An intelligent campus access control system

Abstract

The present invention discloses an intelligent campus access control system, which includes: an image detection unit, an image comparison unit and an information output unit; the image detection unit is used to obtain the human appearance image information of the person to be detected, and mark the face image information in the human appearance image information; the image comparison unit is used to perform identity recognition according to the face image information, and perform health status detection according to the human appearance image information; the information output unit is used to sort out and output access control punch-in information according to the identity recognition and health status detection results of the image comparison unit. The health status of the person to be detected is preliminarily evaluated through image processing, and the morning inspection equipment is combined with the access control equipment to improve the intelligence of campus management and the reliability of health management of teachers and students.

Description

Technical Field

[0001] The present invention relates to the technical field of access control equipment, and in particular to an intelligent campus access control system. Background Art

[0002] Schools are places with a large number of people. In order to standardize the management of the entry and exit of relevant personnel in the campus, it is necessary to set up access control systems at various entrances and exits of the campus. Currently, the registration of relevant personnel in the campus is mainly achieved through the automatic recognition of preset identity information or pass cards with access control equipment.

[0003] Since infectious diseases have a great impact on the spread of diseases on campus, the campus management department needs to effectively supervise the health status of people on campus. The current campus access control system has a single function and cannot meet the health management needs of relevant personnel on campus. Therefore, the detection performance of the campus access control system needs to be improved. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art. The present invention provides an intelligent campus access control system, which performs a preliminary assessment of the health status of the person to be inspected through image processing, combines morning inspection equipment with access control equipment, and improves the intelligence of campus management and the reliability of health management of teachers and students.

[0005] The present invention provides an intelligent campus access control system, which includes: an image detection unit, an image comparison unit and an information output unit;

[0006] The image detection unit is used to obtain the human body appearance image information of the person to be detected, and mark the face image information in the human body appearance image information;

[0007] The image comparison unit is used to perform identity recognition based on the face image information, and to perform health status detection based on the human appearance image information;

[0008] The information output unit is used to organize and output access control punch-in information according to the identity recognition and health status detection results of the image comparison unit.

[0009] Furthermore, the image detection unit includes: an infrared detection component and a camera component;

[0010] The infrared detection component and the camera component are arranged in parallel in the same working circuit, and the branch where the infrared detection component is located is connected with the branch where the camera component is located based on a selection switch.

[0011] Furthermore, the camera assembly is provided with a subject recognition module, and subject detection and recognition is performed on the image information acquired by the camera assembly based on the subject recognition module;

[0012] The subject recognition module extracts the subject object in the image based on the distance transformation function.

[0013] Furthermore, the smart campus access control system also includes a data storage unit, which is used to store the human body appearance image information obtained by the image detection unit and the access control punch-in information output by the information output unit.

[0014] Further, the image comparison unit performs data matching in the data storage unit according to the facial image information;

[0015] Obtain the campus class information and identity information of the person to be tested.

[0016] Further, the image comparison unit queries the historical image information recorded in the data storage unit according to the acquired identity information;

[0017] Comparing the historical image information with the human appearance image information of the person to be detected to obtain a first comparison value;

[0018] The standard image information is obtained in the data storage unit, and the standard image information is compared with the human body appearance image information of the person to be detected to obtain a second comparison value.

[0019] Furthermore, the image comparison unit is provided with an analysis component, and the first comparison value and the second comparison value are analyzed and processed based on the analysis component, and health status information of the person to be detected is output.

[0020] Further, a health assessment coefficient of the person to be tested is calculated based on the analysis component, and if the health assessment coefficient is greater than a preset standard threshold, the health status of the person to be tested is marked as abnormal;

[0021] The information output unit outputs corresponding access control punch-in information according to the evaluation result of the health status of the person to be tested, and notifies the corresponding campus administrator.

[0022] Furthermore, the calculation formula of the health assessment coefficient is:

[0023]

[0024] in, is the health assessment coefficient, γ1 is the first comparison value, γ2 is the second comparison value, a and b are weight coefficients.

