CN115271766B - Mortgage surface sign on-line processing method and system based on remote video - Google Patents
Mortgage surface sign on-line processing method and system based on remote video Download PDFInfo
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Abstract
The invention relates to a remote video-based mortgage surface sign on-line processing method and system, in particular to the technical field of remote surface sign, and the method comprises a login module, a remote video-based mortgage surface sign on-line processing module and a remote video-based mortgage surface sign on-line processing module, wherein the login module is connected with the login module and used for logging in a user; the verification module is used for verifying the identity of the logged-in ordinary user; the acquisition module is connected with the verification module and used for acquiring real-time video images of the ordinary users passing the identity verification; the analysis module is connected with the acquisition module and is used for carrying out data analysis on the acquired real-time video image; the evaluation module is connected with the analysis module and used for evaluating the reliability of the label according to the data analysis result; and the surface label module is connected with the evaluation module and used for prompting a common user to carry out signature when the reliability of the surface label meets the requirement. The invention effectively improves the safety and reliability of the remote video surface label.
Description
Technical Field
The invention relates to the technical field of remote face-to-face signs, in particular to a mortgage face-to-face sign on-line processing method and system based on remote videos.
Background
In a social industry represented by financial industries such as banking, securities, insurance and the like, when providing services to the public, the real identity of a party needs to be checked, namely real-name system verification work is done. With the vigorous development of the internet, in order to greatly save the cost of manpower and network points and also reduce the running suffering of business handling parties, a remote face-to-face system appears.
Chinese patent application publication no: CN106203024A discloses a remote video surface sign method and system, the method includes: sending a face action instruction to a user terminal; receiving video information of a user execution instruction, and obtaining a human face image frame; when judging that the image frame which meets the human face quality standard exists, storing the image frame; obtaining an image frame matched with the instruction, calculating whether the matched proportion reaches a first preset proportion, and if so, judging that the instruction is successfully executed; monitoring whether the number of the sent instructions reaches a preset number, and if not, sending a face action instruction to the user terminal; and if so, judging that the instruction detection is passed, and sending face signing success information to the user terminal when judging that the image frames meeting the face quality standard are stored. Therefore, the environmental state of the user during surface signing is not considered in the scheme, and the safety and the reliability of the surface signing are influenced.
Disclosure of Invention
Therefore, the invention provides a remote video-based mortgage surface signing on-line processing method and system, which are used for solving the problems of low safety and low reliability of remote surface signing caused by the fact that the user environment state is not accurately analyzed in the prior art.
To achieve the above object, in one aspect, the present invention provides a remote video-based mortgage face signing online processing system, including:
the login module is used for logging in a user;
the verification module is connected with the login module and used for verifying the identity of the logged-in ordinary user, a comparison unit is arranged in the verification module and connected with the identification unit, the comparison unit is used for matching the identity card number input by the ordinary user with the stored identity card number so as to primarily verify the identity information of the ordinary user, and the identification unit is used for performing face recognition on the ordinary user who passes the primary verification so as to secondarily verify the identity information of the ordinary user;
the acquisition module is connected with the verification module and used for acquiring real-time video images of the ordinary users passing the identity verification;
the analysis module is connected with the acquisition module and is used for carrying out data analysis on the acquired real-time video images, and the analysis module is also used for carrying out data analysis on the environmental state of a common user so as to determine the number of personnel and the number of dangerous goods in the video images;
the evaluation module is connected with the analysis module and used for evaluating the reliability of the tag according to the data analysis result, a calculation unit is arranged in the evaluation module and connected with a judgment unit, the calculation unit is used for calculating the safety coefficient of the environment in real time according to the number of people in the video image, the judgment unit is used for judging the environment state of a common user according to the safety coefficient, the evaluation module is further used for adjusting the safety coefficient according to the number of dangerous goods in the video image and correcting the adjusted safety coefficient according to the video interruption frequency, and the evaluation module is further used for evaluating the reliability of the tag according to the duration of the environment safety state in the video image;
and the surface label module is connected with the evaluation module and used for prompting a common user to carry out signature when the reliability of the surface label meets the requirement.
