CN108920924B - Data sharing method based on face recognition - Google Patents
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Abstract
The invention discloses a data sharing method based on face recognition, wherein a first office generates a first image by face brushing for a transactor, identity authentication is carried out through the first image, if the affair transacted by the transactor needs assistance of a second office, the second office carries out identity authentication through the first image, acquires assistance data, and then sends the assistance data to the first office and transacts the affair, thereby greatly simplifying the transaction process, shortening the approval time, improving the transaction efficiency, avoiding the time of a user for running back and forth and waiting in line, and simultaneously improving the authentication accuracy to the utmost extent and ensuring the information safety by face brushing.
Description
Technical Field
The invention relates to the field of data transmission, in particular to a data sharing method based on face recognition.
Background
As is known, everyone or each enterprise inevitably needs to transact business with various institutions such as government offices, public institutions, civil and private enterprises and the like, during which the transaction of various businesses needs to authenticate the basic identity information of the person or the enterprise, such as the need to provide an identification card or a license and verify it without error before proceeding to the next transaction, different data are provided according to the specific requirements of a transaction in the process of transacting a certain transaction, for example, it is desirable to provide various types of documents related to individuals, including academic certificates, degree certificates, title certificates, honor certificates, and the like, for example, it is necessary to provide certificates related to enterprises, including tax registration certificates, account opening licenses, various quality and honor certificates, project application books, and the like, and often a user needs to run many transaction institutions to complete a certain transaction, which brings many bad experiences to the user.
Moreover, after a certain event a is not easy to be done, when transaction B is done, all the data provided during transaction a may need to be provided repeatedly, and additional other data may be added.
Similarly, when transaction C is processed, all the data provided when transaction a and transaction B are processed may need to be provided, and other data may be added additionally.
This leads to the user having to run to the office many times when handling a certain event, running to multiple offices (for example, making other certificates across departments, making a notarization, etc.), repeatedly submitting historical data, labor, low work efficiency, poor user experience, and easy friction.
In this situation, how to simplify the transaction procedure, shorten the approval time, and reduce the back-and-forth and queue-waiting pains of users is also a working pain point of various government departments, public institutions and civil enterprises.
Disclosure of Invention
The embodiment of the invention aims to provide a data sharing method based on face recognition, and aims to solve the problems of complex work handling procedures, long approval time, and running back and forth and queuing of users in the prior art.
The embodiment of the invention is realized in such a way that a data sharing method based on face recognition comprises the following steps:
a first office mechanism brushes faces of office staff to generate a first image, and identity authentication is carried out through the first image;
judging whether the affairs transacted by the transacting personnel need assistance of a second transaction mechanism;
if so, the second office mechanism performs identity authentication through the first image and acquires assistance data;
transmitting the assistance data to the first office;
transacting the transaction.
Preferably, the step of generating a first image by the first office brushing face for the clerk and authenticating identity through the first image includes:
a first office generates a first image by brushing faces of office staff;
extracting a characteristic value of the first image;
judging whether the characteristic values have a matched optimal neural network;
if so, generating a second output value through the optimal neural network, and acquiring a first output value corresponding to the optimal neural network;
judging whether the first output value is the same as the second output value;
and if so, passing the identity authentication.
Preferably, the step of "judging whether the affairs transacted by the clerk need the assistance of a second office" further comprises the following steps:
if not, the step of transacting is entered.
Preferably, the step of "determining whether there is a matching optimal neural network for the feature value" further includes the steps of:
if not, then the first step is executed,
photographing the head portrait on the identity card of the office staff to generate a second image;
acquiring a characteristic value of the second image;
creating a neural network according to the characteristic values;
and acquiring an optimal neural network and a first output value of the optimal genetic factor of the neural network.
Preferably, the first office or the second office refers to an office that provides services to users and transacts various kinds of affairs.
Preferably, the first image is generated by the first office mechanism taking a picture of the face of the office staff through a terminal device with a camera function;
the second image is an image of a certificate photo when the personnel transact the identity card in the third-party database, or an image generated by photographing the head portrait on the identity card of the personnel transact through the terminal equipment with the camera shooting function.
