Visitor passing method and passing system

Abstract

The invention relates to the technical field of intelligent passing, in particular to a visitor passing method and system. Comprising the steps that a visitor body is placed in front of a face recognition module, the face recognition module extracts face features, an identity card is placed on an identity card recognition module, and identity card information recognition is carried out; the central processing unit receives the identity card information and judges whether the big data storage unit performs visitor comparison distinguishing feature input or not; if the visitor comparison distinguishing characteristics are input, directly extracting the face judgment distinguishing characteristics, comparing the face judgment distinguishing characteristics with the comparison distinguishing characteristics, and if the face judgment distinguishing characteristics are consistent with the comparison distinguishing characteristics, automatically inputting the comparison distinguishing characteristics according to the previous information input condition and releasing the visitor; if the visitor compares that the distinguishing feature is not input, extracting the face feature, comparing the face feature with the face feature recorded in the identity card information, judging whether the face feature is consistent with the face feature recorded in the identity card information or not, if so, inputting the information by the visitor through the system, and releasing; the system can realize rapid identification and authentication and rapid release.

Description

Technical Field

[0001] The present invention relates to the field of smart access technology, and in particular to a visitor access method and access system. Background Art

[0002] ‌Visitor access system‌ is a software system used to manage visitors entering and exiting a company or organization, and is mainly used in public places such as enterprises, schools, hospitals, and hotels. Its main functions include visitor reservations, identity verification, electronic signatures, and printing visitor cards, etc., aiming to improve security and convenience; the visitor access system is often used in conjunction with gates and face entry recognition devices. Visitors use the face recognition entry recognition device and the ID card information recognition device to determine that the visitor is himself. Sometimes, in order to facilitate and efficiently enter the information of visitors, a corresponding information entry system will be configured and designed. Visitors can identify the corresponding website or applet through their mobile phones to enter the corresponding visit information on the mobile phone. However, for some places with dense traffic and in peak traffic conditions, the design of the corresponding visitor communication system and gate may affect the speed of visitor travel, but arbitrarily releasing visitors, safety cannot be guaranteed.

[0003] Based on the above problems, there is an urgent need for a visitor access method and access system that can quickly identify and authenticate visitors, quickly release visitors, and ensure security. Summary of the invention

[0004] The current visitor access system performs facial information entry and authentication as well as visitor information entry during peak traffic hours, which may affect the travel speed of visitors. This application provides a visitor access method and access system to solve the above problem.

[0005] To achieve the above object, the present invention is implemented through the following technical solutions: The present application embodiment discloses a visitor access method, including: The visitor stands in front of the face recognition module, which extracts the facial features and places the ID card on the ID card recognition module to identify the ID card information; The central processing unit receives the ID card information and determines whether the big data storage unit performs visitor comparison and distinguishing feature entry; If the visitor's comparison distinguishing features are entered, the facial distinguishing features are directly extracted, and the facial distinguishing features are compared with the comparison distinguishing features. If they are consistent, they are automatically entered according to the previous information entry and released; If the visitor does not enter the distinguishing features, the facial features of the person are extracted and compared with the facial features recorded in the ID card information to determine whether they are consistent. If they are consistent, the visitor enters the information through the system and is released; The comparison and discrimination features of the visitor are not entered. After extracting the facial features of the face, the discrimination features of the extracted facial features are further identified and extracted, and entered into the big data storage unit as the comparison and discrimination features for the next comparison and judgment.

[0006] Adopting the above technical solution: The system provided by the above solution is applied to the visitor access method of the automatic gate. In the case of a large passenger flow, authenticating visitors one by one will cause congestion. However, the designed system can quickly compare and automatically enter information for the visitors who have been authenticated, which can greatly improve the access efficiency of visitors and reduce congestion at the same time.

