CN113570374A - System, method and equipment of mobile payment method based on face recognition - Google Patents
System, method and equipment of mobile payment method based on face recognition Download PDFInfo
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- CN113570374A CN113570374A CN202110670073.1A CN202110670073A CN113570374A CN 113570374 A CN113570374 A CN 113570374A CN 202110670073 A CN202110670073 A CN 202110670073A CN 113570374 A CN113570374 A CN 113570374A
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
- G06Q20/401—Transaction verification
- G06Q20/4014—Identity check for transactions
- G06Q20/40145—Biometric identity checks
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Abstract
The invention provides a mobile payment method, a system and equipment based on face recognition, which comprises the following steps of initiating a payment request; acquiring second face information; carrying out face verification; carrying out real person verification; and if the face verification and the real person verification pass at the same time, completing the payment, otherwise, interrupting the payment. The invention provides a system of a mobile payment method based on face recognition, which comprises a face information acquisition unit and a server. The invention provides equipment comprising a mobile payment method system based on face recognition. The invention can effectively reduce or even eliminate the risk that the user is falsely used by other people by carrying out face and real person double verification on the user, and simultaneously, the invention compares the second face information with the past payment image of the user to judge whether the user is a real person or a photo when paying, compared with the prior art that a 3D camera is used for collecting the first face information, the invention only needs to use a common camera, thereby greatly reducing the cost.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a system, a method and equipment of a mobile payment method based on face recognition.
Background
Mobile payment, also known as mobile payment, is a service that allows users to use their mobile terminals (typically mobile phones) for financial payments of goods or services consumed. The unit or the individual directly or indirectly sends a payment instruction to the bank financial institution through the mobile equipment, the Internet or the close-range sensor to generate money payment and fund transfer behaviors, so that the mobile payment function is realized. The mobile payment integrates terminal equipment, the Internet, an application provider and a financial institution, and provides financial services such as currency payment and payment for a user.
The existing mobile payment has some potential safety hazards. For example, the transaction can be completed only by means of authentication of the user's mobile phone, such as inputting a password. The user's handset may be lost or stolen. Or to a stranger. In this case, if payment is completed only by means of the password, it is easy to cause damage to the property of the user. And paying using face recognition risks others falsifying using photos.
Disclosure of Invention
Aiming at the problem that other people falsely use photos in the prior art, the invention aims to solve the technical problem of identifying photos and real people. And provides the following technical scheme:
a mobile payment method based on face recognition comprises initiating a payment request; acquiring second face information; carrying out face verification; carrying out real person verification; and if the face verification and the real person verification pass at the same time, completing the payment, otherwise, interrupting the payment.
In the above mobile payment method based on face recognition, after the step of obtaining the second face information, the method includes: and encrypting and transmitting the second face information to a server.
In the mobile payment method based on face recognition, the encryption transmission method is to divide the second face information into a plurality of small images, each small image has a respective number, and the numbers are divided into two types and sent to the server through different network transmission modes after being scrambled by using the time information.
In the above mobile payment method based on face recognition, after the step of encrypting and transmitting the second face information to the server, the method further includes: it is decrypted.
The above mobile payment method based on face recognition comprises, before the face verification in the step: and inputting first face information, and binding and storing the input first face information and the corresponding payment account.
In the above mobile payment method based on face recognition, the step of performing face verification includes: matching the second face information with the first face information, and entering real person verification if matching is successful; if the matching is unsuccessful, the payment is interrupted.
The above mobile payment method based on face recognition comprises, before the step of performing real person verification: and storing the image for each payment to a server, wherein the image for each payment is bound with the payment account for storage.
In the above mobile payment method based on face recognition, the step of performing real person verification includes: and comparing the second face information with the payment image, if the comparison is successful, interrupting the payment, otherwise, completing the payment.
A mobile payment system based on face recognition comprises a face information acquisition unit and a server, wherein the face information acquisition unit is used for initiating a payment request; acquiring second face information; carrying out face verification; carrying out real person verification; and if the face verification and the real person verification pass at the same time, completing the payment, otherwise, interrupting the payment.
A mobile payment device based on face recognition comprises the mobile payment system based on face recognition.
According to the scheme, the system, the method and the equipment of the mobile payment method based on the face recognition can effectively reduce or even eliminate the risk that the user is falsely used by photos used by other people by performing double verification on the face and the real person of the user, and meanwhile, compared with the prior art that a 3D camera is used for collecting the first face information, the cost is greatly reduced by only using a common camera by comparing the second face information with the past payment images of the user to judge whether the user is the real person or the photos when the user pays.