Preferably, the feature value refers to a distinguishing feature that the first image or the second image is distinguished from other face images.
Preferably, the first output value or the second output value is a binary value.
Preferably, the step of authenticating the identity of the second office through the first image and acquiring the assistance data by the second office includes:
the first office sends the first image to the second office;
extracting a characteristic value in the first image according to the authentication mode of the second office;
judging whether the characteristic value has a matched optimal neural network in a database of the second office or not;
if so, generating a third output value for the first image through the optimal neural network, and simultaneously acquiring a first output value corresponding to the matched optimal neural network in a database of the second office;
judging whether the third output value is the same as a first output value corresponding to the optimal neural network matched in the database of the second office or not;
if so, assistance data is obtained and the process proceeds to the step "transmit the assistance data to the first office".
Preferably, the step of "determining whether the third output value is the same as the first output value corresponding to the optimal neural network matched in the database of the second office" further includes the steps of:
and if not, acquiring a head portrait on the identity card of the office staff and generating an optimal neural network and a first output value corresponding to the head portrait.
The invention has the beneficial effects that:
the first office mechanism generates a first image by brushing the face of a transactor, identity authentication is carried out through the first image, if the transaction transacted by the transactor needs assistance of a second office mechanism, the second office mechanism carries out identity authentication through the first image, acquires assistance data, and then sends the assistance data to the first office mechanism and transacts the transaction, so that the transaction flow is greatly simplified, the approval time is shortened, the transaction efficiency is improved, the time of a user for running back and forth and waiting in line is avoided, and meanwhile, the accuracy of authentication can be improved to the maximum extent by brushing the face, and the safety of information is ensured; the first image is preferably a face image generated by shooting the face of a clerk by using a terminal device with a shooting function on site in a first office organization, and the second image is preferably a head portrait on an identity card, so that the first image and the second image are compared, the problem of judging whether the holder is the identity card by naked eyes subjectively is omitted, and the judgment accuracy is further improved; the first office organization and the second office organization adopt the same neural network optimization and identification method to generate the first output value, the second output value, the third output value and the optimal neural network, so that the identification efficiency, the office efficiency and the identification accuracy can be further improved; after the transaction is finished, all data required by the transaction are matched and filed as assistance data, so that mutual cooperation and data sharing among multiple mechanisms are facilitated, and a big data sharing information system is built and perfected; the invention also carries out identity authentication by utilizing the neural network technology, thereby further improving the accuracy of authentication and improving the safety of data; the invention is convenient for people, improves the quality and efficiency, improves the convenient accessibility of the office service, really realizes that the business can be transacted by running once at most, and can be effectively popularized and used in various office institutions.
Drawings
FIG. 1 is a flow chart of a first embodiment of a data sharing method based on face recognition according to the present invention;
fig. 2 is a flowchart of a data sharing method based on face recognition according to a second embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and examples, and for convenience of description, only parts related to the examples of the present invention are shown. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example one
Fig. 1 is a flowchart illustrating a data sharing method based on face recognition according to a first embodiment of the present invention, where the method includes the steps of:
s101, a first office mechanism generates a first image by brushing faces of office workers, and identity authentication is carried out through the first image;
the first office organization comprises all office organizations which provide service for users and handle various affairs, such as government departments, public institutions, civil and camp enterprises, and the like, for example, all office organizations which handle business externally, such as business bureaus, tax bureaus, government office centers, patent bureaus, hospitals, schools, various civil and camp enterprises, and the like;
the face brushing finger is used for photographing the face or the head portrait of the person;
