Bionic identity verification calibration method based on human-computer interaction technology

Abstract

The invention relates to the technical field of identity verification, in particular to a bionic identity verification calibration method based on a man-machine interaction technology, which comprises the following steps: installing a manipulator and a man-machine interaction panel on an identity verification gate, and applying the man-machine interaction panel to guide interaction with a user executing identity verification operation, applying a manipulator to point to an operation position on the identity verification gate machine to provide a guide service for the user; in a verification stage when the human-computer interaction panel captures the face of the user, synchronously acquiring a face image of the user, and further optimizing the face image of the user; through interaction of bionic intelligent hardware and a digital person, passengers are guided to operate in real time, and retention caused by an undefined operation process is reduced, so that the passing efficiency is remarkably improved, the dependence of an identity verification position on manual intervention is reduced, workers can concentrate on other important tasks, and the workload is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of identity authentication, and in particular to a bionic identity authentication calibration method based on human-computer interaction technology. Background Art

[0002] In modern airports, rail transit and other transportation hubs, turnstiles, as important access equipment, usually rely on passengers to operate them independently, such as scanning their faces, ID cards or tickets.

[0003] The invention patent with application number 201410264485.5 discloses an identity authentication system, including: The biometric information acquisition and storage device includes a biometric information acquisition module for acquiring biometric information and digitizing the acquired biometric information; the biometric information acquisition and storage device also includes a distributed processing module for encrypting the digitized biometric information and distributing the encrypted data to form more than three data blocks, each of which is stored in a different storage device, and each of which does not contain the complete data of the biometric information; the identity authentication system also has a verification device, which has a data acquisition module for acquiring data stored in multiple storage devices: a data merging module for merging the acquired data and decrypting the merged data; a verification module for comparing the decrypted data with the digitized biometric information data obtained by the biometric information acquisition module, and verifying the authenticity of the identity based on the comparison result.

[0004] The application aims to solve the following problem: "With the development of network technology and electronic technology, cloud storage technology has become a widely used Internet storage technology. In order to ensure the security of data stored on the network, passwords are usually used to protect the stored data. However, due to the different password requirements on many different systems and platforms, the passwords stored in different systems are usually different, which makes it difficult for people to remember and manage; and if the data is stored on a single network system, it will bring great risks to the security of the data. For example, if the network system is attacked by external attacks, hackers or viruses, it will cause data leakage, and data management loopholes will also cause data to be copied and stolen. The data may also be accidentally or maliciously modified, stolen or sold, lost, etc. In addition, unreasonable use of data managers, such as a department being able to arbitrarily view data stored on the server of another department, all lead to the leakage of data stored on the network; once the fingerprint information of people stored by the entry-exit management department is leaked, it will cause the leakage of people's personal information. Moreover, once people's fingerprint information is used by criminals, it will also cause great harm to society."

[0005] However, some passengers often stay in front of the gate because they are not clear about the operation process, which reduces the efficiency of passage. In addition, the proportion of improper operation by passengers is too high, requiring staff to intervene multiple times to give instructions or stand by the side throughout the process, which further reduces the efficiency of self-service passage and increases labor costs. Summary of the invention

[0006] In view of the above-mentioned shortcomings of the prior art, the present invention provides a bionic identity authentication calibration method based on human-computer interaction technology, which solves the technical problems raised in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: A bionic identity authentication calibration method based on human-computer interaction technology, comprising: A robot and a human-machine interaction panel are installed on the identity authentication gate, and the human-machine interaction panel is used to guide and interact with the user who performs the identity authentication operation, and the robot is used to point to the operation position on the identity authentication gate to provide guidance services for the user; in the verification stage when the human-machine interaction panel captures the user's face, the user's face image is synchronously collected, and the user's face image is further optimized; the user's identity magnetic card information sensed at the operation position on the identity authentication gate is compared with the complete and optimized user face image for similarity to determine whether the user's identity authentication is passed; the gate is controlled to open when the user's identity authentication is passed, and the gate is controlled to remain closed when the user's identity authentication is not passed; when the user fails to pass the authentication at the identity authentication gate, the identity authentication gate issues a voice prompt and feeds back the current verification result to the identity authentication gate management user.