[0025] Furthermore, the weight coefficient is set according to the experience of the staff. In this embodiment, the weight coefficient a of the first comparison value involved in the smart campus access control system is 0.2, and the weight coefficient b of the second comparison value is 0.5.

[0026] Furthermore, the data storage unit of the smart campus access control system is configured as a local storage, or the data storage unit of the smart campus access control system is configured as a cloud database.

[0027] The present invention provides an intelligent campus access control system, which performs image detection and recognition on persons to be detected, and performs preliminary assessment of the health status of persons to be detected in conjunction with image processing. While managing the entry and exit of relevant personnel on the campus, it can also perform health checks on people entering and leaving the campus, thereby improving the reliability of intelligent management of campus students and health management. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a schematic diagram of the structural connection of the intelligent campus access control system in an embodiment of the present invention;

[0029] Figure 2 Schematic diagram of the circuit structure of the image detection component of the intelligent campus access control system in an embodiment of the present invention;

[0030] Figure 3 It is a flow chart of the access control monitoring method of the intelligent campus access control system in an embodiment of the present invention. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0032] Embodiment 1:

[0033] Figure 1 The structure diagram of the intelligent campus access control system in an embodiment of the present invention is shown, and the intelligent campus access control system comprises: an image detection unit 10, an image comparison unit 20 and an information output unit 30, wherein the image detection unit 10 is used to obtain the human appearance image information of the person to be detected, and mark the face image information in the human appearance image information;

[0034] The image comparison unit 20 is used to perform identity recognition based on the face image information, and to perform health status detection based on the human appearance image information;

[0035] The information output unit 30 is used to organize and output access control punch-in information according to the identity recognition and health status detection results of the image comparison unit 20.

[0036] Specifically, the smart campus access control system can perform facial recognition punch-in for the person to be detected based on the image detection unit 10 and the image comparison unit 20, thereby avoiding direct contact between the person to be detected and the access control device, reducing the risk of pathogens remaining in the access control device, and thus reducing the risk of infectious diseases spreading among the crowd on campus.

[0037] Furthermore, the persons to be tested include students, teachers, campus staff and visitors. Based on the intelligent campus access control system, the persons entering and leaving the campus are registered, and a preliminary assessment of their health status can be performed during the access control clocking-in process, thereby improving the reliability of campus management.

[0038] Specifically, Figure 2 A circuit structure diagram of the image detection component of the intelligent campus access control system in an embodiment of the present invention is shown, wherein the image detection unit 10 comprises: an infrared detection component 11 and a camera component 12, wherein the infrared detection component 11 and the camera component 12 are arranged in parallel in the same working circuit, and the branch where the infrared detection component 11 is located is connected to the branch where the camera component 12 is located based on a selection switch, and the working states of the infrared detection component 11 and the camera component 12 are adjusted based on the selection switch.

[0039] Specifically, the infrared detection component 11 is connected to the selection switch signal, and the selection switch is driven to switch actions based on the trigger signal of the infrared detection component 11, so that the working states of the infrared detection component 11 and the camera component 12 are switched.

[0040] Furthermore, the camera assembly 12 is connected to the selection switch signal, so that the trigger signal of the camera assembly 12 can drive the selection switch to switch the action, thereby switching the working states of the infrared detection assembly 11 and the camera assembly 12.

[0041] Specifically, when the infrared detection component 11 is in a working state, the infrared detection component 11 identifies whether there is a person to be detected in the detection area of ​​the camera component 12 of the intelligent campus access control system. When the person to be detected enters the shooting and detection area of ​​the camera component 12 and the infrared detection component 11 identifies the person to be detected, the infrared detection component 11 sends a trigger signal to the selection switch, so that the selection switch can switch the branch conduction state, so that the branch where the infrared detection component 11 is located is in a disconnected state, and the branch where the camera component 12 is located is in a conducting state, that is, the infrared detection component 11 switches from a working state to a closed state, and the camera component 12 switches from a closed state to a working state.

