CN107103218B - Service implementation method and device - Google Patents
Service implementation method and device Download PDFInfo
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- CN107103218B CN107103218B CN201610939700.6A CN201610939700A CN107103218B CN 107103218 B CN107103218 B CN 107103218B CN 201610939700 A CN201610939700 A CN 201610939700A CN 107103218 B CN107103218 B CN 107103218B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
- G06F21/31—User authentication
- G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- 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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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/168—Feature extraction; Face representation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2221/00—Indexing scheme relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F2221/21—Indexing scheme relating to G06F21/00 and subgroups addressing additional information or applications relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F2221/2133—Verifying human interaction, e.g., Captcha
Abstract
The application provides a service implementation method and device. The method comprises the following steps: receiving a service request, wherein the service request carries a face image of a service requester; calculating the matching degree of the face image and each real face image in the face image library; when the matching degree of the face image carried in the service request and a certain real face image in the face image library reaches a first threshold value, completing related services based on a service account corresponding to the real face image; when the matching degree of the face image carried in the service request and any real face image in the face image library does not reach a first threshold value, but the matching degree of the face image and one or more real face images in the face image library reaches a second threshold value, acquiring one or more real signatures corresponding to the one or more real face images in the face image library; and when the handwriting of the signature input by the service requester is matched with the acquired handwriting of one of the real signatures, finishing the related service based on the service account corresponding to the real signature.
Description
Technical Field
The present application relates to the field of communications technologies, and in particular, to a method and an apparatus for implementing a service.
Background
With the rapid development of internet technology, more and more services can be realized through the internet, such as: payment transactions, ticket purchase transactions, etc. In the related art, the identity of a user can be identified through a face recognition technology, and then related services are completed. However, the algorithm of the face recognition technology has certain limitations, and cannot completely ensure accurate recognition, which brings risks to the business.
Disclosure of Invention
In view of this, the present application provides a service implementation method and apparatus.
Specifically, the method is realized through the following technical scheme:
a service implementation method is applied to a server side, and the method comprises the following steps:
receiving a service request sent by a service terminal, wherein the service request carries a face image of a service requester;
calculating the matching degree of the face image and each real face image in a face image library through a face recognition algorithm;
when the matching degree of the face image carried in the service request and a certain real face image in the face image library reaches a first threshold value, completing related services based on a service account corresponding to the real face image in the face image library;
when the matching degree between the face image carried in the service request and any real face image in the face image library does not reach the first threshold value, but the matching degree between the face image carried in the service request and one or more real face images in the face image library reaches a second threshold value, acquiring one or more real signatures corresponding to the one or more real face images in the face image library, wherein the second threshold value is smaller than the first threshold value;
and when the handwriting of the signature input by the service requester is matched with the acquired handwriting of one of the real signatures, finishing the related service based on the service account corresponding to the real signature.
A service implementation device is applied to a server, and the device comprises:
the request receiving unit is used for receiving a service request sent by a service terminal, wherein the service request carries a face image of a service requester;
the matching calculation unit is used for calculating the matching degree of the face image and each real face image in the face image library through a face recognition algorithm;
the first operation unit is used for completing related services based on a service account corresponding to a real face image in the face image library when the matching degree of the face image carried in the service request and the real face image in the face image library reaches a first threshold value;
a signature obtaining unit, configured to obtain one or more real signatures corresponding to one or more real face images in the face image library when the matching degree between a face image carried in the service request and any real face image in the face image library does not reach the first threshold, but the matching degree between the face image carried in the service request and one or more real face images in the face image library reaches a second threshold, where the second threshold is smaller than the first threshold;
and the second operation unit is used for finishing related services based on the service account corresponding to the real signature when the handwriting of the signature input by the service requester is matched with the acquired handwriting of the real signature.
The above description shows that the signature verification and the face recognition can be combined to determine the identity of the user, so that the user is assisted to realize related services, the defect that a face recognition algorithm is not accurate enough is overcome, and the service risk is reduced. On the other hand, in daily life, because the signature verification is attached to the habit of the user, the links of signature verification are increased, the sense of incongruity of the user is not increased, and the use experience of the user is not reduced.
Drawings
Fig. 1 is a flowchart illustrating a service implementation method according to an exemplary embodiment of the present application.
Fig. 2 is a schematic flow chart illustrating signature registration according to an exemplary embodiment of the present application.