Further, when the comparison unit performs primary verification on the identity information of the ordinary user, the comparison unit acquires the identity card number input by the ordinary user and matches the identity card number with the stored identity card number, if the matching is successful, the comparison unit judges that the primary verification is passed, the identification unit performs secondary verification on the identity information of the ordinary user which is passed by the primary verification, and if the matching is failed, the comparison unit judges that the primary verification is not passed and needs to input the identity card number again;
the identification unit acquires a video image of a common user and performs face identification when performing secondary verification, takes facial features acquired by the face identification as matching features, acquires facial features in a corresponding identity card as standard features according to an identity card number input by the user, compares the matching features with the standard features, determines that the secondary verification is passed if the matching features are the same as the standard features, and determines that the secondary verification is not passed if the matching features are different from the standard features, and needs to perform face identification again.
Further, when the analysis module analyzes the data of the environment state, the contour curve shape of each object in the video image is obtained, and is compared with the shape of the preset human body part, and the human body area is judged according to the comparison result, wherein,
when the contour curve shape of the object is the same as the preset human body part shape, the analysis module acquires the area S of the shape and compares the area S with the preset human body part area S0, if S is less than or equal to S0, the analysis module judges that the shape is the human body part shape, if S is greater than S0, the analysis module judges that the shape is not the human body part shape, and the analysis module acquires the number of the unconnected human body part shapes in the video image as the number of people;
and when the shape of the contour curve of the object is different from the shape of the preset human body part, the analysis module judges the shape of the non-human body part in the shape.
Further, when the analysis module obtains the number of the dangerous goods, the contour curve shape of each object in the video image is compared with the preset dangerous goods shape, and the dangerous goods area judgment is carried out according to the comparison result, wherein,
when the contour curve shape of the object is the same as the preset dangerous goods shape, the analysis module acquires an area Sa of the shape and compares the area Sa with the preset dangerous goods area Sa0, if Sa is less than or equal to Sa0, the analysis module judges that the shape is a dangerous goods shape, if S is greater than S0, the analysis module judges that the shape is a non-dangerous goods shape, and the analysis module acquires the number of dangerous goods shapes connected with the shape of the human body part in the video image as the number of dangerous goods;
and when the shape of the contour curve of the object is different from the preset shape of the dangerous goods, the analysis module judges that the shape is not the shape of the dangerous goods.
Further, when the calculating unit calculates the safety factor a of the environment in the video image in real time, setting a = H/H0, where H is the number of people in the video image and H0 is the number of preset standard people, the judging unit compares the calculated safety factor a with the preset safety factor A0 and judges the environment state of the general user according to the comparison result, wherein,
when A is less than or equal to A0, the judging unit judges that the environment state is a safe state;
when A > A0, the judgment unit judges that the environmental state is a risk state.
Further, when the evaluation module adjusts the calculated safety factor, the evaluation module compares the number M of the dangerous goods in the acquired video image with the preset number M0 of the dangerous goods, and adjusts the calculated safety factor according to the comparison result, wherein,
when M < M0, the evaluation module does not adjust;
when M > M0, the evaluation module adjusts the safety factor to a ', setting a' = a + a × (M-M0)/M0.
Further, the evaluation module acquires the video interruption frequency F of the video image when correcting the adjusted safety factor, compares the video interruption frequency F with the preset interruption frequency F0, and corrects the adjusted safety factor according to the comparison result, wherein,
when F is less than or equal to F0, the evaluation module does not carry out correction;
when F > F0, the evaluation module corrects the safety factor to a ", setting a" = a '+ a' × (F-F0)/F.
Further, when evaluating the reliability of the tag, the evaluation module obtains the duration T of the security state of the environmental state in the video image, compares the duration T with a preset standard duration T0, and evaluates the reliability of the tag according to the comparison result, wherein,
when T is less than T0, the evaluation module judges that the reliability of the face label does not meet the requirement;
and when T is larger than or equal to T0, the evaluation module judges that the reliability of the surface label meets the requirement, and the surface label module carries out signature prompt.