the first image refers to a face image of the office staff and comprises an image generated by a first office mechanism through photographing the face of the office staff by terminal equipment with a camera shooting function; the first image also comprises an image generated by photographing a head portrait on an identity card of a clerk through terminal equipment with a camera shooting function; the method also comprises the steps of calling an image of a certificate photo when the clerk transacts the identity card in a third-party database; in this embodiment, the first image is preferably an image generated by a first office mechanism taking a picture of the face of a clerk through a terminal device with a camera function;
the first image has a distinguishing characteristic for identifying face images of other office workers, the distinguishing characteristic is a characteristic value, and face identification can be carried out through the characteristic value;
the face image of the office staff can be a face image generated by the office staff photographing on site in the first office, can also be a face image generated by the first office taking photos of the head portrait on the identity card of the office staff in early stage, and can also be a face image generated by the first office taking photos of the head portrait on the identity card of the office staff on site;
the office staff is an operator for transacting affairs on behalf of the user and can also be an operator for transacting affairs on behalf of enterprises;
s102, judging whether the affairs transacted by the clerk need assistance of a second transaction mechanism, if so, entering a step S103, and if not, entering a step S105;
the second office is a third-party office which may be involved in the affairs handled by the office staff, and the third-party office may be a government department, a public institution, a civil-business enterprise and the like;
the assistance means that the affairs handled by the clerk need a second office to confirm identity cards, open certificates, provide data required by the clerk and stored in a database of the second office, and the like;
s103, the second office mechanism performs identity authentication through the first image and acquires assistance data;
the assistance data comprises data in a second office database corresponding to the first image, and also comprises a certification file and the like required to be opened after the first image is authenticated;
generally, since the second office is required to assist, the second office has a certain pre-stored data required by the office, and the data and the office can be associated, queried and indexed by identification card, business license, name or name;
in the invention, under the general condition, no matter the first office or the second office, the neural network optimization of the identity card head portrait of the office personnel by a neural network method is preserved in advance, and a corresponding optimal neural network and a first output value are generated;
if the first office or the second office does not store the optimal neural network or the first output value corresponding to the office worker, it is indicated that the office worker does not transact at the first office or the second office, that is, the office worker does not have the transaction;
s104, transmitting the assistance data to the first office;
the transmission comprises the step of storing the assistance data to a cloud storage center for sharing; the assistance data open interface is used for the first office organization to obtain; further comprising sending the assistance data directly to the first office through prior art techniques;
for example, the office staff needs to go to a certain government department to handle the work entering procedures of the office staff, the student status data and the archive data of the office staff are stored in the school, at this time, the first office organization can send the first image to the school, the school authenticates and determines the first image, and then the student status data and the archive data of the office staff are directly sent to the first office organization, so that the situation that the office staff trembles and runs to the school in a long distance is avoided, the student status data and the archive data can be taken only through coordination of several departments, and then the student status data and the archive data are trembled and returned to the work entering procedures in a long distance is avoided, the work handling process is simplified to the maximum extent, the examination and approval time is shortened, and the work handling efficiency is improved; meanwhile, by brushing the face, the accuracy of authentication can be improved to the maximum extent, and the safety of information is ensured;
s105, transacting the affairs;
the first office mechanism can transact corresponding affairs for the transactants after acquiring the assistance data, all data required by transacting the affairs are filed after the affairs are transacted, index matching is carried out on all the data and the first output value to serve as the assistance data, the assistance data can be directly sent to other mechanisms when other mechanisms need assistance, mutual cooperation and data sharing among the mechanisms are facilitated, and therefore a big data sharing information system is built and perfected.