FIG. 3 is a page view of a registration signature shown in an exemplary embodiment of the present application.
Fig. 4A and 4B are schematic flow diagrams illustrating a payment service implementing method according to an exemplary embodiment of the present application.
Fig. 5 is a schematic structural diagram of a service implementation apparatus according to an exemplary embodiment of the present application.
Fig. 6 is a block diagram of a service implementation apparatus according to an exemplary embodiment of the present application.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It is to be understood that although the terms first, second, third, etc. may be used herein to describe various information, such information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present application. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
In the related art, for example, when a twin or a brother or sister with a long facial image appears, the face recognition technique may not accurately identify the payer due to certain limitations of the algorithm, which may affect the user experience. On the other hand, when someone maliciously pretends to pay, the user may also be lost money.
In order to solve the above problems, the present application provides a service implementation scheme, which combines signature verification and face recognition technologies to identify the identity of a user, thereby improving the security of services such as payment, ticket taking, medicine taking, and the like.
Fig. 1 is a flowchart illustrating a service implementation method according to an exemplary embodiment of the present application.
Referring to fig. 1, the service implementation method may be applied to a server, and specifically may be a server or a server cluster deployed by a service provider, where the service implementation method may include the following steps:
step 101, receiving a service request sent by a service terminal, wherein the service request carries a face image of a service requester.
In this embodiment, the service request may include: a payment request, a drug withdrawal request, a ticket withdrawal request, etc. The business terminal can be a cash register of a merchant, a ticket taking terminal of a cinema, a self-service medicine taking terminal of a hospital and the like, and the application does not specially limit the business terminal.
In this embodiment, the service terminal is usually provided with or associated with a camera for shooting a face image of a service requester. The service requester or the service-related staff can select a 'face brushing' button in the service terminal to start the camera to collect the face image. Taking the payment service as an example, after the cashier selects 'face brushing payment', the payer can face the camera so that the camera can collect the face image of the payer.
In this embodiment, after the face image of the service requester is collected, the face image may be carried in a service request and sent to the server, where the service request usually also carries some service information. Taking the payment service as an example, the service request may also carry payment amount, payment object, current time, and the like, and the processing and implementation of this part may refer to related technologies, which is not described in detail herein.
And 102, calculating the matching degree of the face image and each real face image in a face image library through a face recognition algorithm.
Based on the foregoing step 101, after receiving a service request of a face image carrying a service requester, the server may calculate a matching degree between the face image and each real face image in the face image library through a face recognition algorithm.
In this embodiment, the face image library stores real face images of users. In an example, the real face image may be registered in the server by the user, and still taking a payment service as an example, when the user starts a face payment function, the user may upload the face image of the user to serve as an identification reference of the server. In another example, the real face image may also be obtained automatically by the server, such as: the server can automatically acquire and store the real face image of the user with real name authentication from the public security network.
In an example, the facial image library in this step may be a facial image library composed of real facial images of all users who start a facial service function. In another example, to improve the rate and accuracy of facial image recognition, the facial image library in this step may also be a facial image library corresponding to business time and business object.
In this embodiment, the face recognition algorithm may include an Eigenface algorithm (Eigenface), an LBP (Local Binary Patterns) algorithm, and the like, which is not limited in this application. The presentation form of the matching degree can be percentage, such as: the matching degree of the face image carried in the service request and a certain real face image is 75%, the display form of the matching degree can also be a matching score, taking a full score of 100 as an example, and the matching degree can also be represented as 75.
Step 103, when the matching degree between the face image carried in the service request and a real face image in the face image library reaches a first threshold, completing the related service based on the service account corresponding to the real face image in the face image.
In this embodiment, the first threshold may be set by a developer, and a value of the first threshold is generally higher, for example: 90%, etc. When the matching degree between the face image carried in the service request and a real face image in the face image library reaches the first threshold, the confidence of the service requester is considered to be very high, and the related service can be completed based on the service account corresponding to the real face image without signature verification. The business account may be a user account corresponding to the real facial image, and when the business request is a payment request, the business account may also be a bank account corresponding to the real facial image, and the like.
And 104, when the matching degree between the face image carried in the service request and any real face image in the face image library does not reach the first threshold value, but the matching degree between the face image carried in the service request and one or more real face images in the face image library reaches a second threshold value, acquiring one or more real signatures corresponding to the one or more real face images in the face image library, wherein the second threshold value is smaller than the first threshold value.
