CN111915307A - Contactless mobile payment system and method - Google Patents
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Abstract
The invention discloses a contactless mobile payment system and a contactless mobile payment method, and the contactless mobile payment system comprises a front-end payment device and a cloud management system, wherein the front-end payment device is in communication connection with the cloud management system, the front-end payment device comprises a shell and a bracket, the shell is used for placing a region to be paid through the bracket, a display screen and an image acquisition device are nested on the upper end surface of the shell, and the cloud management system is provided with a face original data binding module, a face defect recognition module, a face data acquisition module, a face data reconstruction module, an identity recognition module and a payment data processing module; according to the scheme, the face image is shot, classified, reconstructed, extracted and compared, so that a relatively accurate identity authentication result can be obtained, and payment operation is facilitated for users wearing masks and the like with face shields.
Description
Technical Field
The invention relates to the technical field of mobile payment, in particular to a contactless mobile payment system and a contactless mobile payment method.
Background
Traditional shopping payment methods are including cash payment, bank card payment, credit card payment etc., along with internet of things's development, mobile payment begins to be extensively by the practicality, current mobile payment mainly by two kinds, one kind is to sweep the sign indicating number payment through user's cell-phone, this kind of mode convenient and fast, the security performance is high, but has the payment leak simultaneously, consequently, some internet salaries have developed biological characteristic identification payment methods, it is common have fingerprint payment and face identification payment, wherein, because contactless payment during face identification payment, but special occasion uses safe convenient more, it is highly popular with the user.
The face recognition is a biological feature recognition technology for identity authentication based on human physiognomic feature information, and the maximum feature of the technology is that personal information can be prevented from being leaked and the technology is used for recognition in a non-contact mode. Because of the spread of new crown epidemic situation in the world, people urgently need the non-contact mode to replace the traditional contact payment mode on the one hand, and people also encounter a lot of difficulties in face payment on the other hand.
Disclosure of Invention
The invention aims to solve the problem that the existing face payment system is low in identification efficiency of shields such as a mask worn by a user, and provides a non-contact mobile payment system and a non-contact mobile payment method.
In order to achieve the technical purpose, the invention provides a technical scheme that a contactless mobile payment system and a contactless mobile payment method are characterized in that: the system comprises front-end payment equipment and a cloud management system, wherein the front-end payment equipment is in communication connection with the cloud management system and comprises a shell and a support, the shell is used for placing an area to be paid through the support, a display screen and image acquisition equipment are nested on the upper end face of the shell, and the cloud management system is provided with a face original data binding module, a face defect recognition module, a face data acquisition module, a face data reconstruction module, an identity recognition module and a payment data processing module;
the display screen is used for displaying a two-dimensional code picture for payment or synchronously displaying a face image;
the image acquisition equipment acquires a face image of a user and transmits the face image to the face data acquisition module through a network;
the face original data binding module is used for acquiring original face data of a single user from the mobile payment cloud data platform, processing the original face data of the single user through the face data reconstruction module to obtain reconstructed face data, binding the original face data and the reconstructed face data to generate a binding data packet, and storing the binding data packet in a comparison unit of the identity recognition module;
the face defect identification module acquires face image data of the face data acquisition module, identifies the type of a face obstruction in the face image data, and shares a judgment result to the face data reconstruction module;
the face data reconstruction module is used for virtually filling face image data with a shielding object, sending the filled face reconstruction image data to a comparison unit of the identity recognition module to be compared with the binding data packet, and verifying the identity of a user;
and the payment data processing module executes payment operation after the face information of the user is compared without errors.
The human face data acquisition module comprises a human face detection unit, a human face display unit and a behavior recognition unit;
the human face detection unit dynamically acquires human face image data through image acquisition equipment and automatically focuses;
the face display unit dynamically displays face image information through a display screen, so that a user can conveniently adjust a camera shooting angle;
the behavior identification unit randomly acquires a plurality of pieces of face image data by detecting the user behavior data.
The identity recognition module also comprises a face feature extraction unit and a result identification unit;
the human face feature extraction module is used for extracting features of a plurality of groups of human face image data in the human face data acquisition module and extracting features of the human face image data in the binding data packet stored in the comparison unit to generate a feature comparison template; comparing the feature points extracted from the multiple groups of face image data with the feature points in the feature comparison template one by one through a face recognition core algorithm, and finally returning a recognition value;
a result identification unit: comparing the maximum similarity value with the set minimum similarity threshold value according to a plurality of groups of recognition values obtained by a face recognition core algorithm to determine the identity of the user, synchronously calibrating the picture data of the maximum similarity value, and further replacing the face image data in the original comparison unit.