Example two
Fig. 2 is a flowchart illustrating a second embodiment of a data sharing method based on face recognition according to the present invention, where the method includes the steps of:
s201, a first office generates a first image by brushing faces of office workers;
s202, extracting a characteristic value of the first image;
the characteristic value refers to a distinguishing characteristic that the first image is distinguished from other images, and the characteristic value comprises a characteristic value in a face image which is subjected to face recognition by using a neural network;
s203, judging whether the characteristic values have the matched optimal neural network, if so, entering a step S204, and if not, entering a step S211;
the optimal neural network refers to the process that when a neural network is used for face recognition, a user face needs to be photographed in advance to generate an image, then a characteristic value of the image is extracted, the neural network is generated through the characteristic value, learning and optimization are carried out on the neural network through weighting and a threshold value, so that an optimal neural network corresponding to an optimal genetic factor is determined and stored, a first output value corresponding to the optimal neural network is output, the first output value is a value of the first image different from other images, the first output value can be a numerical value of any binary system, decimal system and the like, the binary value is optimized, and optimization and recognition of the neural network are improved;
s204, generating a second output value through the optimal neural network, and acquiring a first output value corresponding to the optimal neural network;
s205, judging whether the first output value is the same as the second output value, if so, entering the step S206, and if not, entering the step S210;
the identity may be the same, or may be approximately the same after weighting;
whether the first output value is the same as the second output value or not indicates that the identity authentication of the transactants is passed, and the transaction can be continued;
s206, judging whether the affairs transacted by the clerk need assistance of a second transaction mechanism, if so, entering step S207, and if not, entering step S210;
s207, the second office organization performs identity authentication through the first image and acquires assistance data;
the first office sends the first image to the second office;
after the second office mechanism acquires the first image, extracting a characteristic value in the first image according to an authentication mode of the second office mechanism, and judging whether the characteristic value has a matched optimal neural network in a database of the second office mechanism;
each office organization has a mechanism for authenticating the identity of the user, so that the first image only needs to be sent to the second office organization, and the second office organization authenticates the identity of the user according to the authentication of the user, and strictly respects the office process, the office criteria and the office standards of the second office organization;
if so, generating a third output value for the first image through the optimal neural network, and simultaneously acquiring a first output value corresponding to the matched optimal neural network in a database of the second office; if not, acquiring a head portrait on the identity card according to the identity card information of the office staff and generating an optimal neural network and a first output value corresponding to the head portrait;
judging whether the third output value is the same as a first output value corresponding to the optimal neural network matched in the database of the second office or not, and if so, acquiring assistance data; if not, refusing to obtain the assistance data;
s208, transmitting the assistance data to the first office;
s209, the first transaction mechanism receives the assistance data and transacts the transaction;
s210, refusing to transact the affair.
After receiving the assistance notification, the second office mechanism does not directly query the database of the mechanism through the second output value generated by the first office mechanism, but regenerates the third output value according to the identity authentication standard of the mechanism, and then queries whether the matched first output value exists in the database of the mechanism, so that the situation that a certain office mechanism forges and counterfeits the first output value to the maximum extent, information leakage of office staff or enterprises is caused, and loss is caused is avoided; only when the first output value and the third output value stored in the second office database are the same, the assistance data is sent, so that the data security is improved, and the user privacy is protected; otherwise, the fact that the first output value of the clerk is not matched with the first output value of the second office mechanism is indicated, a difference occurs, or the clerk and the second office mechanism are determined not to be the same person, and the fact that the assistance data are sent to the first office mechanism is refused;
after the first office organization receives the notification of refusing to assist, the first office organization needs to confirm the office staff again, so that the privacy of the office staff or the enterprise is protected to the maximum extent, and the safety of data is ensured;
s211, photographing the head portrait on the identity card of the office staff to generate a second image;
the head portrait on the identity card can be a 1-inch photo or a 2-inch photo provided by a handling organization when the handling organization handles the identity card by calling the handling organization (for example, the identity card photo taken by the handling organization when handling the identity card can be acquired by being connected with a photo studio, the identity card photo taken by the handling organization when handling the identity card can be acquired by being connected with a public security bureau system), or an image generated by photographing the head portrait on the identity card by the handling organization through terminal equipment;
the second image is preferably generated by calling an image of a certificate photo when the clerk transacts the identity card in a third-party database or by photographing a head portrait on the identity card of the clerk through terminal equipment with a camera shooting function;
s212, acquiring a characteristic value of the second image;
the characteristic value refers to a distinguishing characteristic that the second image is distinguished from other images, and the characteristic value comprises a characteristic value in a face image which is subjected to face recognition by using a neural network;
s213, creating a neural network according to the characteristic value;
the neural network is an operation model and is formed by mutually connecting a large number of nodes (or called neurons), each node represents a specific output function, the connection between every two nodes represents a weighted value for a signal passing through the connection, and the output value of the neural network is different according to the connection mode, the weighted value and the excitation function of the neural network; the neural network itself is usually an approximation to a certain algorithm or function in the nature, so as to obtain an optimal neural network and a first output value corresponding to the optimal genetic factor;
s214, obtaining the optimal neural network and the first output value of the optimal genetic factor of the neural network.