[0007] Preferably, the extraction method of the discrimination features includes: Collect the still images of the visitors, extract and judge the features of the image brightness, facial blurriness and facial angle of the still images of the visitors, and screen out high-quality still images as the facial feature extraction images through the screening feature algorithm; Extract the discrimination feature points of the high-quality still images through the discrimination feature point extraction algorithm. The human face discrimination feature points include the small triangle discrimination feature and the large triangle discrimination feature of the human face. The small triangle area includes the triangle area formed by the connection line between the ends of the two eye corners and the tip of the nose, and the large triangle area includes the triangle area where the two earlobes and the center point of the mandible are located; Identify the ratio of the lengths of the three sides and the angles of the three angles of the small triangle area and the large triangle area as the discrimination feature points of the image.

[0008] Adopting the above technical solution: The above solution provides a facial recognition solution, which can realize the corresponding recognition of the specific facial features of visitors. When the user authenticates through the ID card, it can quickly compare and judge whether the visitor is the person himself and quickly enter the visitor information.

[0009] Further preferably, the process of screening high-quality still images is as follows: Establish a feature coefficient interval. There are multiple rows and columns of square grid areas on the feature coefficient space. The image brightness influence coefficients and facial blurriness influence coefficients corresponding to different square grid intervals are different. Place the collected still images of the visitors in the square grid intervals, extract the brightness feature values and blurriness feature values and calculate the screening feature values, calculate the offset angle of the still images of the visitors based on the reference contour angle, and calculate the screening feature values according to the offset angle.

[0010] Adopting the above technical solution: The above solution can realize the determination of the collected facial images of visitors, and screen out the images that are suitable in terms of brightness, facial blurriness and facial offset degree as the images to be authenticated and recognized.

[0011] Further preferably, the feature screening algorithm formula is: , in, To filter feature values, is the number of grid intervals, For the The brightness eigenvalue corresponding to the grid interval, For the The image brightness influence coefficient corresponding to the grid interval, For the The facial fuzziness eigenvalue corresponding to the grid interval, For the The facial fuzziness influence coefficient corresponding to the grid interval, is the base profile angle, Rotate the visitor's face angle. is the visitor's facial angle influence coefficient.

[0012] Adopt the above technical solution: the above solution provides a feature screening algorithm formula, which can screen out the most suitable image as the judgment image according to the brightness, blurriness and facial offset angle of the visitor's face.

[0013] Further preferably, the comparison process of the face judgment distinguishing features and the comparison distinguishing features is as follows: in the judgment distinguishing feature entry process, the identified small triangle area and the triangular figures of the large and three small areas and the ratios of the three sides and the angles of the three corners corresponding to the triangular figures are entered; after the entry of the judgment distinguishing features is confirmed according to the ID card information, the ratios of the three sides and the angles of the three corners of the small triangle area and the large triangle area on the visitor's face are identified and compared with the judgment distinguishing features; if the similarity exceeds the set threshold, the visitor information is automatically entered and released.

[0014] Adopting the above technical solution: the above solution can realize the rapid comparison and judgment of the face identification features and the contrast identification features, whether the ID card image information is consistent with the personal information, and when the visitor has been authenticated and the information has been entered within the previously set time, there is no need to enter the information again and the visitor will be released immediately.

[0015] Further preferably, if the comparison and distinction features entered into the big data storage unit are not extracted and compared within a specified time, the corresponding comparison and distinction features are eliminated.

[0016] By adopting the above technical solution, if an authenticated visitor does not continue to visit within the set time, he or she can be confirmed as an infrequent visitor and eliminated, which can reduce the storage capacity of the big data storage unit and improve the operating efficiency of the system.

[0017] Further preferably, the visitor frequency is also included in the identification. When the visitor frequency is lower than the set threshold, the facial features of the face are extracted to compare with the facial features recorded in the ID card information. When the visitor frequency is higher than the set threshold, the face determination distinguishing features are extracted and compared with the comparison distinguishing features. If there are no comparison distinguishing features in the big data storage unit, the facial features are continued to be extracted.