In this embodiment, the second threshold may also be set by a developer, and the second threshold is smaller than the first threshold, for example: 60%, 70%, and the like, when the matching degree between the face image carried by the service request and any real face image in the face image library does not reach the first threshold, but the matching degree between the face image carried by the service request and one or more real face images in the face image library reaches a second threshold, signature verification can be performed to reduce the risk of the service. In particular, one or more real signatures corresponding to the one or more real face images may be obtained. Such as: for the real face images with the matching degree reaching the second threshold, the user account corresponding to each real face image may be determined first, and then the corresponding real signature may be obtained according to the user account. The authentic signature is typically registered by the user with the service.
And 105, when the handwriting of the signature input by the service requester is matched with the acquired handwriting of one real signature, finishing the related service based on the service account corresponding to the real signature.
Based on the foregoing step 104, after the one or more real signatures are obtained, it may be determined whether the handwriting of the signature input by the service requester matches the handwriting of the real signature. Wherein the signature can be input by a service requester in a handwritten signature associated with the service terminal. For example, a cashier of a merchant may provide a handwritten signature pad for signature by a payer. The service terminal may also add the signature input by the service requester to the service request and send the service request to the service end, and the service terminal may also send the signature to the service end when receiving the request for obtaining the signature sent by the service end, which is not particularly limited in this application.
In this embodiment, according to the related art, the signatures are usually in a serial form in the device, and the step may calculate the matching degree between the two signatures by calculating the similarity of the corresponding matrixes of the two signatures, and when the matching degree between the two signatures reaches a preset matching degree, it may be determined that the two signatures match. Of course, other ways may also be adopted to determine whether the two signatures are matched, and the processing and implementation of this part may refer to related technologies, which are not described in detail herein.
In this step, when the signature input by the service requester matches the handwriting of one of the one or more real signatures, the related service is completed based on the service account corresponding to the real signature.
It should be noted that, in the present application, the service account may correspond to one or more real face images, and the service account may also correspond to one or more real signatures. In other words, a unique corresponding service account can be determined by either a real face image or a real signature.
The above description shows that the signature verification and the face recognition can be combined to determine the identity of the user, so that the user is assisted to realize related services, the defect that a face recognition algorithm is not accurate enough is overcome, and the service risk is reduced. On the other hand, in daily life, because the signature verification is attached to the habit of the user, the links of signature verification are increased, the sense of incongruity of the user is not increased, and the use experience of the user is not reduced.
Fig. 2 is a schematic flow chart illustrating signature registration according to an exemplary embodiment of the present application.
Referring to fig. 2, the signature registration process can be applied to the client, and includes the following steps:
step 201, detecting that a face brushing function is started.
In this embodiment, the user may select to start the "face brushing function" through the client, and the client may further display the page shown in fig. 3 for the user to input a signature. Of course, in practical application, the client may also call an externally-connected handwriting signature pad to collect the signature input by the user.
Step 202, collecting the signature input by the user.
Step 203, complexity detection is performed on the signature.
Based on the foregoing step 202, after the signature input by the user is collected, complexity detection may be performed on the signature, such as: detecting the stroke number of the signature, and determining that the signature passes the complexity detection when the stroke number is larger than a preset number.
It should be noted that the signature may be a name of the user, and the signature may also be a special character input by the user, which is specifically input by the user.
Step 204, when the signature passes the complexity detection, the signature input by the user is collected again.
And step 205, when the two signatures are consistent, uploading the signatures to the service end to finish signature registration.
In this embodiment, similar to the password setting, the user is usually required to input two signatures, when the two signatures input by the user are consistent, one of the two signatures can be uploaded to the service end as a real signature to complete signature registration, and the service end can further store the real signature under a corresponding user account. The method for checking the consistency of signatures can refer to the related art. Optionally, the signature complexity detection and the consistency check may also be completed by the server side, which is not particularly limited in this application.
The following describes the implementation process of the present application in detail by taking a payment service as an example.
Fig. 4A and 4B are schematic flow diagrams illustrating a payment service implementing method according to an exemplary embodiment of the present application.
Referring to fig. 4A and 4B, the payment service implementation method may include two stages, one is a consumer subscription stage and the other is a payment stage. Wherein the reservation phase may comprise the steps of:
and step 401, the consumer appoints KFC experience face-refreshing payment through the client.