Furthermore, the users comprise working personnel and common users, the working personnel log in through the working codes, and the common users log in through the identity card numbers.
In another aspect, the present invention further provides a remote video-based mortgage surface signing on-line processing method, including,
s1, carrying out identity authentication on a logged-in common user;
s2, acquiring a real-time video image of the ordinary user passing the identity authentication;
s3, performing data analysis on the acquired real-time video image to determine the number of personnel and dangerous goods in the video image;
s4, evaluating the reliability of the face badge according to the data analysis result, calculating the safety coefficient of the environment in real time according to the number of personnel in the video image during evaluation, judging the environment state of a common user according to the safety coefficient, adjusting the safety coefficient according to the number of dangerous goods in the video image during calculation of the safety coefficient, correcting the adjusted safety coefficient according to the video interruption frequency, and evaluating the reliability of the face badge according to the duration time of the environment safety state in the video image after judgment of the environment state is completed;
and S5, prompting a common user to sign when the reliability of the surface label meets the requirement.
Compared with the prior art, the method has the advantages that the real-time video image of the ordinary user is collected through the collection module, the collected real-time video image is analyzed through the analysis module, the video image is analyzed frame by frame in a video frame extraction mode during analysis, the environment state of the ordinary user during face signing is determined through data analysis of the video image, the accuracy of evaluation of the face signing reliability of the ordinary user is improved, the safety and the reliability of the remote video face signing are improved, after the environment state of the ordinary user is analyzed, the evaluation module calculates the safety coefficient according to the analyzed parameter information to judge the environment state, and when the safety and the duration time of the environment state meet requirements, the ordinary user is prompted to sign, and the reliability and the safety of the face signing are further guaranteed.
Especially, when the verification module performs identity authentication on a common user, firstly, the input identity card number is verified, if the verification is successful, the verification is performed in a face recognition mode, so that the login user is ensured to be the user, the safety and the reliability of the remote face-to-face sign are improved, when the primary verification is performed, the identity card number is directly matched with the stored identity card number, when the secondary verification is performed, the facial features of the login user are obtained through obtaining a video image, then the facial features in the corresponding identity card are obtained through the identity card number for comparison, so that the accuracy of a comparison result is ensured, if the secondary verification is performed, the login user is proved to be the user, and the safety and the reliability of the remote face-to-face sign are effectively improved through two times of verification.
Particularly, when the analysis module obtains the number of people in the video image, the analysis module obtains the contour curve shapes of all objects in the video image to perform comparison analysis so as to determine the number of people, after the shapes are compared, the analysis module further judges the shapes according to the shape areas so as to finally determine whether the shapes are the shapes of human body parts, and if the shape areas are within a preset value, the shapes are judged to be the shapes of the human body parts, so that the accuracy of judging the number of people in the video image is improved, and the accuracy of judging the environment state in the video image is further improved.
Particularly, when the analysis module obtains the number of dangerous goods in the video image, the analysis module obtains the contour curve shapes of all objects in the video image to perform comparison analysis so as to determine the number of dangerous goods, after the shapes are compared, the analysis module further judges the shapes according to the shape areas so as to finally determine whether the shapes of the dangerous goods are dangerous goods, and if the shape areas are within a preset value, the shapes of the dangerous goods are judged, so that the accuracy of judging the number of the dangerous goods in the video image is improved, and the accuracy of judging the environment state in the video image is further improved.
Particularly, the evaluation module judges the environment state by calculating the safety factor, so that the reliability of the facial tags can be evaluated conveniently according to the environment state, the safety factor is increased along with the increase of the number of the personnel, when the safety factor A is larger than a preset value, the environment state is judged to have risks, if the safety factor A is within the preset value, the environment state is judged to be the safety state, and the reliability and the safety of the facial tags are improved by judging the environment state.