Drawings
In order to more clearly illustrate the embodiments of the present application or technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings can be obtained by those skilled in the art according to the drawings.
FIG. 1 is a diagram: the present embodiment provides a logical structure diagram of a mobile payment method based on face recognition.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without inventive work based on the embodiments of the present invention, belong to the scope of protection of the present invention.
In one application scenario of the embodiment of the present invention: for example, when a user needs to pay through a mobile payment device after purchasing a commodity, the face information can be recognized through a face information acquisition unit, such as a camera, of the portable terminal, and after the authentication is successful, money is automatically deducted from an account corresponding to the face information.
Specifically, the video stream of the face image may be acquired by the face information acquiring unit, the single-frame image of the face image may be acquired by the face information acquiring unit, or both the single-frame image and the video stream of the face image may be acquired by the face information acquiring unit. And uploading the face image acquired by the face information acquisition unit to a server, authenticating by the server, automatically deducting money from an account corresponding to the face information if the authentication is passed, and prompting that the money deduction is failed if the authentication is not passed.
The mobile payment method based on face recognition provided by the embodiment of the invention comprises the steps of firstly, constructing a face database, wherein the face database is stored in a server, the face database is formed by uploading first face information formed by shooting face information by a user through mobile electronic equipment such as a mobile phone and a tablet, the user is registered, and accounts which can be used for paying money, such as a bank card and a credit card, are bound through payment software such as a payment bank, a WeChat and a cloud flash payment software, and the first face information is bound with the account information. After the first face information is uploaded to the server, the server analyzes the first face information, calculates 68 feature points of the face, appropriately adjusts the position of the face, aligns the face, and then puts the obtained face image into a neural network to obtain 128 feature measurement values and stores the feature measurement values.
In a first aspect, an embodiment of the present invention provides a mobile payment method based on face recognition, and with reference to fig. 1, the method includes the following steps:
step S1, a payment request is initiated.
In this step, a salesperson scans the two-dimensional code, the bar code and the like of the commodity by using a code scanning gun or a user aligns the two-dimensional code and the bar code of the commodity with a scanning port in a self-service checkout machine, a cash register or the self-service checkout machine initiates a payment request to the user after obtaining the total amount to be paid according to the information of the unit price, the amount and the like of the commodity, and the user can pay in various ways, for example, the payment code of payment software is aligned with the code scanning gun or the scanning port to pay, the payment is carried out by swiping a card by using a bank card or a credit card and the like, the face information is acquired by a face information acquisition unit to authenticate and realize automatic payment and the like. Preferably, the face information is acquired by the face information acquisition unit to be authenticated so as to realize automatic payment. In the embodiment of the invention, after the cash register or the self-service checkout machine initiates the payment request, a scanner or a card swiping machine or a face information acquisition unit of a specified payment client on the mobile terminal can be called up in a wired control or wireless control mode. Preferably, after the payment request is initiated by the cash register or the self-service checkout machine, the face information acquisition unit of the appointed payment client on the mobile terminal is called up in a wireless control mode to acquire the face information for authentication so as to realize automatic payment. The limited control can be data transmission with the cash register through a data line, and the wireless control can be data transmission through Bluetooth, WiFi and the like.
In step S2, second face information is acquired.
As described above, before the user completes payment, it is necessary to verify whether the user is himself or herself by a certain method to ensure property security of the user, in this embodiment, it is preferable to determine authenticity of the user identity by using face information, specifically, after a payment request is initiated by a cash register or a self-service checkout machine, a face information obtaining unit is invoked to obtain second face information, the face information obtaining unit may be a camera, and the obtained second face information may be a single frame image or a video stream.
In step S3, face verification is performed.
As described above, after the face information acquisition unit acquires the second face information, the face information acquisition unit performs face verification to make a preliminary determination as to whether the person is used. The face verification comprises the following steps:
and S31, encrypting and transmitting the second face information to a server.
After the face information acquiring unit acquires the second face information, in order to prevent an operator or other persons who do not use the face information acquiring unit from copying and taking away the image information in the face information acquiring unit, the face information acquiring unit preferably does not have an information storage function, and in order to further ensure the security of the face information of the user, encryption transmission is preferably performed in the process of transmitting the second face information to the server. The encryption transmission mode is to divide the second face information into a plurality of small images, for example, a complete picture is divided into 64 small images, each image has a number, the numbers are scrambled by using time information, then the scrambled images are classified into two types, and the two parts of the images are sent to the server through different network transmission modes, specifically, one type of the images is sent to the server through a mobile communication network, and the other type of the images is sent to the server through a wifi network. By the encryption method, the safety of the user face information in the process of retransmission can be improved, because the next decryption can be carried out only by simultaneously intercepting two groups of information, if the content transmitted by one transmission mode is intercepted in the transmission process, the whole image cannot be restored because the content transmitted by the other transmission mode cannot be acquired. The second face information should contain the shooting time, the number (ID) of the camera shooting, and other information with a unique identifier when being uploaded to the server.