In this step, the consumer can pre-order the KFC experience for face-brushing payment through the client, and generally speaking, the consumer also needs to input the experience time and store information of the KFC at the time of the appointment. Suppose the experience time is 2016, 10 months and 10 days, and the store information is KFC Hangzhou star Daidai stores. The client can further send a reservation application carrying the experience time and the store information to the server, and prompt information is generated according to a reservation result returned by the server.
Step 402, the server establishes a face image library corresponding to experience time and store information.
Based on the foregoing step 401, after receiving the appointment application, the server may first determine whether a facial image library corresponding to the experience time and store information is established. If not, a facial image library corresponding to the experience time and store information can be established. If so, step 403 may be performed.
In this embodiment, the division reference of the experience time may be set by a developer according to a service type, for example: the unit of the time is day or hour, and the application is not limited to this.
And step 403, the server adds the real face image of the consumer to the face image library corresponding to the experience time and store information.
In this embodiment, the server may obtain a registered real face image based on account information of the consumer, and add the real face image to the face image library.
With continued reference to fig. 4B, the payment phase may include the following steps:
and step 404, a camera associated with the cash register terminal collects the payment face image of the consumer.
In this embodiment, the consumer can consume from 10/2016 to KFC hangzhou starlight avenue store, and after the consumer orders a meal, the cashier can select "face-brushing payment" in the cash terminal, and then call the camera associated with the cash terminal to collect the face image of the consumer.
And 405, the cashier terminal carries the payment face image in a payment request and sends the payment face image to a server.
In this embodiment, besides the payment face image, the payment request may generally include: store information, payment time, payment amount, etc.
And step 406, the server determines a face image library corresponding to the payment time and store information, and calculates the matching degree of the payment face image and each real face image in the face image library.
Based on the foregoing step 405, after receiving the payment request, the server may determine a facial image library corresponding to 2016, 10/KFC hangzhou starlight avenue shop, and calculate matching degrees of the payment facial image and each real facial image in the facial image library, respectively.
Step 407, when the matching degree between the payment face image and only one real face image in the face images reaches 90%, the server completes payment based on the payment account corresponding to the real face image.
And step 408, when the matching degree of the payment face image and any real face image in the face image library does not reach 90%, but the matching degree of the payment face image and a real face image reaches 60%, the server side acquires a real signature corresponding to the real face image.
In this step, the server may obtain a corresponding real signature according to the payment account corresponding to the real face image, and the registration process of the real signature may refer to the embodiment shown in fig. 2, which is not described herein again. Assuming that the payment account numbers of the real face images are payment account numbers 1 respectively, and the obtained real signature is a real signature.
And 409, when the handwriting of the payment signature input by the consumer is matched with the handwriting of the real signature, completing related services based on the payment account corresponding to the real signature.
In this embodiment, the consumer can sign through the handwritten signature pad that the cashier provided after gathering the face image in order to be as the payment signature of this payment. In one example, the cashier terminal may send the payment signature to the server also carried in the payment request. In another example, the service end may send a signature collection instruction to the cash register terminal when it is determined that the matching degree between the payment face image and any one of the real face images in the face image library does not reach 90%, but the matching degree between the payment face image and one or more real face images reaches 60%, and the cash register terminal may send the collected payment signature to the service end after receiving the instruction. Optionally, the cashier may also sign the customer after the service end returns the instruction. Furthermore, when the server determines that the matching degree of the payment face image and any real face image in the face image library does not reach 60%, a prompt of payment error can be returned to the cash register terminal, and then the signature of a consumer is not needed. The application does not make any special restrictions on the signing time and the transmission time of the payment signature.
In this step, still taking the example in step 408 as an example, assuming that the payment signature matches the real signature 1, the payment can be completed based on the payment account number 1 corresponding to the real signature 1.
And step 410, when the handwriting of the payment signature is not matched with the handwriting of the real signature, the server returns the real signature to the cash register terminal so that a cash register can check manually.
In this embodiment, in order to avoid the failure of handwriting matching caused by the insufficient accuracy of the handwriting matching algorithm, the server may send the real signature 1 to the cash register terminal when the handwriting of the payment signature is not matched with the handwriting of the real signature 1, so that the cash register terminal can display the handwriting for the cash register. The cashier can manually determine whether the consumer is a legitimate user corresponding to the authentic signature 1, such as: the consumer can be provided with a mobile phone number, and the consumer can also show an identity card and the like.