[0042] Furthermore, when the camera component 12 shoots the detection area of ​​the smart campus access control system, human body detection is performed on the captured image to detect whether there is a person to be detected in the detection area of ​​the smart campus access control system. If not, the camera component 12 can generate a trigger signal and send it to the selection switch, so that the selection switch switches the connectivity state of the working circuit, so that the branch where the infrared detection component 11 is located is in the on state, and the branch where the camera component 12 is located is in the off state, that is, the infrared detection component 11 can be switched to the working state, and the camera component 12 can be switched to the off state.

[0043] Furthermore, by performing linkage control on the camera component 12 and the infrared detection component 11, the infrared detection component 11 can avoid interfering with the shooting and detection work of the camera component 12 during the operation of the camera component 12; at the same time, when the smart campus access control system is in an idle state, the infrared detection component 11 can perform the detection operation of the entry and exit of personnel, avoiding the camera component 12 from being in a working state for a long time, thereby reducing the working loss of the camera component 12, and at the same time can reduce the operating consumption of the smart campus access control system.

[0044] Specifically, the camera component 12 is provided with a subject recognition module, and subject detection and recognition is performed on the image information obtained by the shooting component based on the subject recognition module, so that the camera component 12 can identify the person to be detected in the image, ensuring that the person to be detected exists in the detection area of ​​the smart campus access control system, and at the same time can improve the accuracy of the image detection unit 10 in identifying the person to be detected in the detection area of ​​the smart campus access control system.

[0045] Furthermore, the subject recognition module of the camera component 12 segments the image based on the watershed algorithm, and performs an opening operation on the image taken by the camera component 12, that is, by first corroding the image and then dilating it, the noise in the image is removed through the opening operation, thereby reducing the interference of the environmental noise of the image on the subject recognition.

[0046] The denoised image is morphologically processed to extract the image boundary, and the detection area of ​​the intelligent campus access control system is set so that the detection area satisfies the shooting of the shooting component and reduces the interference of external environmental characteristics on the shooting area. The subject image frame boundary is further limited through morphological processing so that the shooting component can identify the shooting subject in the image, that is, identify the person to be detected in the image.

[0047] Specifically, the subject recognition module extracts the subject object in the image based on the distance transformation function, calculates the distance from any point in the image to the nearest background point based on the distance transformation function cv2.distanceTransform(), and obtains the distance relationship between each pixel point and the background based on the distance transformation function, thereby obtaining the outline of the subject in the image and achieving the effect of extracting the subject.

[0048] Furthermore, based on the relative fixity of the shooting detection position of the smart campus access control system, the image background acquired by the shooting component is relatively fixed, thereby improving the accuracy of subject recognition and extraction by the subject recognition module.

[0049] Specifically, the smart campus access control system also includes a data storage unit 40, which is used to store the human body appearance image information obtained by the image detection unit 10 and the access control punch-in information output by the information output unit 30. The data storage unit 40 is used to record the punch-in information and image detection data of the smart campus access control system.

[0050] The data storage unit 40 stores standard image data, which includes health status image data and pathological image data corresponding to various common diseases. The standard image data covers image data of the skin, oral cavity, eyes, hands and other parts, so that the smart campus access control system can preliminarily identify whether the person to be tested has symptoms such as skin jaundice, conjunctivitis, oral herpes ulcers and skin rashes.

[0051] Specifically, the image comparison unit 20 performs data matching in the data storage unit 40 according to the facial image information to obtain the campus class information and identity information of the person to be detected. The data storage unit 40 stores the relevant identity information and class information of students, teachers and school staff on campus. Based on the facial image information obtained by the shooting component, the facial information of the campus-related personnel stored in the data storage unit 40 can be matched to obtain the identity information and class information of the person to be detected, so as to register the entry and exit of the campus-related personnel.

[0052] Furthermore, the smart campus access control system inputs the identity information and class information of campus-related personnel in advance, so that the data storage unit 40 can record the information of campus-related personnel, thereby meeting the automated and intelligent access management of campus-related personnel.