And S32, decrypting the encrypted second face information.
After receiving the second face information transmitted by different network transmission modes, the server firstly recombines the two partial images, namely splices the two partial images into a complete image, and then decrypts each small image, thereby restoring the original second face information.
And S33, matching the second face information with the first face information.
The step is used for preliminarily judging whether the actual payer and the account holder are the same person, and the face recognition technology used in the step mainly relates to four parts of contents: and preprocessing the acquired second face information, positioning the face, extracting face characteristic parameters and comparing and identifying a face database. The face database is formed by uploading first face information formed by shooting face information by a user through mobile electronic equipment such as a mobile phone and a tablet. Specifically, 68 feature points of the face are calculated according to the second face information, the face position is appropriately adjusted, the face is aligned, the obtained face image is placed in a neural network, 128 feature measurement values are obtained and stored, the Euclidean distance is calculated together with the measurement values calculated according to the first face information, Euclidean distance values are obtained, the values are compared, and whether the two people are the same person is judged.
The Euclidean distance is calculated according to the following formula:
and if the facial features of the actual payer and the account holder are judged to be consistent through the steps, judging whether the actual payer and the account holder are the same person again, and if the facial features of the actual payer and the account holder are judged to be inconsistent through the steps, interrupting the payment and giving an error prompt to the user.
And S4, carrying out real person verification.
The face verification in the last step analyzes and judges the face characteristic values of the first face information and the second face information, so that the behavior of falsely using a transaction account by other people is prevented to a certain extent, but the falsely using photos by other people cannot be solved. In order to prevent a person from impersonating himself/herself holding a photograph, that is, taking a photograph of a user in real time, it is necessary to recognize that a person takes a printed photograph of a user and impersonates the user. In this case, there are two solutions, one is to take continuous video images, where the user is required to shake his head from side to side and to nod his head up and down. In this case, the person may also cover the camera by swinging the camera with a previously shot video image having a nodding head and a shaking head. Another safer mode is that the server stores the photo or video sent by the cash register during each payment of the user, compares the photo or photo sent by the user during the payment, and feeds back the photo or video to the cash register to interrupt the payment if the probability of the same copy is too high.
When the method is used for real person verification, images of the user in each payment are stored in the server, the stored payment images in each payment are bound with the payment account, the stored payment images of the user in the past are combined into a database, and when the user pays for a new time, the database is compared with the stored payment images of the user in the past to judge whether the user is a real-time photo or other people masquerade. The specific comparison method can be as follows:
(1) and polling each pixel in the past payment image of each user in the database and each pixel in the second face information, comparing one by one, if one pixel is different, judging that the past payment image is inconsistent with the second face information, and analyzing the rate of how much the past payment image of the user in the database is consistent with the second face information.
(2) Converting the data stream of the second face information and the past payment image of each user in the database into a string of Base64 strings, then comparing the strings, if a pixel point is different, judging that the past payment image is inconsistent with the second face information, and analyzing the rate of how much the past payment image of the user in the database is consistent with the second face information.
The first method has the problem that a large number of queries can significantly slow down the system speed, and even the system may fail when too many images are compared, while the second method can effectively avoid the above problems and has the advantages of high accuracy and high speed, so the preferred comparison method is the second method.
The comparison method analyzes the rate of how much the past payment images of the user in the database are consistent with the second face information, when the rate is higher than 5%, the server determines that the user uses pictures or videos by others at present, the payment is interrupted, and the user can verify the payment by retrying or other verification methods.
In a second aspect, the present embodiment provides a system of a mobile payment method based on face recognition, including a face information obtaining unit and a server.
Specifically, the face information acquisition unit is used for acquiring image information of a user during payment, the face information acquisition unit is connected with a cash register or an automatic checkout machine, and the cash register or the automatic checkout machine can be used for starting the face information acquisition unit to acquire second face information of the user after a commodity is scanned, and uploading the acquired second face information to the server. The face information acquiring unit may be a camera or other devices, and in order to ensure the security of the face information of the user, the camera is preferably a camera without a storage function.