And 411, the server finishes the payment according to the check result of the cashier.
In this step, the cashier can send the manual check result to the server through the cashier terminal, and the server can further complete the payment operation according to the check result. Assuming that the cashier manually determines that the consumer is a legal user corresponding to the real signature 1, the service end can complete payment based on the payment account number 1 corresponding to the real signature 1. When the cashier manually determines that the consumer is not the legal user corresponding to the real signature 1, the service end can return a message of canceling payment, and the consumer can pay in other modes.
Alternatively, in another example, assuming that a sister and a sister in a twin reserve consumption from 2016 10 th to KFC Hangzhou starlight Daddy store, the face image library corresponding to 2016 10 th and KFC Hangzhou starlight Daddy store stores the real face images of the sister and the sister. And supposing that the sister pays for the money after consumption, because of the extraordinary image of the sister and the sister, the server determines that the matching degree of two real face images in the face image library and the collected face image for payment of the sister is more than 60 percent but less than 90 percent. At this time, the server can determine to adopt the payment account of the sister to pay according to the payment signature input by the sister. Because in daily life, the consumer often all need carry out the signature after the payment of punching the card, consequently this application combines signature check-up and face identification in order to realize the payment, and the user's of laminating daily custom is experienced with the payment to the rate of accuracy of "pay by brushing the face" has been improved.
Optionally, in practical application, a situation that the matching degree between the payment face image and two or more real face images in the face image library reaches 90% may also occur, at this time, signature verification may also be combined, and when handwriting of a payment signature matches handwriting of a certain real signature, payment may be completed based on a payment account corresponding to the real signature.
Optionally, in order to further improve the rate and accuracy of face recognition, after the server completes payment based on the real face image or the payment account corresponding to the real signature, the real face image corresponding to the payment account in the face image library may be deleted, so as to reduce the number of real face images in the face image library. In another example, when the experience time is exceeded, the server may delete all face image libraries corresponding to the experience time. Such as: the server can delete all the face image libraries corresponding to 2016, 10 and 10 days at 2016, 10, 11 and zero hours.
It should be noted that the service implementation scheme provided by the application can be applied not only to an electronic payment scenario, but also to an intelligent medicine taking scenario, an intelligent ticket taking scenario, and the like. Using the scene of getting it filled as an example, the patient can arrive self-service machine department of getting it filled and brush face, signature and get it filled after paying the cost of medicine, and whole process need not artifical the intervention, and intelligent degree is high, has saved a large amount of manpower resources.
Corresponding to the embodiment of the service implementation method, the application also provides an embodiment of a service implementation device.
The embodiment of the service implementation device can be applied to a server. The device embodiments may be implemented by software, or by hardware, or by a combination of hardware and software. Taking a software implementation as an example, as a logical device, the device is formed by reading corresponding computer program instructions in the nonvolatile memory into the memory for operation through the processor of the server where the device is located. In terms of hardware, as shown in fig. 5, a hardware structure diagram of a server where the service implementation apparatus of the present application is located is shown, except for the processor, the memory, the network interface, and the nonvolatile memory shown in fig. 5, the server where the apparatus is located in the embodiment may also include other hardware according to the actual function of the server, which is not described again.
Referring to fig. 6, the service implementation apparatus 500 can be applied in the server shown in fig. 5, and includes: a request receiving unit 501, a matching calculation unit 502, a first operation unit 503, a signature acquisition unit 504, a second operation unit 505, a third operation unit 506, a manual collation unit 507, an error return unit 508, an image maintenance unit 509, and a signature registration unit 510.
The request receiving unit 501 receives a service request sent by a service terminal, where the service request carries a face image of a service requester;
a matching calculation unit 502 for calculating the matching degree between the face image and each real face image in the face image library by a face recognition algorithm;
a first operation unit 503, configured to complete a related service based on a service account corresponding to a real face image in the face image library when a matching degree between the face image carried in the service request and the real face image in the face image library reaches a first threshold;
a signature obtaining unit 504, configured to obtain one or more real signatures corresponding to one or more real face images in the face image library when the matching degree between a face image carried in the service request and any real face image in the face image library does not reach the first threshold, but the matching degree between the face image carried in the service request and one or more real face images in the face image library reaches a second threshold, where the second threshold is smaller than the first threshold;
and a second operation unit 505, configured to, when the handwriting of the signature input by the service requester matches the acquired handwriting of the real signature, complete a related service based on the service account corresponding to the real signature.