[0018] Adopting the above technical solution: The above solution can quickly authenticate visitors during the peak visitor period to prevent congestion, and can efficiently authenticate during the low visitor period to ensure accurate visitor information. Including: Visitor information entry unit: The visitor information entry unit can identify and authenticate the visitor's facial information and ID card information, and send the visitor information to the cloud big data storage unit in an encrypted form. Visitors can enter visitor information through the visitor information entry unit; Central processing unit: Built-in system algorithm, can screen the collected faces for high-quality freeze-frame images, can compare and judge the visitors' distinguishing features with the distinguishing features, and can also compare and judge the facial features of the faces with the facial features recorded in the ID card information; Big data storage unit: The big data storage unit stores the visitor comparison and distinction features entered by the system and the entry information of the corresponding visitors.

[0019] Further preferably, it also includes: Access authority management unit: The system can generate an invitation code based on the visitor's reservation information and send it to the visitor's terminal. The visitor uses the invitation code for identity authentication and fast access. Data statistics and query unit: The system supports daily data statistics and query functions to facilitate the management of visitor information and access records.

[0020] Further preferably, it also includes: Expired information elimination unit: the expired information elimination unit cooperates with the big data storage unit, and if the comparison and distinction features entered in the big data storage unit are not extracted and compared within the specified time, the corresponding comparison and distinction features are eliminated; Visitor frequency identification unit: The visitor frequency identification unit cooperates with the central processing unit to record the visitor frequency within a specified time. When the visitor frequency is lower than the set threshold, the facial features of the face are extracted and compared with the facial features recorded in the ID card information. When the visitor frequency is higher than the set threshold, the facial judgment distinguishing features are extracted and compared with the comparison distinguishing features. If there are no comparison distinguishing features in the big data storage unit, the facial features are extracted. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 This is a flow chart of the visitor access method for this application; Figure 2 This is the connection block diagram of the traffic system for this application.

[0023] In the figure: 1. Visitor information entry unit; 2. Central processing unit; 3. Big data storage unit; 4. Access authority management unit; 5. Data statistics and query unit; 6. Expired information removal unit; 7. Visitor frequency identification unit. DETAILED DESCRIPTION

[0024] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0025] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0026] See also Figure 1-Figure 2 , such as the design of the original visitor communication system and gate, in places with large flow of people or during peak flow of people, the travel speed of visitors may be affected. If visitors are allowed to pass arbitrarily to ensure the speed of visitors, safety cannot be guaranteed. Based on the above problems, the embodiment of the present application discloses a visitor passage method, including: The visitor stands in front of the face recognition module, which extracts the facial features and places the ID card on the ID card recognition module to identify the ID card information; The central processing unit 2 receives the ID card information and determines whether the big data storage unit 3 performs visitor comparison and distinguishing feature entry; If the visitor's comparison distinguishing features are entered, the facial distinguishing features are directly extracted, and the facial distinguishing features are compared with the comparison distinguishing features. If they are consistent, they are automatically entered according to the previous information entry and released; If the visitor does not enter the distinguishing features, the facial features of the person are extracted and compared with the facial features recorded in the ID card information to determine whether they are consistent. If they are consistent, the visitor enters the information through the system and is released; The visitor's contrast distinguishing features are not entered. After the facial features of the human face are extracted, the judgment distinguishing features of the extracted facial features are further identified and extracted, and entered into the big data storage unit 3 as contrast distinguishing features for the next contrast judgment.

[0027] It is worth mentioning that in the above scheme, after the visitor makes the first visit and enters the information, the corresponding input information will be stored and the visitor's facial comparison and distinguishing features will be entered; when the visitor makes a second visit or multiple visits, the visitor's information can be quickly authenticated to see whether the visitor's facial information is consistent with the information on the ID card. If it is consistent, the visitor's facial information will be automatically entered and released.

[0028] The method for extracting the distinguishing features comprises: Collect the visitor's frozen images, extract and judge the features of the visitor's frozen images, such as image brightness, facial blur and facial angle, and select high-quality frozen images as facial feature extraction images through a feature screening algorithm; Extracting distinguishing feature points of a high-quality frozen image by using a distinguishing feature point extraction algorithm, wherein the distinguishing feature points of a human face include small triangular distinguishing features and large triangular distinguishing features of a human face, wherein the small triangular area includes a triangular area connecting the ends of the eye corners and the nose tip, and the large triangular area includes a triangular area where the earlobes and the center point of the mandible are located; The ratio of the three sides of the small triangle area and the large triangle area and the angles of the three corners are identified as the distinguishing feature points of the image.