Particularly, when the safety factor is calculated, the safety factor is adjusted by acquiring the quantity of dangerous goods in the video image, the safety factor is increased by adjusting, so that the accuracy of judging the environmental state is improved, if the quantity M of the dangerous goods is greater than a preset value, the safety factor is increased along with the increase of the quantity M of the dangerous goods, so that the accuracy of judging the environmental state is improved, meanwhile, the evaluation module corrects the adjusted safety factor according to the video interruption frequency F of the video image, and increases the safety factor by correcting, so that the accuracy of judging the environmental state is further improved, and if the video interruption frequency F is greater than the preset value, the corrected safety factor is increased along with the increase of the video interruption frequency F, so that the accuracy of judging the environmental state is further improved, and the reliability and the safety of the surface label are improved.
Drawings
Fig. 1 is a schematic structural diagram of a remote video-based mortgage face sign-on-line processing system according to an embodiment of the invention;
FIG. 2 is a structural framework diagram of the verification module of the present embodiment;
FIG. 3 is a structural framework diagram of an evaluation module according to the present embodiment;
fig. 4 is a flowchart illustrating the remote video-based mortgage surface sign-on-line processing method according to the embodiment.
Detailed Description
In order that the objects and advantages of the invention will be more clearly understood, the invention is further described below with reference to examples; it should be understood that the specific embodiments described herein are merely illustrative of the invention and do not delimit the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only for explaining the technical principles of the present invention, and do not limit the scope of the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Referring to fig. 1-3, a remote video-based mortgage face signing on-line processing system of the present embodiment includes,
the login module is used for logging in a user, the user comprises a worker and a common user, the worker logs in through a work code, and the common user logs in through an identity card number;
the verification module is connected with the login module and used for verifying the identity of the logged-in ordinary user, a comparison unit is arranged in the verification module and connected with the identification unit, the comparison unit is used for matching the identity card number input by the ordinary user with the stored identity card number so as to primarily verify the identity information of the ordinary user, and the identification unit is used for performing face recognition on the ordinary user passing primary verification so as to secondarily verify the identity information of the ordinary user;
the acquisition module is connected with the verification module and used for acquiring real-time video images of the ordinary users passing the identity verification;
the analysis module is connected with the acquisition module and used for carrying out data analysis on the acquired real-time video images, and the analysis module is also used for carrying out data analysis on the environmental state of a common user so as to determine the number of personnel and dangerous goods in the video images;
the evaluation module is connected with the analysis module and used for evaluating the reliability of the tag according to the data analysis result, a calculation unit is arranged in the evaluation module and connected with a judgment unit, the calculation unit is used for calculating the safety coefficient of the environment in real time according to the number of people in the video image, the judgment unit is used for judging the environment state of a common user according to the safety coefficient, the evaluation module is further used for adjusting the safety coefficient according to the number of dangerous goods in the video image and correcting the adjusted safety coefficient according to the video interruption frequency, and the evaluation module is further used for evaluating the reliability of the tag according to the duration of the environment safety state in the video image;
and the surface label module is connected with the evaluation module and used for prompting a common user to carry out signature when the reliability of the surface label meets the requirement.
Specifically, the system of the embodiment is applied to a terminal, when a worker and a common user perform video surface signing, the worker sends out a surface signing application, the common user receives the surface signing application and completes signing, in the embodiment, the worker and the common user log in different modes when logging in, and log in and verify in different modes, so that the reliability and the safety of the surface signing are ensured, meanwhile, in the embodiment, a real-time video image of the common user is collected through a collection module, the collected real-time video image is analyzed through an analysis module, the video image is analyzed frame by frame in a mode of extracting a video frame during analysis, the environmental state of the common user when signing is determined through data analysis on the video image, so that the accuracy of evaluating the reliability of the surface signing of the common user is improved, the safety and the reliability of a remote video surface signing are improved, after the environmental state of the common user is analyzed, the evaluation module further calculates a safety factor according to calculate the safety coefficient according to judge the environmental state, and prompts the common user to sign the reliability and the safety of the surface signing when the environmental state safety and the duration meet requirements. It can be understood that, in this embodiment, the login verification manner of the worker is not limited, and a person skilled in the art can freely set the login verification manner, for example, when the input work code is successfully matched, the worker can be verified in a manner of password or face recognition or fingerprint recognition, and the login verification requirement of the worker is only required to be met; in this embodiment, the dangerous goods are not limited, and may be various kinds of dangerous goods, and those skilled in the art may freely set the dangerous goods, and if the video image includes different kinds of dangerous goods, the number of the dangerous goods is directly superimposed.