The user behavior data comprises blink data, gesture data and mouth shape data.
The payment data processing module comprises a data setting unit, a camera shooting guide unit, a quality judgment unit, a weight setting unit and a random photographing unit;
the behavior data setting unit comprises blink frequency setting, gesture comparison data setting and mouth opening and closing degree comparison data setting;
the camera shooting guide unit is used for guiding a user to adjust the face angle and acquiring a qualified image;
the weight setting unit is used for setting the size of the lowest similarity threshold in the comparison unit;
the random photographing unit obtains effective pictures according to the behavior data and randomly selects a plurality of pictures from the effective pictures as a plurality of groups of face image data;
the quality evaluation unit judges whether the real-time shot picture meets the specification or not, and transmits the judgment result to the shooting guide unit to serve as a basis for guiding the user to adjust the face angle.
Step S1, the user stands in front of the front-end payment device, selects to pay by scanning the code or pay by brushing the face according to the user 'S will, the device sets the payment mode according to the user' S selection, displays the two-dimensional code for payment on the display screen of the device or starts the image acquisition device, if the user selects the mobile phone to scan the two-dimensional code for payment, the image acquisition device is not started; if the user selects face brushing payment, the image acquisition equipment is started, and the step S2 is executed;
step S2, displaying real-time face images on a display screen, shooting a plurality of qualified square face images according to behavior data of the user face, and transmitting the qualified square face images to a face data acquisition module;
step S3, the face defect recognition module acquires the qualified face image data acquired by the face data acquisition module, and classifies the sheltering object according to whether the face image is sheltered, wherein the sheltering object is a mask or sunglasses;
step S4, importing the shielding face image into a face data reconstruction module, preprocessing the shielding face image through the face data reconstruction module, and sending the processed shielding face image and the non-shielding face image to an identity recognition module;
step S5, the identity identification module extracts facial features of the processed shielding face image and the shielding-free face image, and extracts the features of the face image data in the binding data packet stored in the comparison unit to generate a feature comparison template; comparing feature points extracted from the groups of processed shielding face images and non-shielding face images with feature points in a feature comparison template one by one through a face identification core algorithm, and finally returning an acquaintance value;
step S6, comparing the maximum similarity value with the set minimum similarity threshold value according to several groups of similarity values obtained by the face recognition core algorithm, determining the user identity, synchronously calibrating the face image data of the maximum similarity value, and further replacing the face image data in the original comparison unit;
and step S7, after the face information of the user is successfully compared, the payment data processing module carries out payment transaction, and the transaction result is displayed through the display screen to be known by the user.
When step S2 is executed, if the collected picture is unqualified, the display screen prompts to collect again and displays an image collection outline frame, the user can know the direction and the angle of the face adjustment through the voice or the character mode, and when the face direction and the angle are adjusted correctly, the current image is locked through blinking or mouth shape or gesture.
The preprocessing of the shielding face image through the face data reconstruction module comprises the following steps:
a1, judging the type of a shelter for sheltering the face image, wherein the type of the shelter comprises a sunglass or a mask;
a2, virtually adjusting the images of the face to be shielded, namely correcting or filling the shielding area of the face shielding object by simulating sunglasses or a mask;
and A3, performing virtual occlusion on the original face data to generate a face occlusion comparison template.
The invention has the beneficial effects that: according to the contactless mobile payment system and the contactless mobile payment method, the accurate identity authentication result can be obtained by shooting, classifying, reconstructing the image, extracting the characteristics and comparing the face image, and the payment operation is convenient for users wearing masks and the like with face shelters; the accuracy rate of recognition is improved while the payment convenience is guaranteed.
Drawings
Fig. 1 is a schematic structural diagram of a contactless mobile payment system according to the present invention.
The notation in the figure is: the system comprises a front-end payment device, a 2-cloud management system, an 11-image acquisition device, a 12-display screen, a 21-face original data binding module, a 22-face data acquisition module, a 23-face defect recognition module, a 24-face data reconstruction module, a 25-identity recognition module and a 26-payment data processing module.