In this embodiment, it is preferable that the second image is a head portrait on an identity card, and the first image is a face image generated by shooting a face of a clerk by using a terminal device with a shooting function in the field of the first office organization, so that the first image and the face image are compared, the problem of subjective judgment of whether the clerk is the identity of the clerk by naked eyes is solved, and the judgment accuracy is improved.
In this embodiment, the first office organization and the second office organization preferably use the same neural network optimization and recognition method to generate the first output value, the second output value, the third output value and the optimal neural network, so that the recognition efficiency, the transaction efficiency and the recognition accuracy can be further improved.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (5)
1. A data sharing method based on face recognition is characterized by comprising the following steps:
a first office mechanism brushes faces of office staff to generate a first image, and identity authentication is carried out through the first image;
judging whether the affairs transacted by the transacting personnel need assistance of a second transaction mechanism;
if so, the second office mechanism performs identity authentication through the first image and acquires assistance data;
transmitting the assistance data to the first office;
transacting the transaction;
the step that a first office generates a first image by brushing faces of office staff and performs identity authentication through the first image is specifically as follows:
a first office generates a first image by brushing faces of office staff;
extracting a characteristic value of the first image;
judging whether the characteristic values have a matched optimal neural network;
if so, generating a second output value through the optimal neural network, and acquiring a first output value corresponding to the optimal neural network;
judging whether the first output value is the same as the second output value;
if yes, passing the identity authentication;
the step of judging whether the affairs transacted by the clerk need the assistance of a second transaction institution further comprises the following steps:
if not, entering the step of transacting the transaction;
the step of judging whether the characteristic value has the matched optimal neural network further comprises the following steps:
if not, then the first step is executed,
photographing the head portrait on the identity card of the office staff to generate a second image;
acquiring a characteristic value of the second image;
creating a neural network according to the characteristic values;
acquiring an optimal neural network and a first output value of the optimal genetic factor of the neural network;
the first office organization or the second office organization is an office organization which provides service for users and handles various affairs;
the first image is generated by the first office mechanism through face photographing of office staff by terminal equipment with a camera shooting function;
the second image is an image of a certificate photo when the personnel transact the identity card in the third-party database, or an image generated by photographing the head portrait on the identity card of the personnel transact through the terminal equipment with the camera shooting function.
2. The method of claim 1, wherein the feature value refers to a distinguishing feature that the first image or the second image is distinguished from other face images.
3. The method of claim 1, wherein the first output value or the second output value is a binary numerical value.
4. The data sharing method based on face recognition according to claim 1, wherein the step "the second office performs identity authentication through the first image and acquires assistance data" specifically includes:
the first office sends the first image to the second office;
extracting a characteristic value in the first image according to the authentication mode of the second office;
judging whether the characteristic value has a matched optimal neural network in a database of the second office or not;
if so, generating a third output value for the first image through the optimal neural network, and simultaneously acquiring a first output value corresponding to the matched optimal neural network in a database of the second office;
judging whether the third output value is the same as a first output value corresponding to the optimal neural network matched in the database of the second office or not;
if so, assistance data is obtained and the process proceeds to the step "transmit the assistance data to the first office".
5. The method for sharing data based on face recognition according to claim 4, wherein the step of "determining whether the third output value is the same as the first output value corresponding to the optimal neural network matched in the database of the second office" further comprises the steps of:
and if not, acquiring a head portrait on the identity card of the office staff and generating an optimal neural network and a first output value corresponding to the head portrait.
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