[0029] The above scheme provides a facial recognition scheme that can realize corresponding recognition of specific facial features of visitors. When the user authenticates through the ID card, it can quickly compare and determine whether the visitor is the real person, and quickly enter the visitor information.

[0030] The process of screening high-quality still images is as follows: establishing a feature coefficient interval, setting a plurality of rows and columns of square grid areas in the feature coefficient space, the image brightness influence coefficients and facial blur influence coefficients corresponding to the intervals where different square grids are located are different, placing the collected still images of the visitors in the square grid intervals, extracting the brightness characteristic values ​​and blur characteristic values, calculating the screening characteristic values, calculating the offset angle of the still images of the visitors based on the reference contour angle, and calculating the screening characteristic values ​​according to the offset angle.

[0031] The above scheme can realize the determination of the collected visitor's facial images, and screen out images with suitable brightness, facial blur and facial deviation as the authenticated recognition images.

[0032] The feature screening algorithm formula is: , in, To filter feature values, is the number of grid intervals, For the The brightness eigenvalue corresponding to the grid interval, For the The image brightness influence coefficient corresponding to the grid interval, For the The facial fuzziness eigenvalue corresponding to the grid interval, For the The facial fuzziness influence coefficient corresponding to the grid interval, is the base profile angle, Rotate the visitor's face angle. is the visitor’s facial angle influence coefficient.

[0033] The above scheme provides a feature screening algorithm formula, which can screen out the most suitable image as the judgment image according to the brightness, blurriness and facial offset angle of the visitor's face.

[0034] The comparison process of the face judgment distinguishing features and the comparison distinguishing features is as follows: in the judgment distinguishing feature entry process, the identified small triangle area and the triangle figures of the large and three small areas and the ratios of the three sides and the angles of the three corners corresponding to the triangle figures are entered; after the judgment distinguishing feature entry is confirmed according to the ID card information, the ratios of the three sides and the angles of the three corners of the small triangle area and the large triangle area on the visitor's face are identified and compared with the judgment distinguishing features; if the similarity exceeds the set threshold, the visitor information is automatically entered and released.

[0035] The above scheme can quickly compare and judge the distinguishing features of the face and the contrast distinguishing features to determine whether the ID card image information is consistent with the personal information, and when the visitor has been authenticated and the information has been entered within the previously set time, the visitor will be released immediately without having to enter the information.

[0036] If the comparison and distinction features recorded in the big data storage unit 3 are not extracted and compared within the specified time, the corresponding comparison and distinction features will be eliminated.

[0037] If an authenticated visitor does not continue to visit within the set time, he or she can be identified as an infrequent visitor and removed, which can reduce the storage capacity of the big data storage unit 3 and improve the operating efficiency of the system.

[0038] It also includes identifying the visitor frequency. When the visitor frequency is lower than the set threshold, the facial features of the face are extracted to compare with the facial features recorded in the ID card information. When the visitor frequency is higher than the set threshold, the face judgment distinguishing features are extracted and compared with the comparison distinguishing features. If there are no comparison distinguishing features in the big data storage unit 3, the facial features are continued to be extracted.

[0039] The above solution can quickly authenticate visitors during peak visitor periods to prevent congestion, and can efficiently authenticate visitors during low visitor periods to ensure accurate visitor information. It includes: Visitor information entry unit 1: The visitor information entry unit 1 can identify and authenticate the visitor's facial information and ID card information, and send the visitor information to the cloud big data storage unit 3 in an encrypted form. The visitor can enter the visitor information through the visitor information entry unit 1; Central processing unit 2: Built-in system algorithm, capable of screening high-quality frozen images of collected faces, capable of comparing and judging the distinguishing features of visitors with the distinguishing features, and capable of comparing and judging the facial features of people with the facial features recorded in the ID card information; Big data storage unit 3: Big data storage unit 3 stores the visitor comparison and distinction features entered by the system and the entry information of the corresponding visitors.