Optionally, the signature obtaining unit 504 is further configured to, when the matching degree between the face image carried in the service request and two or more real face images in the face image library reaches the first threshold, respectively obtain two or more real signatures corresponding to the two or more real face images in the face image library;
a third operation unit 506, configured to, when the handwriting of the signature input by the service requester matches with the obtained handwriting of a certain real signature, complete a related service based on the service account corresponding to the real signature.
And the manual checking unit 507, when the handwriting of the signature input by the service requester is not matched with the obtained handwriting of any real signature, returns the one or more real signatures to the service terminal so as to perform manual checking, and completes related services according to a manual checking result.
And an error returning unit 508, configured to return an error prompt to the service terminal when the matching degree between the face image carried in the service request and any real face image in the face image library does not reach the second threshold.
Optionally, the face image library corresponds to a service time and a service object;
the image maintenance unit 509 receives a service subscription application sent by a service requester, where the service subscription application includes: business time and business object; and adding the real face image of the service requester into a face image library corresponding to the service time and the service object according to the service time and the service object in the service reservation application.
Optionally, the image maintenance unit 509 deletes the real face image corresponding to the service account in the face image library after completing the related service based on the real face image or the service account corresponding to the real signature.
Optionally, the image maintenance unit 509 deletes the face image library corresponding to the service time when the service time corresponding to the face image library is exceeded.
A signature registration unit 510 for receiving and storing the real signature registered by the user;
the authentic signature has passed the complexity check.
Optionally, the service request is a payment request.
The implementation process of the functions and actions of each unit in the above device is specifically described in the implementation process of the corresponding step in the above method, and is not described herein again.
For the device embodiments, since they substantially correspond to the method embodiments, reference may be made to the partial description of the method embodiments for relevant points. The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of the application. One of ordinary skill in the art can understand and implement it without inventive effort.
The above description is only exemplary of the present application and should not be taken as limiting the present application, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present application should be included in the scope of protection of the present application.
Claims (16)
1. A service implementation method is applied to a server, and is characterized in that the method comprises the following steps:
receiving a service request sent by a service terminal, wherein the service request carries a face image of a service requester;
calculating the matching degree of the face image and each real face image in a face image library through a face recognition algorithm;
when the matching degree of the face image carried in the service request and a certain real face image in the face image library reaches a first threshold value, completing related services based on a service account corresponding to the real face image in the face image library;
when the matching degree between the face image carried in the service request and any real face image in the face image library does not reach the first threshold value, but the matching degree between the face image carried in the service request and one or more real face images in the face image library reaches a second threshold value, acquiring one or more real signatures corresponding to the one or more real face images in the face image library, wherein the second threshold value is smaller than the first threshold value;
when the handwriting of the signature input by the service requester is matched with the acquired handwriting of one of the real signatures, the related service is completed based on the service account corresponding to the real signature;
the face image library corresponds to service time and a service object;
the method further comprises the following steps:
receiving a service reservation application sent by a service requester, wherein the service reservation application comprises: business time and business object;
and adding the real face image of the service requester into a face image library corresponding to the service time and the service object according to the service time and the service object in the service reservation application.
2. The method of claim 1, further comprising:
when the matching degree between the face image carried in the service request and two or more real face images in the face image library reaches the first threshold value, respectively acquiring two or more real signatures corresponding to the two or more real face images in the face image library;
and when the handwriting of the signature input by the service requester is matched with the acquired handwriting of a certain real signature, finishing the related service based on the service account corresponding to the real signature.
3. The method of claim 1, further comprising:
when the handwriting of the signature input by the service requester is not matched with the handwriting of any one obtained real signature, returning one or more real signatures to the service terminal so as to carry out manual verification;
and finishing related services according to the manual checking result.
4. The method of claim 1, further comprising:
and when the matching degree of the face image carried in the service request and any real face image in the face image library does not reach the second threshold value, returning an error prompt to the service terminal.
5. The method of claim 1, further comprising:
and after the related service is completed based on the service account corresponding to the real face image or the real signature, deleting the real face image corresponding to the service account in the face image library.
6. The method of claim 1, further comprising:
and deleting the face image library corresponding to the service time when the service time corresponding to the face image library is exceeded.
7. The method of claim 1, further comprising:
receiving and storing a real signature registered by a user;
the authentic signature has passed the complexity check.