Specifically, when the comparison unit performs primary verification on the identity information of the ordinary user, the identification unit acquires the identity card number input by the ordinary user and matches the identity card number with the stored identity card number, if the matching is successful, the comparison unit judges that the primary verification is passed, the identification unit performs secondary verification on the identity information of the ordinary user passing the primary verification, and if the matching is failed, the comparison unit judges that the primary verification is not passed and needs to input the identity card number again;
the identification unit acquires a video image of a common user and performs face identification when performing secondary verification, takes facial features acquired by the face identification as matching features, acquires facial features in a corresponding identity card as standard features according to an identity card number input by the user, compares the matching features with the standard features, determines that the secondary verification is passed if the matching features are the same as the standard features, and determines that the secondary verification is not passed if the matching features are different from the standard features, and needs to perform face identification again.
Specifically, in this embodiment, when the verification module performs identity authentication on a general user, the verification module firstly verifies an input identity card number, and if the verification is successful, the verification is performed in a face recognition manner to ensure that a login user is the identity of the login user, so as to improve the security and reliability of a remote face-to-face tag. It can be understood that, in this embodiment, the facial features are not specifically limited, and those skilled in the art can freely set the facial features, for example, the obtained facial features are set as color features, contour features, texture features, structural features, and the like of a human face, and other features can be set for face recognition, so that only the requirements of face recognition need to be met.
Specifically, when the analysis module performs data analysis on the environmental state, the analysis module acquires the contour curve shape of each object in the video image, compares the contour curve shape with the shape of a preset human body part, and performs human body region judgment according to the comparison result, wherein,
when the contour curve shape of the object is the same as the preset human body part shape, the analysis module acquires the area S of the shape and compares the area S with the preset human body part area S0, if S is less than or equal to S0, the analysis module judges that the shape is the human body part shape, if S is greater than S0, the analysis module judges that the shape is not the human body part shape, and the analysis module acquires the number of unconnected human body part shapes in the video image as the number of people;
when the shape of the contour curve of the object is different from the shape of the preset human body part, the analysis module judges the shape of the non-human body part in the shape.
Specifically, in this embodiment, when the analysis module obtains the number of people in the video image, the number of people is determined by obtaining the contour curve shapes of the objects in the video image and performing comparison analysis, after the shape comparison passes, the analysis module further determines the shape according to the shape area to finally determine whether the shape is the shape of the body part, and if the shape area is within a preset value, the shape is determined to be the shape of the body part, so that the accuracy of determining the number of people in the video image is improved, and the accuracy of determining the environment state in the video image is further improved. It can be understood that, in this embodiment, the shape of the preset human body part is not specifically limited, and when the human body is set by a person skilled in the art, the whole shape and a part of the shape of the human body can be set to perform comprehensive comparison and determination, so as to improve the accuracy of determining the number of the people.
Specifically, when the analysis module obtains the number of dangerous goods, the analysis module compares the contour curve shape of each object in the video image with a preset dangerous goods shape, and judges the dangerous goods area according to the comparison result, wherein,
when the contour curve shape of the object is the same as the preset dangerous goods shape, the analysis module acquires an area Sa of the shape and compares the area Sa with the preset dangerous goods area Sa0, if Sa is less than or equal to Sa0, the analysis module judges that the shape is a dangerous goods shape, if S is greater than S0, the analysis module judges that the shape is a non-dangerous goods shape, and the analysis module acquires the number of dangerous goods shapes connected with the shape of the human body part in the video image as the number of dangerous goods;
and when the shape of the contour curve of the object is different from the preset shape of the dangerous goods, the analysis module judges that the shape is not the shape of the dangerous goods.