Detailed Description
For the purpose of better understanding the objects, technical solutions and advantages of the present invention, the following detailed description of the present invention with reference to the accompanying drawings and examples should be understood that the specific embodiment described herein is only a preferred embodiment of the present invention, and is only used for explaining the present invention, and not for limiting the scope of the present invention, and all other embodiments obtained by a person of ordinary skill in the art without making creative efforts shall fall within the scope of the present invention.
Example (b): as shown in fig. 1, a contactless mobile payment system and method includes a front-end payment device 1 and a cloud management system 2, the front-end payment device 1 is in communication connection with the cloud management system 2, the front-end payment device 1 includes a housing and a support, the housing is placed in a region to be paid through the support, a display screen 12 and an image acquisition device 11 are nested on an upper end surface of the housing, and the cloud management system 2 is provided with a face original data binding module 21, a face defect recognition module 23, a face data acquisition module 22, a face data reconstruction module 24, an identity recognition module 25 and a payment data processing module 26;
the display screen 12 is used for displaying a two-dimensional code picture for payment or synchronously displaying a face image;
the image acquisition device 11 acquires a face image of a user and transmits the face image to the face data acquisition module 22 through a network;
the face original data binding module 21 is used for acquiring original face data of a single user from the mobile payment cloud data platform, processing the original face data of the single user by the face data reconstruction module 24 to obtain reconstructed face data, binding the original face data and the reconstructed face data to generate a binding data packet, and storing the binding data packet in a comparison unit of the identity recognition module 25;
the face defect identification module 23 is used for acquiring the face image data of the face data acquisition module 22, identifying the type of a face obstruction in the face image data, and sharing the judgment result to the face data reconstruction module 24;
the face data reconstruction module 24 is configured to virtually fill face image data with a blocking object, send the filled face reconstruction image data to a comparison unit of the identity recognition module 25, compare the filled face reconstruction image data with the binding data packet, and verify the identity of the user;
and the payment data processing module 26 executes payment operation after the face information of the user is compared without errors.
The face data acquisition module 22 comprises a face detection unit, a face display unit and a behavior identification unit;
the human face detection unit dynamically collects human face image data through the image collection equipment 11 and automatically focuses;
the face display unit dynamically displays face image information through the display screen 12, so that a user can conveniently adjust a camera shooting angle;
and the behavior identification unit is used for randomly acquiring a plurality of pieces of face image data by detecting the user behavior data.
The identity recognition module 25 further comprises a face feature extraction unit and a result identification unit;
the human face feature extraction module performs feature extraction on a plurality of groups of human face image data in the human face data acquisition module 22, and performs feature extraction on the human face image data in the binding data packet stored in the comparison unit to generate a feature comparison template; comparing the feature points extracted from the multiple groups of face image data with the feature points in the feature comparison template one by one through a face recognition core algorithm, and finally returning a recognition value;
a result identification unit: comparing the maximum similarity value with the set minimum similarity threshold value according to a plurality of groups of recognition values obtained by a face recognition core algorithm to determine the identity of the user, synchronously calibrating the picture data of the maximum similarity value, and further replacing the face image data in the original comparison unit.
The user behavior data includes blink data, gesture data, and mouth shape data.
The payment data processing module 26 comprises a data setting unit, a camera shooting guide unit, a quality evaluation unit, a weight setting unit and a random photographing unit;
the behavior data setting unit comprises the setting of the blinking times, the setting of gesture comparison data and the setting of mouth opening and closing degree comparison data;
the camera shooting guide unit is used for guiding a user to adjust the face angle and acquiring a qualified image;
the weight value setting unit is used for setting the size of the lowest similarity threshold value in the comparison unit;
the random photographing unit is used for obtaining effective pictures according to the behavior data and randomly selecting a plurality of pictures from the effective pictures as a plurality of groups of face image data;
and the quality evaluation unit is used for judging whether the real-time shot picture meets the specification or not, and transmitting the judgment result to the camera shooting guide unit to serve as a basis for guiding the user to adjust the face angle.
Step S1, the user stands in front of the front-end payment device 1, selects to pay by scanning a code or by brushing a face according to the user 'S will, the device sets a payment mode according to the user' S selection, displays a two-dimensional code for payment on the display screen 12 of the device or starts the image acquisition device 11, if the user selects a mobile phone to scan the two-dimensional code for payment, the image acquisition device 11 is not started; if the user selects the face-brushing payment, the image capturing device 11 is turned on, and step S2 is executed.
