CN111080438A - Credit report self-service printing method - Google Patents
Credit report self-service printing method Download PDFInfo
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- CN111080438A CN111080438A CN201911281920.4A CN201911281920A CN111080438A CN 111080438 A CN111080438 A CN 111080438A CN 201911281920 A CN201911281920 A CN 201911281920A CN 111080438 A CN111080438 A CN 111080438A
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- 238000001727 in vivo Methods 0.000 claims description 3
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- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/12—Digital output to print unit, e.g. line printer, chain printer
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Abstract
The invention discloses a credit report self-service printing method, which comprises the following steps: s1: a face image collection step, which is used for establishing an information base with face images for the identity information acquisition codes; s2: a face image information acquisition step, namely reading a mobile information card with face image information presented by a user by a self-service printing terminal; s3: an offline living body detection SDK step, configured to detect and acquire the living body of the face of the user, compare consistency between the face image and the living body image in the mobile information card, and perform step S2 if the consistency is inconsistent; s4: an off-line human face image information base comparison step, wherein the human face image after the off-line living body detection SDK is compared with the human face image in the information base, and when the comparison is not consistent, the step S2 is executed; s5: and a self-service printing step, wherein the user prints out the credit report through a printer by self service. The invention has strong practicability, simple and convenient operation, high safety and wide application range.
Description
Technical Field
The invention relates to the field of credit report self-service printing methods.
Background
The society develops faster and faster nowadays, people move more and more frequently, and particularly, related financial services are penetrated into various industries. Therefore, social credibility is increasingly valued, such as: the driving license, good personal and good events, social public welfare, job title and the like help us to establish a good credit, the citizen credit is high, and the method is an embodiment of citizen quality and an embodiment of social robust development. Particularly, the credit degree related to personal credit investigation is high, which is beneficial to improving the social status; in the past, people who want to know personal credit need to go to related banks to inquire and print, and the people can better inquire on the ATM by self. This often brings a lot of inconvenience, and the security of the general ATM self-service query is not high, which brings risks to the customer, and the personal privacy may be leaked. It would be desirable to be able to safely and quickly self-query and print personal credit reports.
Disclosure of Invention
The purpose of the invention is as follows: in order to overcome the defects in the prior art, the invention provides a self-service printing method of a credit report, which can realize the effect of safely and quickly self-service printing of the credit report in an off-line state.
The technical scheme is as follows: in order to achieve the purpose, the technical scheme of the invention is as follows:
a credit report self-service printing method comprises the following steps:
s1: a face image collection step, which is used for establishing an information base with face images for the identity information acquisition codes;
s2: a face image information acquisition step, namely reading a mobile information card with face image information presented by a user by a self-service printing terminal;
s3: an offline living body detection SDK step, configured to detect and acquire the living body of the face of the user, compare consistency between the face image and the living body image in the mobile information card, and perform step S2 if the consistency is inconsistent;
s4: an off-line human face image information base comparison step, wherein the human face image after the off-line living body detection SDK is compared with the human face image in the information base, and when the comparison is not consistent, the step S2 is executed;
s5: and a self-service printing step, wherein the user prints out the credit report through a printer by self service.
Further, the step of obtaining the face image information comprises reading information of an identity card and a citizen card to obtain the face image.
Further, the off-line living body detection SDK face living body image feature extraction algorithm is a deep learning method.
Further, the step of off-line in-vivo detection SDK is divided into two flows,
the first flow is a front-end face moving end face living body detection technology;
and the second process is background offline face recognition.
Furthermore, the front-end face moving end face living body detection technology ensures that the operation is the real living body face through the combined actions of blinking, mouth opening, head shaking and head nodding at the front end.
Further, the background offline face recognition is to obtain the whole face image in the mobile end face living body detection technology link, then to scan and recognize the identity card or the citizen card, and to compare and recognize the on-site face image with the face image on the identity card or the citizen card after obtaining the face image.
Further, under the condition that the contrast of the face image after the off-line living body detection SDK is consistent with the contrast of the face image in the information base, the face image in the mobile information card, the face living body image and the face image in the information base are simultaneously compared and are all in an off-line state.