Specifically, in this embodiment, when the analysis module obtains the number of dangerous goods in the video image, the analysis module performs comparison analysis by obtaining the contour curve shapes of the objects in the video image to determine the number of dangerous goods, after the shape comparison passes, the analysis module further determines the shape according to the shape area to finally determine whether the shape is a dangerous goods shape, and if the shape area is within a preset value, the shape is determined to be a dangerous goods shape, so that the accuracy of determining the number of dangerous goods in the video image is improved, and the accuracy of determining the environment state in the video image is further improved. It can be understood that, in this embodiment, no specific limitation is made on the preset shape of the dangerous goods, and those skilled in the art can freely set the shape, for example, the shape of the dangerous goods such as the control tool is set as the preset shape of the dangerous goods, and other shapes of the dangerous goods can also be set, and only the requirement of identification and judgment on the dangerous goods needs to be satisfied.
Specifically, when the computing unit computes the safety factor a of the environment in the video image in real time, a = H/H0 is set, H is the number of people in the video image, H0 is the number of preset standard people, the judging unit compares the computed safety factor a with the preset safety factor A0, and judges the environment state of the ordinary user according to the comparison result, wherein,
when A is less than or equal to A0, the judging unit judges that the environment state is a safe state;
when A > A0, the judgment unit judges that the environmental state is a risk state.
Specifically, the evaluation module in this embodiment calculates a safety factor through the calculation unit to determine the environment state, so as to facilitate evaluation of the reliability of the face-slip according to the environment state, the safety factor increases with the increase of the number of people, when the safety factor a is greater than a preset value, it is determined that the environment state has a risk, and if the safety factor a is within the preset value, it is determined that the environment state is a safe state, and the environment state is determined to improve the reliability and the safety of the face-slip.
Specifically, when the evaluation module adjusts the calculated safety factor, the evaluation module compares the number M of the dangerous goods in the acquired video image with a preset number M0 of the dangerous goods, and adjusts the calculated safety factor according to the comparison result, wherein,
when M < M0, the evaluation module does not adjust;
when M > M0, the evaluation module adjusts the safety factor to a ', setting a' = a + a × (M-M0)/M0.
Specifically, the evaluation module acquires the video interruption frequency F of the video image when correcting the adjusted safety factor, compares the video interruption frequency F with the preset interruption frequency F0, and corrects the adjusted safety factor according to the comparison result, wherein,
when F is less than or equal to F0, the evaluation module does not perform correction;
when F > F0, the evaluation module modifies the safety factor to a ″, setting a "= a '+ a' × (F-F0)/F.
Specifically, in this embodiment, when the safety factor is calculated, the safety factor is adjusted by acquiring the number of dangerous articles in the video image, the safety factor is increased by adjustment to improve the accuracy of judgment on the environmental state, and if the number M of dangerous articles is greater than a preset value, the safety factor is increased along with the increase of the number M of dangerous articles to improve the accuracy of judgment on the environmental state. It can be understood that, in this embodiment, the video interruption frequency is not specifically limited, and a person skilled in the art can freely set the video interruption frequency, for example, when the video interruption frequency F is obtained, the video interruption frequency within a preset time is used as the video interruption frequency, such as the video interruption frequency within 30 seconds or 1 minute.
Specifically, when evaluating the reliability of the tag, the evaluation module obtains the duration T of the security status of the environmental status in the video image, compares the duration T with a preset standard duration T0, and evaluates the reliability of the tag according to the comparison result, wherein,
when T is less than T0, the evaluation module judges that the reliability of the face label does not meet the requirement;
and when the T is larger than or equal to T0, the evaluation module judges that the reliability of the surface label meets the requirement, and the surface label module carries out signature prompt.
Specifically, in the embodiment, the reliability of the remote video countersign is evaluated, so that the countersign module performs signature prompting when the reliability meets the requirement, so as to improve the reliability and the safety of the remote video countersign, if the duration T of the environmental state being the safety state is greater than a preset value, the reliability is judged to meet the requirement, otherwise, the requirement is not met, and the reliability and the safety of the remote video countersign are effectively improved through the reliability evaluation.