8. The method of claim 1,
the service request is a payment request.
9. A service implementation apparatus applied to a server, the apparatus comprising:
the request receiving unit is used for receiving a service request sent by a service terminal, wherein the service request carries a face image of a service requester;
the matching calculation unit is used for calculating the matching degree of the face image and each real face image in the face image library through a face recognition algorithm;
the first operation unit is used for completing related services based on a service account corresponding to a real face image in the face image library when the matching degree of the face image carried in the service request and the real face image in the face image library reaches a first threshold value;
a signature obtaining unit, configured to obtain one or more real signatures corresponding to one or more real face images in the face image library when the matching degree between a face image carried in the service request and any real face image in the face image library does not reach the first threshold, but the matching degree between the face image carried in the service request and one or more real face images in the face image library reaches a second threshold, where the second threshold is smaller than the first threshold;
the second operation unit is used for completing related services based on the service account corresponding to the real signature when the handwriting of the signature input by the service requester is matched with the acquired handwriting of the real signature;
the face image library corresponds to service time and a service object;
the device further comprises:
the image maintenance unit receives a service reservation application sent by a service requester, wherein the service reservation application comprises: business time and business object; and adding the real face image of the service requester into a face image library corresponding to the service time and the service object according to the service time and the service object in the service reservation application.
10. The apparatus of claim 9,
the signature acquiring unit is further configured to acquire two or more real signatures corresponding to two or more real face images in the face image library respectively when the matching degrees between the face image carried in the service request and the two or more real face images in the face image library reach the first threshold;
the device further comprises:
and the third operation unit is used for finishing related services based on the service account corresponding to a certain real signature when the signature handwriting input by the service requester is matched with the acquired handwriting of the real signature.
11. The apparatus of claim 9, further comprising:
and the manual checking unit returns the one or more real signatures to the service terminal when the handwriting of the signature input by the service requester is not matched with the acquired handwriting of any real signature so as to carry out manual checking and complete related services according to a manual checking result.
12. The apparatus of claim 9, further comprising:
and the error returning unit is used for returning an error prompt to the service terminal when the matching degree of the face image carried in the service request and any real face image in the face image library does not reach the second threshold.
13. The apparatus of claim 9,
and the image maintenance unit deletes the real face image corresponding to the service account in the face image library after the related service is completed based on the real face image or the service account corresponding to the real signature.
14. The apparatus of claim 9,
and the image maintenance unit deletes the face image library corresponding to the service time when the service time corresponding to the face image library is exceeded.
15. The apparatus of claim 9, further comprising:
the signature registration unit is used for receiving and storing the real signature registered by the user;
the authentic signature has passed the complexity check.
16. The apparatus of claim 9,
the service request is a payment request.
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| CN108053210A (en) * | 2017-11-20 | 2018-05-18 | 胡研 | A kind of shape of face method of payment, shape of face reserving method and traction equipment |
| CN108171513A (en) * | 2017-11-20 | 2018-06-15 | 胡研 | A kind of fingerprint method of payment, fingerprint reserving method and traction equipment |
| CN108022098A (en) * | 2017-11-20 | 2018-05-11 | 胡研 | A kind of method of commerce, traction equipment and computer-readable recording medium |
| CN108171514A (en) * | 2017-11-20 | 2018-06-15 | 胡研 | A kind of finger vein method of payment refers to vein reserving method and traction equipment |
| CN108428275A (en) * | 2018-01-03 | 2018-08-21 | 平安科技（深圳）有限公司 | Row number method, server and storage medium based on recognition of face |
| CN114374560A (en) * | 2018-02-07 | 2022-04-19 | 阿里巴巴集团控股有限公司 | Data processing method, device and storage medium |
| CN110490026A (en) * | 2018-05-14 | 2019-11-22 | 阿里巴巴集团控股有限公司 | The methods, devices and systems of identifying object |
| CN109409547A (en) * | 2018-09-04 | 2019-03-01 | 中国平安人寿保险股份有限公司 | Service request processing method, device, computer equipment and storage medium |
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| CN111259698B (en) * | 2018-11-30 | 2023-10-13 | 百度在线网络技术（北京）有限公司 | Method and device for acquiring image |
| CN110276892A (en) * | 2019-06-26 | 2019-09-24 | 深圳市腾讯计算机系统有限公司 | Self-service method, apparatus, equipment and storage medium |
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