[0008] Furthermore, the human-machine interaction panel is integrated with a camera and a speaker. The camera captures the dynamic face closest to its own lens end and facing itself in real time, and the speaker stores prompt voices such as "please move your head upwards", "please move your head downwards", "please move your head to the left", and "please move your head to the right". After capturing the dynamic face, the camera simultaneously identifies the relative position of the dynamic face and controls the speaker to emit a corresponding prompt sound based on the relative position of the dynamic face.

[0009] Furthermore, the speaker stores English prompt voices indicating "Please move your head up", "Please move your head down", "Please move your head to the left", and "Please move your head to the right". When the camera captures a dynamic face, it synchronously identifies the color of the pupils in the dynamic face, and further binds the pupil color with the Chinese and English prompt voices, and decides on the language of the prompt voice based on the recognized pupil color in the dynamic face.

[0010] Furthermore, the recognition logic of the relative position of the dynamic face is expressed as: ; Where: is the lateral reference distance; is the longitudinal reference distance; The center coordinates of the user's face in the vertical perspective relative to the human-computer interaction panel and the user performing identity authentication; The center coordinates of the authentication area on the human-computer interaction panel; The user face center coordinates refer to the coordinates of the user's nose tip on the user's face image. ,and When it is a negative number, the speaker will issue a voice prompt "Please move your head to the right". ,and When it is a positive number, the speaker will issue a voice prompt "Please move your head to the right". ,and When it is a negative number, the speaker will issue a prompt "Please move your head upwards". ,and When it is a positive number, the speaker issues a voice prompt of "Please move your head down". Based on the above operations, the human-computer interaction interface collects the complete face of the user performing identity authentication.

[0011] Furthermore, a designated operation logic is set in the manipulator, and when the designated operation frequency is operated, the manipulator moves from the initial position to above the identity verification gate based on the designated operation logic, pointing to the user identity magnetic card sensing area on the identity verification gate; Among them, the user identity magnetic card sensing area is the operating position on the identity verification gate. During the operation stage of the robot, it monitors in real time whether the human-computer interaction panel captures the user's face. When the user's face is captured, it triggers the operation.

[0012] Furthermore, the user face image is collected from a dynamic image containing the user face captured by the human-computer interaction. In the user face image collection stage, the dynamic image is segmented to obtain a plurality of user face frames, the quality of each user face frame is identified, and a user face frame with the best quality is selected as an optimization processing target; Among them, the user face picture frame is the user face image.

[0013] Furthermore, when identifying the quality of the user face frame, any one of a PSNR algorithm and a SSIM algorithm is applied for identification.

[0014] Furthermore, the optimization processing logic of the user face image is expressed as: ; Where: is the Hamming distance between user face image A and user face image B; is the total amount of hash codes for face images; , is the i-th hash code in user face image A and user face image B; in, The smaller the value, the higher the similarity between the two user face images. Compare, in When the similarity determination threshold is met, the user face verification is determined to have passed; otherwise, the user face verification is determined to have failed.

[0015] Furthermore, the duration of each opening of the identity verification gate is customized by the user, and the application of the identity verification gate opening duration starts counting after each user identity verification is passed; During the identity authentication gate opening phase, the user identity authentication operation is performed synchronously. After the user identity authentication is passed and the identity authentication gate senses the passing of a moving target, the currently configured opening duration of the identity authentication gate is iterated by the new opening duration.

[0016] Furthermore, the identity verification gate generates an operation message synchronously during daily operation: The operation message content generated by the identity authentication gate includes: the cumulative number of users passing through, the similarity comparison results of user identities, the number of verification errors, and the iteration frequency of the duration of the identity authentication gate opening.