Please refer to fig. 4, which is a flowchart illustrating a remote video-based mortgage face sign-on-line processing method according to an embodiment of the present invention, the method includes,
s1, performing identity authentication on a logged-in common user;
s2, acquiring a real-time video image of the ordinary user passing the identity authentication;
s3, carrying out data analysis on the collected real-time video image to determine the number of personnel and dangerous goods in the video image;
s4, evaluating the reliability of the tag according to the data analysis result, calculating the safety coefficient of the environment in real time according to the number of people in the video image during evaluation, judging the environment state of a common user according to the safety coefficient, adjusting the safety coefficient according to the number of dangerous goods in the video image during calculation of the safety coefficient, correcting the adjusted safety coefficient according to the video interruption frequency, and evaluating the reliability of the tag according to the duration of the environment safety state in the video image after judgment of the environment state is completed;
and S5, prompting a common user to sign when the reliability of the surface label meets the requirement.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can be within the protection scope of the invention.
Claims (10)
1. A remote video-based mortgage surface sign-on-line processing system is characterized by comprising,
the login module is used for logging in a user;
the verification module is connected with the login module and used for verifying the identity of the logged-in ordinary user, a comparison unit is arranged in the verification module and connected with the identification unit, the comparison unit is used for matching the identity card number input by the ordinary user with the stored identity card number so as to primarily verify the identity information of the ordinary user, and the identification unit is used for performing face recognition on the ordinary user passing primary verification so as to secondarily verify the identity information of the ordinary user;
the acquisition module is connected with the verification module and used for acquiring real-time video images of the ordinary users passing the identity verification;
the analysis module is connected with the acquisition module and used for carrying out data analysis on the acquired real-time video images, and the analysis module is also used for carrying out data analysis on the environmental state of a common user so as to determine the number of personnel and dangerous goods in the video images;
the evaluation module is connected with the analysis module and used for evaluating the reliability of the tag according to the data analysis result, a calculation unit is arranged in the evaluation module and connected with a judgment unit, the calculation unit is used for calculating the safety coefficient of the environment in real time according to the number of people in the video image, the judgment unit is used for judging the environment state of a common user according to the safety coefficient, the evaluation module is further used for adjusting the safety coefficient according to the number of dangerous goods in the video image and correcting the adjusted safety coefficient according to the video interruption frequency, and the evaluation module is further used for evaluating the reliability of the tag according to the duration of the environment safety state in the video image;
and the surface signing module is connected with the evaluation module and is used for prompting a common user to sign when the reliability of the surface signing meets the requirement.
2. The system according to claim 1, wherein the comparison unit obtains the identity card number input by the general user and matches the identity card number with the stored identity card number when performing primary verification on the identity information of the general user, the comparison unit determines that the primary verification is passed if the matching is successful, the identification unit performs secondary verification on the identity information of the general user who passes the primary verification, and if the matching is failed, the comparison unit determines that the primary verification is failed and re-inputs the identity card number;
when the identification unit carries out secondary verification, the video image of a common user is obtained, face recognition is carried out, facial features obtained by face recognition are used as matching features, the identification unit obtains the facial features in the corresponding identity card according to the identity card number input by the user and uses the facial features as standard features, the matching features are compared with the standard features, if the matching features are the same as the standard features, the identification unit judges that the secondary verification is passed, and if the matching features are different from the standard features, the identification unit judges that the secondary verification is not passed and needs to carry out face recognition again.
3. The remote video-based mortgage surface sign-on-line processing system as claimed in claim 1, wherein the analysis module obtains a contour curve shape of each object in the video image, compares the contour curve shape with a preset human body part shape, and judges a human body area according to a comparison result, wherein,
when the contour curve shape of the object is the same as the preset human body part shape, the analysis module acquires the area S of the shape and compares the area S with the preset human body part area S0, if S is less than or equal to S0, the analysis module judges that the shape is the human body part shape, if S is greater than S0, the analysis module judges that the shape is not the human body part shape, and the analysis module acquires the number of the unconnected human body part shapes in the video image as the number of people;
when the shape of the contour curve of the object is different from the shape of the preset human body part, the analysis module judges the shape of the non-human body part in the shape.