The server is used for storing image information, account information and first face information when the user pays, receiving second face information, performing face verification, real person verification and the like. The server, also known as a server, is a device that provides computing services. Since the server needs to respond to and process the service request, the server generally has the capability of assuming and securing the service. The server is constructed to include a processor, a hard disk, a memory, a system bus, etc., similar to a general-purpose computer architecture, but requires high processing power, stability, reliability, security, scalability, manageability, etc., due to the need to provide highly reliable services. Under a network environment, the server is divided into a file server, a database server, an application server, a WEB server and the like according to different service types provided by the server. The application-level partitioning is also commonly referred to as "server-level partitioning" or "network-scale" partitioning, and is the most common partitioning method for servers, and is mainly based on the level of application of the servers in the network (or the level of the servers). It should be noted that the server class referred to herein is not divided according to the level of the main frequency of the CPU of the server, but rather is measured according to the overall performance of the entire server, particularly according to the server-specific techniques employed. According to this division method, the server can be divided into: an entry level server, a workgroup level server, a department level server, an enterprise level server, and a video server. This embodiment is preferably an enterprise level server.
In a third aspect, the embodiment provides a mobile payment device based on face recognition, which includes a mobile payment system based on face recognition, and the device may be used for an offline merchant to perform a payment receiving service.
While certain exemplary embodiments of the present invention have been described above by way of illustration only, it will be apparent to those of ordinary skill in the art that the described embodiments may be modified in various different ways without departing from the spirit and scope of the invention. Accordingly, the drawings and description are illustrative in nature and should not be construed as limiting the scope of the invention.
Claims (10)
1. A mobile payment method based on face recognition is characterized by comprising the following steps:
initiating a payment request;
acquiring second face information;
carrying out face verification;
carrying out real person verification;
and if the face verification and the real person verification pass at the same time, completing the payment, otherwise, interrupting the payment.
2. The mobile payment method based on face recognition of claim 1, wherein after the step of obtaining the second face information, the method comprises: and encrypting and transmitting the second face information to a server.
3. The mobile payment method based on face recognition according to claim 2, wherein the encryption transmission method is to divide the second face information into a plurality of small images, each small image has its own number, and after the numbers are scrambled by using time information, the small images are divided into two types and sent to the server through different network transmission modes.
4. The mobile payment method based on face recognition of claim 3, further comprising, after the step of transmitting the second face information to a server in an encrypted manner: it is decrypted.
5. The mobile payment method based on face recognition according to claim 4, wherein before the step of face verification, the method comprises: and inputting first face information, and binding and storing the input first face information and the corresponding payment account.
6. The mobile payment method based on face recognition of claim 5, wherein the step of performing face verification comprises: matching the second face information with the first face information, and entering real person verification if matching is successful; if the matching is unsuccessful, the payment is interrupted.
7. The mobile payment method based on face recognition as claimed in claim 6, wherein before the step of performing real person verification, the method comprises: and storing the image for each payment to a server, wherein the image for each payment is bound with the payment account for storage.
8. The mobile payment method based on face recognition as claimed in claim 7, wherein the step of performing real person verification comprises: and comparing the second face information with the payment image, if the comparison is successful, interrupting the payment, otherwise, completing the payment.
9. A mobile payment system based on face recognition is characterized by comprising:
the face information acquisition unit and the server are used for initiating a payment request; acquiring second face information; carrying out face verification; carrying out real person verification; and if the face verification and the real person verification pass at the same time, completing the payment, otherwise, interrupting the payment.
10. A mobile payment device based on face recognition, characterized by comprising the mobile payment system based on face recognition as claimed in claim 9.
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| CN202110670073.1A CN113570374A (en) | 2021-06-17 | 2021-06-17 | System, method and equipment of mobile payment method based on face recognition |
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| CN202110670073.1A CN113570374A (en) | 2021-06-17 | 2021-06-17 | System, method and equipment of mobile payment method based on face recognition |
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| CN113570374A true CN113570374A (en) | 2021-10-29 |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114037467A (en) * | 2015-10-20 | 2022-02-11 | 索尼公司 | Information processing system, information processing method, and computer-readable storage medium |
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2021
- 2021-06-17 CN CN202110670073.1A patent/CN113570374A/en not_active Withdrawn
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114037467A (en) * | 2015-10-20 | 2022-02-11 | 索尼公司 | Information processing system, information processing method, and computer-readable storage medium |
| CN114037467B (en) * | 2015-10-20 | 2024-08-13 | 索尼公司 | Information processing system, information processing method, and computer-readable storage medium |
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