[0017] Compared with the known public technology, the technical solution provided by the present invention has the following beneficial effects: The present invention provides a bionic identity authentication calibration method based on human-computer interaction technology. During the execution of the method, bionic intelligent hardware and digital human interaction are used to guide passengers' operations in real time, reduce detention caused by unclear operation procedures, thereby significantly improving the passage efficiency, reducing the dependence of identity authentication positions on manual intervention, and enabling staff to focus on other important tasks and reduce their workload. Through intuitive interaction, passengers can obtain real-time and clear operation guidance, improve the overall user experience, reduce confusion and anxiety caused by improper operation, monitor the passenger's operation status in real time, and make dynamic adjustments based on feedback, thereby improving the intelligence level of identity authentication, ensuring the functionality and efficiency of the gate, and improving the overall travel experience of passengers. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 Schematic diagram of a flow chart of a bionic identity authentication calibration method based on human-computer interaction technology. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] The present invention will be further described below in conjunction with the embodiments.

[0022] Embodiment 1: A bionic identity authentication calibration method based on human-computer interaction technology in this embodiment, such as Figure 1 As shown, including: A manipulator and a human-machine interaction panel are installed on the identity authentication gate, and the human-machine interaction panel is used to guide and interact with the user who performs the identity authentication operation, and the manipulator is used to point to the operation position on the identity authentication gate to provide guidance services for the user; During the verification phase when the human-computer interaction panel captures the user's face, the user's face image is collected synchronously, and the user's face image is further optimized; The user's identity card information sensed at the operating position on the identity verification gate is compared with the complete and optimized user's face image to determine whether the user's identity verification has been passed; The recognition logic of the relative position of dynamic faces is expressed as: ; Where: is the lateral reference distance; is the longitudinal reference distance; The center coordinates of the user's face in the vertical perspective relative to the human-computer interaction panel and the user performing identity authentication; The center coordinates of the authentication area on the human-computer interaction panel; The user face center coordinates refer to the coordinates of the user's nose tip on the user's face image. ,and When it is a negative number, the speaker will issue a voice prompt "Please move your head to the right". ,and When it is a positive number, the speaker will issue a voice prompt "Please move your head to the right". ,and When it is a negative number, the speaker will issue a prompt "Please move your head upwards". ,and When it is a positive number, the speaker will issue a voice prompt of "Please move your head downwards", and the complete face of the user performing identity authentication is collected on the human-computer interaction interface based on the above operations; When the user identity verification is passed, the gate is controlled to open; when the user identity verification is not passed, the gate is controlled to remain closed; When the user fails to pass the authentication at the identity verification gate, the identity verification gate will issue a voice prompt and feedback the current authentication result to the identity verification gate management user; The robot is set with a specified operation logic. When the robot operates at a specified operation frequency, the robot moves from the initial position to the top of the identity verification gate based on the specified operation logic, pointing to the user identity magnetic card sensing area on the identity verification gate; Among them, the user identity magnetic card sensing area is the operating position on the identity verification gate. During the operation stage of the robot, it monitors in real time whether the human-computer interaction panel captures the user's face. When the user's face is captured, it triggers the operation; When identifying the quality of the user's face frame, either the PSNR algorithm or the SSIM algorithm is used for identification; The optimization processing logic of user face images is expressed as: ; Where: is the Hamming distance between user face image A and user face image B; is the total amount of hash codes for face images; , is the i-th hash code in user face image A and user face image B; in, The smaller the value, the higher the similarity between the two user face images. Compare, in When the similarity determination threshold is met, the user face verification is determined to have passed; otherwise, the user face verification is determined to have failed.