Step S2, displaying the real-time face image on the display screen 12, taking a plurality of qualified square face images according to the behavior data of the user face, and transmitting the images to the face data acquisition module 22; when step S2 is executed, if the collected picture is not qualified, the display screen 12 prompts to re-collect and displays an image collection outline box, so that the user can know the direction and angle of the facial adjustment in the form of voice or characters, and when the direction and angle of the facial adjustment are correct, the current image is locked by blinking or by mouth shape or by gesture.
Step S3, the face defect recognition module 23 obtains the qualified face image data collected by the face data collection module 22, and classifies the blocking object according to whether the face image is blocked, where the blocking object is a mask or sunglasses.
Step S4, importing the occluded face image into the face data reconstruction module 24, preprocessing the occluded face image by the face data reconstruction module 24, and sending the processed occluded face image and the non-occluded face image to the identity recognition module 25.
Step S5, the identity identification module extracts facial features of the processed shielding face image and the shielding-free face image, and extracts the features of the face image data in the binding data packet stored in the comparison unit to generate a feature comparison template; and comparing the feature points extracted from the groups of processed shielding face images and non-shielding face images with the feature points in the feature comparison template one by one through a face identification core algorithm, and finally returning the acquaintance values.
And step S6, comparing the maximum similarity value with the set minimum similarity threshold value according to a plurality of groups of similarity values obtained by the face recognition core algorithm, determining the identity of the user, synchronously calibrating the face image data with the maximum similarity value, and further replacing the face image data in the original comparison unit.
In step S7, after the comparison of the user face information is successful, the payment data processing module 26 performs payment transaction, and displays the transaction result through the display screen 12 for the user to know.
The preprocessing of the occlusion face image by the face data reconstruction module 24 includes:
a1, judging the type of a shelter for sheltering the face image, wherein the type of the shelter comprises a sunglass or a mask;
a2, virtually adjusting the images of the face to be shielded, namely correcting or filling the shielding area of the face shielding object by simulating sunglasses or a mask;
and A3, performing virtual occlusion on the original face data to generate a face occlusion comparison template.
The above-mentioned embodiments are preferred embodiments of the contactless mobile payment system and method of the present invention, and not intended to limit the scope of the present invention, which includes but is not limited to the embodiments, and all equivalent changes in shape and structure made by the present invention are within the scope of the present invention.
Claims (8)
1. A contactless mobile payment system characterized by: the system comprises front-end payment equipment and a cloud management system, wherein the front-end payment equipment is in communication connection with the cloud management system and comprises a shell and a support, the shell is used for placing an area to be paid through the support, a display screen and image acquisition equipment are nested on the upper end face of the shell, and the cloud management system is provided with a face original data binding module, a face defect recognition module, a face data acquisition module, a face data reconstruction module, an identity recognition module and a payment data processing module;
the display screen is used for displaying a two-dimensional code picture for payment or synchronously displaying a face image;
the image acquisition equipment acquires a face image of a user and transmits the face image to the face data acquisition module through a network;
the face original data binding module is used for acquiring original face data of a single user from the mobile payment cloud data platform, processing the original face data of the single user through the face data reconstruction module to obtain reconstructed face data, binding the original face data and the reconstructed face data to generate a binding data packet, and storing the binding data packet in a comparison unit of the identity recognition module;
the face defect identification module acquires face image data of the face data acquisition module, identifies the type of a face obstruction in the face image data, and shares a judgment result to the face data reconstruction module;
the face data reconstruction module is used for virtually filling face image data with a shielding object, sending the filled face reconstruction image data to a comparison unit of the identity recognition module to be compared with the binding data packet, and verifying the identity of a user;
and the payment data processing module executes payment operation after the face information of the user is compared without errors.
2. A contactless mobile payment system according to claim 1, characterized in that:
the human face data acquisition module comprises a human face detection unit, a human face display unit and a behavior recognition unit;
the human face detection unit dynamically acquires human face image data through image acquisition equipment and automatically focuses;
the face display unit dynamically displays face image information through a display screen, so that a user can conveniently adjust a camera shooting angle;
the behavior identification unit randomly acquires a plurality of pieces of face image data by detecting the user behavior data.
