided with an edge calculation module, 1.OTops calculation power and 4G Spi-nand Flash storage space, and provides basic guarantee for building a deep learning model. In addition, the chip can realize the access of a double-way Mipi camera and provides the MIPI-RX2 to realize the timing adjustment of a double-way camera receiving device.
In order to ensure the connection reliability of the terminal management module, the entrance guard terminal and the face recognition module, the terminal management module is in long connection with the entrance guard terminal and the face recognition module in a Socket long connection mode, and the terminal management module can monitor whether the entrance guard terminal and the face recognition module work normally or not at the background by utilizing a heartbeat protocol and a self-defined communication protocol.
From the above description, the beneficial effects of the present invention are:
1) the invention provides a scene of combined use of a background equipment management system and a front-end embedded equipment, which is used for carrying out on-line management and general service function configuration on an access control system of an unmanned supermarket store and providing convenience and practicability for the access control system of the current unmanned supermarket;
2) the invention uses a Linux embedded core development board, provides a method for accelerating the face feature recognition of an equipment end by using an edge computing module, and successfully applies the method to the reality, thereby improving the speed of the face recognition of the equipment end.
3) The background equipment management system provides rich management functions for front-end equipment management, realizes a three-party docking interface, facilitates information statistics and quality upgrading of the current unmanned supermarket, and simultaneously provides a concept of private deployment that a user can deploy the system to a desktop computer of a store directly without depending on a public network, thereby reducing the use cost of the unmanned supermarket access control system.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes performed by the present specification and drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. The utility model provides a face identification access control system in unmanned supermarket which characterized in that: comprises a face recognition module and an entrance guard terminal,
the face recognition module is used for acquiring face image data of a recognition area, recognizing the acquired face image data to obtain face recognition data, comparing the face recognition data with registered face information data in a database to obtain comparison result information, generating an access control signal according to the comparison result, and sending the access control signal to the access control terminal, wherein the database comprises an online database and a local database, and the access control signal comprises a door opening allowing signal and a door opening forbidding signal;
the access control terminal is used for controlling the door lock to be opened or closed according to the acquired access control signal.
2. The face recognition access control system of an unmanned supermarket of claim 1, wherein: the face recognition module is further used for carrying out living body detection on the users in the recognition area to obtain detection results, the detection results are sent to the entrance guard terminal, and the entrance guard terminal generates prompt information according to the detection results and prompts the users in the recognition area.
3. The face recognition access control system of an unmanned supermarket of claim 1, wherein: the system comprises an entrance guard terminal and a terminal management module, wherein the entrance guard terminal is used for sending request registration information to the entrance guard terminal, and the entrance guard terminal prompts and guides users in an identification area to register according to the request registration information.
4. The face recognition access control system of an unmanned supermarket of claim 3, wherein: the face recognition module is also used for sending the comparison result information to the terminal management module, and the terminal management module generates an access information record of the user according to the comparison result information.
5. The face recognition access control system of an unmanned supermarket of claim 4, wherein: the terminal management module is also used for carrying out data butt joint with a data analysis center of the unmanned supermarket and pushing the access information record of the user to the data analysis center.
6. A face recognition access control method of an unmanned supermarket, which is applied to the system of any one of claims 1-5, the method comprising:
acquiring face image data of a recognition area through a face recognition module, recognizing the acquired face image data to obtain face recognition data, comparing the face recognition data with registered face information data in a database to obtain comparison result information, generating an access control signal according to the comparison result, and sending the access control signal to an access control terminal, wherein the database comprises an online database and a local database, and the access control signal comprises a door opening allowing signal and a door opening forbidding signal;
and the door control terminal controls the door lock to be opened or closed according to the acquired door control signal.
7. The face recognition access control method of an unmanned supermarket according to claim 6, characterized in that: before the step of acquiring the face image data of the identification area through the face identification module, the method further comprises the step of performing living body detection on the user of the identification area to obtain a detection result, and sending the detection result to the entrance guard terminal, and if the detection result is not in line with the requirement, the entrance guard terminal generates prompt information and prompts the user of the identification area.
8. The face recognition access control method of an unmanned supermarket according to claim 7, characterized in that: in the step of comparing the face recognition data with the registered face information data in the database by the face recognition module, if the face recognition data is not matched with the registered face information data in the database, sending unmatched information to the terminal management module, sending request registration information to the access control terminal by the terminal management module according to the unmatched information, and prompting and guiding users in a recognition area to register by the access control terminal according to the request registration information.
9. The face recognition access control method of an unmanned supermarket according to claim 8, characterized in that: before the step of comparing the face recognition data with the registered face information data in the database by the face recognition module, the method also comprises the step of judging the working mode of the face recognition module, and when the working mode of the face recognition module is an online mode, the database of the cloud server is accessed; otherwise, accessing the database of the intranet server.
10. A computer-readable storage medium having stored thereon a computer program, characterized in that: the computer program, when executed by a processor, implements the face recognition access control method of any one of claims 6 to 9.
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| CN114120515A (en) * | 2021-11-12 | 2022-03-01 | 国网冀北电力有限公司唐山供电公司 | Transformer substation multifunctional access control system based on Internet of things and use method thereof |
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