[0023] like Figure 1As shown, the human-computer interaction panel is integrated with a camera and a speaker. The camera captures the dynamic face closest to its own lens end and facing itself in real time, and the speaker stores the prompt voices of "Please move your head up", "Please move your head down", "Please move your head to the left", and "Please move your head to the right". After capturing a dynamic face, the camera simultaneously identifies the relative position of the dynamic face and controls the speaker to emit a corresponding prompt sound based on the relative position of the dynamic face; The speaker stores prompt voices in English, such as "Please move your head up", "Please move your head down", "Please move your head to the left", and "Please move your head to the right". When the camera captures a dynamic face, it simultaneously identifies the color of the pupils in the dynamic face, and further binds the pupil color with the prompt voices in Chinese and English. The application of the prompt voice language is determined based on the recognized pupil color in the dynamic face. The identity verification gate generates operation messages synchronously during daily operation: The operation message content generated by the identity authentication gate includes: the cumulative number of users passing through, the similarity comparison results of user identities, the number of verification errors, and the iteration frequency of the duration of the identity authentication gate opening.

[0024] In this embodiment, through the method in the above embodiment, passengers are guided in real time to reduce detentions caused by unclear operating procedures, thereby significantly improving travel efficiency and reducing the reliance of identity verification locations on manual intervention, allowing staff to focus on other important tasks and reduce their workload.

[0025] Embodiment 2: In terms of specific implementation, based on Example 1, this example refers to Figure 1 The bionic identity authentication calibration method based on human-computer interaction technology in Example 1 is further specifically described as follows: The user face image is collected from a dynamic image containing the user face captured by the human-computer interaction. In the user face image collection stage, the dynamic image is segmented to obtain a number of user face frames, the quality of each user face frame is identified, and the user face frame with the best quality is selected as the optimization processing target; Among them, the user face picture frame is the user face image.

[0026] like Figure 1 As shown, the duration of each opening of the identity authentication gate is customized by the user, and the application of the opening duration of the identity authentication gate starts counting after each user identity authentication is passed; During the authentication gate opening phase, the user identity authentication operation is performed synchronously. After the user identity authentication is passed and the authentication gate senses the passing of a moving target, the currently configured opening duration of the authentication gate is iterated by the new opening duration.

[0027] In this embodiment, the above settings provide further step execution logic and data support for the execution of the method in Example 1, ensuring the stable execution of the method in Example 1 and bringing auxiliary effects to the identity authentication gate.

[0028] In summary, during the execution of the method in the above embodiment, bionic intelligent hardware and digital human interaction are used to guide passengers' operations in real time, reduce detentions caused by unclear operating procedures, thereby significantly improving traffic efficiency, reducing the dependence of identity authentication locations on manual intervention, and enabling staff to focus on other important tasks and reduce workload. Through intuitive interaction, passengers can obtain real-time and clear operating instructions, improve the overall user experience, reduce confusion and anxiety caused by improper operation, monitor passengers' operations in real time, and make dynamic adjustments based on feedback, thereby improving the intelligence level of identity authentication, ensuring the functionality and efficiency of the gate, and improving the overall travel experience of passengers.

[0029] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A bionic identity verification calibration method based on human-computer interaction technology, characterized in that: include: A manipulator and a human-machine interaction panel are installed on the identity authentication gate, and the human-machine interaction panel is used to guide and interact with the user who performs the identity authentication operation, and the manipulator is used to point to the operation position on the identity authentication gate to provide guidance services for the user; During the verification phase when the human-computer interaction panel captures the user's face, the user's face image is collected synchronously, and the user's face image is further optimized; The user's identity card information sensed at the operating position on the identity verification gate is compared with the complete and optimized user's face image to determine whether the user's identity verification has been passed; When the user identity verification is passed, the gate is controlled to open; when the user identity verification is not passed, the gate is controlled to remain closed; When the user fails to pass the authentication at the identity verification gate, the identity verification gate will issue a voice prompt and feedback the current authentication result to the identity verification gate management user.

2. According to the bionic identity verification calibration method based on human-computer interaction technology in claim 1, it is characterized in that: The human-machine interaction panel is integrated with a camera and a speaker. The camera captures the dynamic face closest to its own lens end and facing itself in real time. The speaker stores prompt voices such as "Please move your head upwards", "Please move your head downwards", "Please move your head to the left", and "Please move your head to the right". After capturing the dynamic face, the camera simultaneously identifies the relative position of the dynamic face and controls the speaker to emit a corresponding prompt sound based on the relative position of the dynamic face.