[0040] Also includes: Access authority management unit 4: The system can generate an invitation code based on the visitor's reservation information and send it to the visitor's terminal. The visitor uses the invitation code to authenticate his identity and achieve fast access; Data statistics and query unit 5: The system supports daily data statistics and query functions to facilitate the management of visitor information and access records.

[0041] Also includes: Expired Information Removal Unit 6: The Expired Information Removal Unit 6 cooperates with the Big Data Storage Unit 3. If extraction and comparison are not performed within the time specified by the comparison and discrimination features entered in the Big Data Storage Unit 3, the corresponding comparison and discrimination features will be removed. Visitor Frequency Recognition Unit 7: The Visitor Frequency Recognition Unit 7 cooperates with the Central Processing Unit 2 and can record the visitor frequency within a specified time. When the visitor frequency is lower than the set threshold, the facial features recorded in the ID card information are compared by extracting the facial features of the face. When the visitor frequency is higher than the set threshold, the extracted facial determination discrimination features are compared with the comparison and discrimination features. If there are no comparison and discrimination features in the Big Data Storage Unit 3, the method of extracting the facial features of the face is continued.

[0042] This system cooperates with intelligent hardware, such as turnstiles, access control systems, and electric controls, to achieve intelligent management of visitors in schools and enterprises.

[0043] Through intelligent visitor management, a good visiting experience is provided for visitors, while improving security and passage efficiency.

[0044] This application can perform multi-mode reservation and quick verification. The system supports online information entry and offline quick verification, improving the comfort of the visitor experience and reducing property management costs.

[0045] This device can perform custom permission settings. The system allows the visited person to register the visitor's name, phone number, face photo, etc. through a mobile APP, and set the visiting time, access floor, passage area, etc., improving the convenience experience of visitors.

[0046] In the above embodiments, the device components involved are all conventional device components unless otherwise specified. The connection methods and control methods involved are all conventional connection methods and control methods unless otherwise specified.

[0047] The above has described the present invention in detail with reference to the embodiments. However, those skilled in the art can understand that without departing from the purpose of the present invention, various specific parameters in the above embodiments can be changed to form multiple specific embodiments, which are all within the common change range of the present invention and will not be elaborated here one by one.

Claims

1. A visitor access method, characterized in that: include: The visitor stands in front of the face recognition module, which extracts the facial features and places the ID card on the ID card recognition module to identify the ID card information; The central processing unit receives the ID card information and determines whether the big data storage unit performs visitor comparison and distinguishing feature entry; If the visitor's comparison distinguishing features are entered, the facial distinguishing features are directly extracted, and the facial distinguishing features are compared with the comparison distinguishing features. If they are consistent, they are automatically entered according to the previous information entry and released; If the visitor does not enter the distinguishing features, the facial features of the person are extracted and compared with the facial features recorded in the ID card information to determine whether they are consistent. If they are consistent, the visitor enters the information through the system and is released; The visitor comparison distinguishing features are not entered. After the facial features of the face are extracted, the judgment distinguishing features of the extracted facial features are further identified and extracted, and entered into the big data storage unit as comparison distinguishing features for the next comparison and judgment.

2. A visitor access method according to claim 1, characterized in that: The method for extracting the distinguishing features comprises: Collect the visitor's frozen images, extract and judge the features of the visitor's frozen images, such as image brightness, facial blur and facial angle, and select high-quality frozen images as facial feature extraction images through a feature screening algorithm; Extracting distinguishing feature points of a high-quality frozen image by using a distinguishing feature point extraction algorithm, wherein the distinguishing feature points of a human face include small triangular distinguishing features and large triangular distinguishing features of a human face, wherein the small triangular area includes a triangular area connecting the ends of the eye corners and the nose tip, and the large triangular area includes a triangular area where the earlobes and the center point of the mandible are located; The ratio of the three sides of the small triangle area and the large triangle area and the angles of the three corners are identified as the distinguishing feature points of the image.