3. A contactless mobile payment system according to claim 1 or 2, characterized in that:
the identity recognition module also comprises a face feature extraction unit and a result identification unit;
the human face feature extraction module is used for extracting features of a plurality of groups of human face image data in the human face data acquisition module and extracting features of the human face image data in the binding data packet stored in the comparison unit to generate a feature comparison template; comparing the feature points extracted from the multiple groups of face image data with the feature points in the feature comparison template one by one through a face recognition core algorithm, and finally returning a recognition value;
a result identification unit: comparing the maximum similarity value with the set minimum similarity threshold value according to a plurality of groups of recognition values obtained by a face recognition core algorithm to determine the identity of the user, synchronously calibrating the picture data of the maximum similarity value, and further replacing the face image data in the original comparison unit.
4. A contactless mobile payment system according to claim 3, characterized in that: the user behavior data comprises blink data, gesture data and mouth shape data.
5. A contactless mobile payment system according to claim 4, characterized in that:
the payment data processing module comprises a data setting unit, a camera shooting guide unit, a quality judgment unit, a weight setting unit and a random photographing unit;
the behavior data setting unit comprises blink frequency setting, gesture comparison data setting and mouth opening and closing degree comparison data setting;
the camera shooting guide unit is used for guiding a user to adjust the face angle and acquiring a qualified image;
the weight setting unit is used for setting the size of the lowest similarity threshold in the comparison unit;
the random photographing unit obtains effective pictures according to the behavior data and randomly selects a plurality of pictures from the effective pictures as a plurality of groups of face image data;
the quality evaluation unit judges whether the real-time shot picture meets the specification or not, and transmits the judgment result to the shooting guide unit to serve as a basis for guiding the user to adjust the face angle.
6. A contactless mobile payment method, characterized by: the method comprises the following steps:
step S1, the user stands in front of the front-end payment device, selects to pay by scanning the code or pay by brushing the face according to the user 'S will, the device sets the payment mode according to the user' S selection, displays the two-dimensional code for payment on the display screen of the device or starts the image acquisition device, if the user selects the mobile phone to scan the two-dimensional code for payment, the image acquisition device is not started; if the user selects face brushing payment, the image acquisition equipment is started, and the step S2 is executed;
step S2, displaying real-time face images on a display screen, shooting a plurality of qualified square face images according to behavior data of the user face, and transmitting the qualified square face images to a face data acquisition module;
step S3, the face defect recognition module acquires the qualified face image data acquired by the face data acquisition module, and classifies the sheltering object according to whether the face image is sheltered, wherein the sheltering object is a mask or sunglasses;
step S4, importing the shielding face image into a face data reconstruction module, preprocessing the shielding face image through the face data reconstruction module, and sending the processed shielding face image and the non-shielding face image to an identity recognition module;
step S5, the identity identification module extracts facial features of the processed shielding face image and the shielding-free face image, and extracts the features of the face image data in the binding data packet stored in the comparison unit to generate a feature comparison template; comparing feature points extracted from the groups of processed shielding face images and non-shielding face images with feature points in a feature comparison template one by one through a face identification core algorithm, and finally returning an acquaintance value;
step S6, comparing the maximum similarity value with the set minimum similarity threshold value according to several groups of similarity values obtained by the face recognition core algorithm, determining the user identity, synchronously calibrating the face image data of the maximum similarity value, and further replacing the face image data in the original comparison unit;
and step S7, after the face information of the user is successfully compared, the payment data processing module carries out payment transaction, and the transaction result is displayed through the display screen to be known by the user.
7. A contactless mobile payment method according to claim 6, characterized in that: the method comprises the following steps:
when step S2 is executed, if the collected picture is not qualified, the display screen prompts to collect again, displays an image collection outline frame, lets the user know the direction and angle of the face adjustment through the form of voice or characters, and locks the current image through blinking or mouth shape or gesture when the face direction and angle adjustment is correct.
8. A contactless mobile payment method according to claim 6, characterized in that: the method comprises the following steps: the preprocessing of the shielding face image through the face data reconstruction module comprises the following steps:
a1, judging the type of a shelter for sheltering the face image, wherein the type of the shelter comprises a sunglass or a mask;
a2, virtually adjusting the images of the face to be shielded, namely correcting or filling the shielding area of the face shielding object by simulating sunglasses or a mask;
and A3, performing virtual occlusion on the original face data to generate a face occlusion comparison template.
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| CN112766973A (en) * | 2021-01-19 | 2021-05-07 | 湖南校智付网络科技有限公司 | Face payment terminal |
| CN115619410A (en) * | 2022-10-19 | 2023-01-17 | 闫雪 | Self-adaptive financial payment platform |
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