4. The remote video-based mortgage surface sign-on-line processing system according to claim 3, wherein the analysis module compares a contour curve shape of each object in the video image with a preset dangerous goods shape, and judges a dangerous goods area according to the comparison result, wherein,
when the contour curve shape of the object is the same as the preset dangerous goods shape, the analysis module acquires an area Sa of the shape and compares the area Sa with the preset dangerous goods area Sa0, if Sa is less than or equal to Sa0, the analysis module judges that the shape is a dangerous goods shape, if S is greater than S0, the analysis module judges that the shape is a non-dangerous goods shape, and the analysis module acquires the number of dangerous goods shapes connected with the shape of the human body part in the video image as the number of dangerous goods;
and when the shape of the contour curve of the object is different from the preset shape of the dangerous goods, the analysis module judges that the shape is not the shape of the dangerous goods.
5. The remote video-based mortgage surface sign-on-line processing system according to claim 1, wherein the calculating unit sets a = H/H0 when calculating a safety factor a of an environment in the video image in real time, H being the number of persons in the video image, H0 being a preset standard number of persons, the judging unit compares the calculated safety factor a with the preset safety factor A0 and judges an environmental state of a general user according to a comparison result, wherein,
when A is less than or equal to A0, the judging unit judges that the environment state is a safe state;
when A > A0, the judgment unit judges that the environmental state is a risk state.
6. The remote video-based mortgage surface sign-on-line processing system according to claim 5, wherein the evaluation module compares the number M of dangerous goods in the obtained video image with a preset number M0 of dangerous goods when adjusting the calculated safety factor, and adjusts the calculated safety factor according to the comparison result,
when M < M0, the evaluation module does not adjust;
when M > M0, the evaluation module adjusts the safety factor to a ', setting a' = a + a × (M-M0)/M0.
7. The remote video-based mortgage surface signing on-line processing system of claim 6, wherein the evaluation module, when modifying the adjusted safety factor, obtains a video interruption frequency F of the video image, compares the video interruption frequency F with a preset interruption frequency F0, and modifies the adjusted safety factor according to the comparison result, wherein,
when F is less than or equal to F0, the evaluation module does not perform correction;
when F > F0, the evaluation module modifies the safety factor to a ″, setting a "= a '+ a' × (F-F0)/F.
8. The system of claim 7, wherein the evaluation module, when evaluating the security of the face tag, obtains the duration T of the security status of the environmental status in the video image, compares the duration T with a preset standard duration T0, and evaluates the security of the face tag according to the comparison result, wherein,
when T is less than T0, the evaluation module judges that the reliability of the face label does not meet the requirement;
and when the T is larger than or equal to T0, the evaluation module judges that the reliability of the surface label meets the requirement, and the surface label module carries out signature prompt.
9. The remote video-based mortgage surface signing on-line processing system of claim 1, wherein the users include staff and ordinary users, the staff logs in through the work code, and the ordinary users log in through the identification number.
10. A method for use in the remote video-based mortgage face-on-line processing system of any one of claims 1-9, comprising,
s1, carrying out identity authentication on a logged-in common user;
s2, acquiring a real-time video image of the ordinary user passing the identity authentication;
s3, carrying out data analysis on the collected real-time video image to determine the number of personnel and dangerous goods in the video image;
s4, evaluating the reliability of the tag according to the data analysis result, calculating the safety coefficient of the environment in real time according to the number of people in the video image during evaluation, judging the environment state of a common user according to the safety coefficient, adjusting the safety coefficient according to the number of dangerous goods in the video image during calculation of the safety coefficient, correcting the adjusted safety coefficient according to the video interruption frequency, and evaluating the reliability of the tag according to the duration of the environment safety state in the video image after judgment of the environment state is completed;
and S5, prompting a common user to sign when the reliability of the surface label meets the requirement.
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