Further, the user views the displayed credit report information on a display screen of the mobile terminal; and the user confirms the printing of the credit report on the touch screen of the mobile terminal, and the mobile terminal controls the printer to print the credit report.
Has the advantages that: the invention has strong practicability, simple and convenient operation, high safety and wide application range. Including but not limited to the following technical effects:
1) the self-service printing end collects a living body face image by using an offline living body detection SDK technology and performs primary two-way comparison and secondary three-way comparison in an offline state, so that the safety of client information is improved, and the leakage of the client information is avoided;
2) the multi-mode verification information and the mode of comparing and verifying under the offline condition for many times bring convenience to the client, effectively avoid the risk of client information leakage, and improve a safer inquiry printing environment for the client.
Drawings
FIG. 1 is a diagram of the steps of a credit report self-service printing method;
FIG. 2 is an off-line alignment schematic.
Detailed Description
The present invention will be further described with reference to the accompanying drawings.
As shown in the attached figures 1-2: a credit report self-service printing method comprises the following steps:
s1: a face image collection step, which is used for establishing an information base with face images for the identity information acquisition codes; the information base is obtained from the cloud in a networking state;
s2: a face image information acquisition step, namely reading a mobile information card with face image information presented by a user by a self-service printing terminal; storing the information with the face image into a hard disk of a self-service printing end;
s3: an offline living body detection SDK step, configured to detect and acquire the living body of the face of the user, compare consistency between the face image and the living body image in the mobile information card, and perform step S2 if the consistency is inconsistent; mainly comparing facial features on two people connected images;
s4: an off-line human face image information base comparison step, wherein the human face image after the off-line living body detection SDK is compared with the human face image in the information base, and when the comparison is not consistent, the step S2 is executed; comparing the face image obtained by the off-line living body detection SDK, the face image obtained by the mobile information card and the face image in the information base in three ways;
s5: and a self-service printing step, wherein the user prints out the credit report through a printer by self service. The customer can check the credit information on the display screen of the self-service printing terminal and then select whether to print or not.
The step of acquiring the face image information comprises the steps of reading the information of an identity card and a citizen card to acquire a face image; the citizen card can replace an identity card on a certain basis, and convenience is brought to doing things in our trip.
The off-line living body detection SDK face living body image feature extraction algorithm is a deep learning method. An SDK, a software development kit, is a collection of development tools used by software engineers to create application software for a particular software package, software framework, hardware platform, operating system, and the like.
The step of off-line in-vivo detection SDK is divided into two flows,
the first flow is a front-end face moving end face living body detection technology; detecting whether an operator is a living body;
and the second process is background offline face recognition.
The front-end face moving end face living body detection technology ensures that the operated real living body face is the real living body face through the combined actions of blinking, mouth opening, shaking and nodding at the front end. The obtained face image is detected to be an image set of the whole face, so that the situation that an illegal person provides a face photo of a client for the camera for taking the photo to finish the photo taking can be avoided, and the personal privacy safety of the client is effectively guaranteed.
The background offline face recognition is to obtain the whole face image in the mobile end face living body detection technology link, then to scan and recognize the identity card or the citizen card, and to compare and recognize the on-site face image with the face image on the identity card or the citizen card after obtaining the face image. The background compares the acquired face images in an off-line state to determine whether the face images are consistent, so that the online comparison is prevented from being attacked by network viruses or a network illegal person from stealing client information.
Under the condition that the human face image after the off-line living body detection SDK is compared and moved consistently with the human face image in the information base, the human face image in the mobile information card, the human face living body image and the human face image in the information base are compared simultaneously and are all in an off-line state; after the identity is confirmed once, the confirmed face image is compared with the information in the information base again to confirm, three-party comparison is formed, and the whole comparison and confirmation process is in an off-line state, so that the information in the information base can be effectively prevented from being stolen, and the information safety of customers is guaranteed.
The user checks the displayed credit report information on a display screen of the mobile terminal; and the user confirms the printing of the credit report on the touch screen of the mobile terminal, and the mobile terminal controls the printer to print the credit report. After two off-line face comparison confirmation, the customer can check the personal credit information and select printing.