3. A visitor access method according to claim 2, characterized in that: The process of screening high-quality still images is as follows: establishing a feature coefficient interval, setting a plurality of rows and columns of square grid areas in the feature coefficient space, the image brightness influence coefficients and facial blur influence coefficients corresponding to the intervals where different square grids are located are different, placing the collected still images of the visitors in the square grid intervals, extracting the brightness characteristic values ​​and blur characteristic values, calculating the screening characteristic values, calculating the offset angle of the still images of the visitors based on the reference contour angle, and calculating the screening characteristic values ​​according to the offset angle.

4. A visitor access method according to claim 2, characterized in that: The feature screening algorithm formula is: ， in, To filter feature values, is the number of grid intervals, For the The brightness eigenvalue corresponding to the grid interval, For the The image brightness influence coefficient corresponding to the grid interval, For the The facial fuzziness eigenvalue corresponding to the grid interval, For the The facial fuzziness influence coefficient corresponding to the grid interval, is the base profile angle, Rotate the visitor's face angle. is the visitor's facial angle influence coefficient.

5. A visitor access method according to claim 2, characterized in that The comparison process of the face judgment distinguishing features and the comparison distinguishing features is as follows: in the judgment distinguishing feature entry process, the identified small triangle area and the triangle figures of the large and three small areas and the ratio of the three sides and the angles of the three corners corresponding to the triangle figures are entered. After the judgment distinguishing feature entry is confirmed according to the ID card information, the ratio of the three sides and the angles of the three corners of the small triangle area and the large triangle area on the visitor's face are identified and compared with the judgment distinguishing features. If the similarity exceeds the set threshold, the visitor information is automatically entered and released.

6. A visitor access method according to claim 1, characterized in that: If the contrast and distinction features entered into the big data storage unit are not extracted and compared within a specified time, the corresponding contrast and distinction features will be eliminated.

7. A visitor access method according to claim 6, characterized in that: It also includes identifying the visitor frequency. When the visitor frequency is lower than the set threshold, the facial features of the face are extracted and compared with the facial features recorded in the ID card information. When the visitor frequency is higher than the set threshold, the facial judgment distinguishing features are extracted and compared with the comparison distinguishing features. If there are no comparison distinguishing features in the big data storage unit, the facial features are continued to be extracted.

8. A pass system, applied to the visitor pass method according to any one of claims 1 to 7, characterized in that: include: Visitor information entry unit: The visitor information entry unit can identify and authenticate the visitor's facial information and ID card information, and send the visitor information to the cloud big data storage unit in an encrypted form. Visitors can enter visitor information through the visitor information entry unit; Central processing unit: Built-in system algorithm, can screen the collected faces for high-quality freeze-frame images, can compare and judge the visitors' distinguishing features with the distinguishing features, and can also compare and judge the facial features of the faces with the facial features recorded in the ID card information; Big data storage unit: The big data storage unit stores the visitor comparison and distinction features entered by the system and the entry information of the corresponding visitors.

9. A passage system according to claim 8, characterized in that: Also includes: Access authority management unit: The system can generate an invitation code based on the visitor's reservation information and send it to the visitor's terminal. The visitor uses the invitation code for identity authentication and fast access. Data statistics and query unit: The system supports daily data statistics and query functions to facilitate the management of visitor information and access records.

10. A passage system according to claim 8, characterized in that: Also includes: Expired information elimination unit: the expired information elimination unit cooperates with the big data storage unit, and if the comparison and distinction features entered in the big data storage unit are not extracted and compared within the specified time, the corresponding comparison and distinction features are eliminated; Visitor frequency identification unit: The visitor frequency identification unit cooperates with the central processing unit to record the visitor frequency within a specified time. When the visitor frequency is lower than the set threshold, the facial features of the face are extracted and compared with the facial features recorded in the ID card information. When the visitor frequency is higher than the set threshold, the facial judgment distinguishing features are extracted and compared with the comparison distinguishing features. If there are no comparison distinguishing features in the big data storage unit, the facial features are extracted.

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