3. According to claim 2, a bionic identity verification calibration method based on human-computer interaction technology is characterized in that: The speaker stores English prompt voices indicating "Please move your head up", "Please move your head down", "Please move your head to the left", and "Please move your head to the right". When the camera captures a dynamic face, it synchronously identifies the color of the pupils in the dynamic face, and further binds the prompt voices in Chinese and English based on the pupil color, and decides on the application of the prompt voice language based on the recognized pupil color in the dynamic face.

4. The bionic identity verification calibration method based on human-computer interaction technology according to claim 1, characterized in that: The recognition logic of the relative position of the dynamic face is expressed as: ； Where: is the lateral reference distance; is the longitudinal reference distance; The coordinates of the center of the user's face in the vertical perspective relative to the human-computer interaction panel and the user performing identity authentication; The center coordinates of the authentication area on the human-computer interaction panel; The user face center coordinates refer to the coordinates of the user's nose tip on the user's face image. ,and When it is a negative number, the speaker will issue a voice prompt "Please move your head to the right". ,and When it is a positive number, the speaker will issue a voice prompt "Please move your head to the right". ,and When it is a negative number, the speaker will issue a prompt "Please move your head upwards". ,and When it is a positive number, the speaker issues a voice prompt of "Please move your head down". Based on the above operations, the human-computer interaction interface collects the complete face of the user performing identity authentication.

5. The bionic identity verification calibration method based on human-computer interaction technology according to claim 1, characterized in that: The manipulator is set with a designated operation logic. When the designated operation frequency is in operation, the manipulator moves from the initial position to above the identity verification gate based on the designated operation logic, pointing to the user identity magnetic card sensing area on the identity verification gate; Among them, the user identity magnetic card sensing area is the operating position on the identity verification gate. During the operation stage of the robot, it monitors in real time whether the human-computer interaction panel captures the user's face. When the user's face is captured, it triggers the operation.

6. The bionic identity verification calibration method based on human-computer interaction technology according to claim 1, characterized in that: The user face image is collected from a dynamic image containing the user face captured by the human-computer interaction. In the user face image collection stage, the dynamic image is segmented to obtain a plurality of user face frames, the quality of each user face frame is identified, and a user face frame with the best quality is selected as an optimization processing target; Among them, the user face picture frame is the user face image.

7. The bionic identity verification calibration method based on human-computer interaction technology according to claim 1, characterized in that: When identifying the quality of the user face frame, any one of the PSNR algorithm and the SSIM algorithm is used for identification.

8. The bionic identity verification calibration method based on human-computer interaction technology according to claim 1, characterized in that: The optimization processing logic of the user face image is expressed as: ； Where: is the Hamming distance between user face image A and user face image B; is the total amount of hash codes for face images; , is the i-th hash code in user face image A and user face image B; in, The smaller the value, the higher the similarity between the two user face images. Compare, in When the similarity determination threshold is met, the user face verification is determined to have passed; otherwise, the user face verification is determined to have failed.

9. The bionic identity verification calibration method based on human-computer interaction technology according to claim 1, characterized in that: The duration of each opening of the identity verification gate is customized by the user, and the duration of the identity verification gate opening is applied to start timing each time the user's identity verification is passed; During the identity authentication gate opening phase, the user identity authentication operation is performed synchronously. After the user identity authentication is passed and the identity authentication gate senses the passing of a moving target, the currently configured opening duration of the identity authentication gate is iterated by the new opening duration.

10. The bionic identity verification calibration method based on human-computer interaction technology according to claim 1, characterized in that: The identity verification gate generates operation messages synchronously during daily operation: The operation message content generated by the identity authentication gate includes: the cumulative number of users passing through, the similarity comparison results of user identities, the number of verification errors, and the iteration frequency of the duration of the identity authentication gate opening.

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