The specific operation implementation steps are as follows: the information base in the step S1 is an information base in the cloud, and when a customer reads a card to identify the identity, information related to the customer is downloaded from the cloud base to the hard disk of the self-service printing terminal; s2, the off-line living body detection SDK acquires information from the client identity card or the citizen card; s3, simultaneously acquiring living body face image information from the camera by an offline living body detection SDK; then, comparing the living body face image with the face image on the identity card or the citizen card in an off-line state; after the consistency is confirmed, comparing the facial image with the facial image in the hard disk of the self-service printing end at the same time, and confirming again; after the confirmation is finished, the customer can check the credit information from the self-service printing terminal and choose to print out the credit report. When the comparison is inconsistent, the customer needs to show the identity card or the citizen card again so that the self-service printing end can obtain the information of the customer mobile card again.
The whole operation process is simple, convenient and quick, and the privacy safety of the client is effectively guaranteed through comparison and confirmation in an off-line state twice; meanwhile, the client can finish the printing of the credit report by self by using the citizen card, and the inconvenience caused by the loss of the identity card or the inconvenience caused by no carrying about can be effectively avoided.
The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention and these are intended to be within the scope of the invention.
Claims (8)
1. A credit report self-service printing method is characterized by comprising the following steps:
s1: a face image collection step, which is used for establishing an information base with face images for the identity information acquisition codes;
s2: a face image information acquisition step, namely reading a mobile information card with face image information presented by a user by a self-service printing terminal;
s3: an offline living body detection SDK step, configured to detect and acquire the living body of the face of the user, compare consistency between the face image and the living body image in the mobile information card, and perform step S2 if the consistency is inconsistent;
s4: an off-line human face image information base comparison step, wherein the human face image after the off-line living body detection SDK is compared with the human face image in the information base, and when the comparison is not consistent, the step S2 is executed;
s5: and a self-service printing step, wherein the user prints out the credit report through a printer by self service.
2. The method of claim 1, wherein the method further comprises: the step of acquiring the face image information comprises the step of reading the information of the identity card and the citizen card to acquire the face image.
3. The method of claim 1, wherein the method further comprises: the off-line living body detection SDK face living body image feature extraction algorithm is a deep learning method.
4. A credit report self-service printing method according to claim 1 or 3, characterized in that: the step of off-line in-vivo detection SDK is divided into two flows,
the first flow is a front-end face moving end face living body detection technology;
and the second process is background offline face recognition.
5. The credit report self-service printing method according to claim 1 or 4, wherein: the front-end face moving end face living body detection technology ensures that the operated real living body face is the real living body face through the combined actions of blinking, mouth opening, shaking and nodding at the front end.
6. The credit report self-service printing method according to claim 1 or 5, wherein: the background offline face recognition is to obtain the whole face image in the mobile end face living body detection technology link, then to scan and recognize the identity card or the citizen card, and to compare and recognize the on-site face image with the face image on the identity card or the citizen card after obtaining the face image.
7. A credit report self-service printing method as claimed in claim 1, wherein: and under the condition that the contrast of the face image after the off-line living body detection SDK is consistent with the contrast of the face image in the information base, simultaneously comparing the face image in the mobile information card, the face living body image and the face image in the information base, and keeping the face image, the face living body image and the face image in the information base in an off-line state.
8. The method of claim 1, wherein the method further comprises: the user checks the displayed credit report information on a display screen of the mobile terminal; and the user confirms the printing of the credit report on the touch screen of the mobile terminal, and the mobile terminal controls the printer to print the credit report.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911281920.4A CN111080438A (en) | 2019-12-13 | 2019-12-13 | Credit report self-service printing method |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201911281920.4A CN111080438A (en) | 2019-12-13 | 2019-12-13 | Credit report self-service printing method |
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| CN111080438A true CN111080438A (en) | 2020-04-28 |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112036340A (en) * | 2020-09-03 | 2020-12-04 | 北京盛华聚龙科技有限公司 | Enterprise credit report query method and device |
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2019
- 2019-12-13 CN CN201911281920.4A patent/CN111080438A/en active Pending
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| CN107944378A (en) * | 2017-11-20 | 2018-04-20 | 广东金赋科技股份有限公司 | The personal identification method and self-help serving system of a kind of Self-Service |
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Application publication date: 20200428 |