[0053] Furthermore, for visitors entering the campus for the first time, the visitor's facial information is obtained based on the campus access control system, and the visitor's scheduled visit information is queried based on the visitor's facial information. If the facial information of the person to be tested matches the facial data reserved in the scheduled visit information, the identity authentication of the person to be tested is completed.

[0054] If the visitor's facial information cannot be matched in the smart campus access control system, the smart campus access control system will send a notification message to relevant staff so that campus staff can quickly perform manual intervention to improve the intelligence and reliability of campus management.

[0055] Specifically, the image comparison unit 20 queries the historical image information recorded in the data storage unit 40 according to the acquired identity information. The data storage unit 40 also records the detection image data of campus-related personnel entering and leaving the campus recently, so that the smart campus access control system can archive and record the entry and exit operations of campus-related personnel, so that the smart campus access control system can continuously monitor and observe the physical health status of campus-related personnel.

[0056] Specifically, the historical image information is compared with the human appearance image information of the person to be detected to obtain a first comparison value. The intelligent campus access control system extracts the historical image data corresponding to the person to be detected in the data storage unit 40 based on the human appearance image information obtained by the image detection unit 10, and compares the historical image data with the human appearance image information of the person to be detected to obtain the recent changes in the physical condition of the person to be detected.

[0057] Specifically, the standard image information is obtained from the data storage unit 40, and the standard image information is compared with the human body appearance image information of the person to be detected to obtain a second comparison value. The human body appearance image information is segmented to divide the facial feature image and the hand feature image in the human body appearance image, and the standard image information of the corresponding part is extracted from the standard image information of the data storage unit 40 according to the division of the human body parts.

[0058] Furthermore, the corresponding standard image data in the data storage unit 40 is extracted according to the human body part, the healthy state image data is extracted from the standard image data as the first part of the image, and the pathological image data is extracted from the standard image data as the second part of the image, and the image information is compared and analyzed based on the first part of the image and the second part of the image, which can improve the accuracy of the image comparison unit 20 in recognizing the human body appearance image data.

[0059] Furthermore, by comparing the first part of the image with the human body appearance image information, the difference between the image state of the person to be detected and the standard image of the healthy state is detected, so as to make a preliminary judgment on the appearance state of the person to be detected and mark the body parts.

[0060] Furthermore, based on the marked parts, image data of corresponding parts are extracted from the second part of the image, and the marked parts of the human body appearance image information are screened based on the second part of the image, which can improve the efficiency and accuracy of image detection of the health status of the person to be detected.

[0061] Specifically, the image contrast unit 20 is provided with an analysis component, and the first contrast value and the second contrast value are analyzed and processed based on the analysis component to output the health status information of the person to be detected.

[0062] The analysis component is used to analyze and process the first contrast value and the second contrast value, perform integrated analysis in combination with the first contrast value and the second contrast value, and calculate the health assessment coefficient of the person to be tested based on the analysis component. If the health assessment coefficient is greater than a preset standard threshold, the health status of the person to be tested is marked as abnormal, so that the information output unit 30 can output the corresponding access control punch-in information and notify the corresponding campus administrator so that the campus administrator can efficiently and standardizedly manage the relevant personnel on campus.

[0063] Specifically, the calculation formula of the health assessment coefficient is:

[0064]

[0065] in, is the health assessment coefficient, γ1 is the first comparison value, γ2 is the second comparison value, a and b are weight coefficients.

[0066] Furthermore, the weight coefficient is set according to the experience of the staff. In this embodiment, the weight coefficient a of the first comparison value involved in the smart campus access control system is 0.2, and the weight coefficient b of the second comparison value is 0.5.

[0067] Specifically, the data storage unit 40 of the smart campus access control system can be configured as local storage. Based on the local storage space of the smart campus access control system, the captured image data of the access control system is stored, so that the smart campus access control system can store the access control punch-in information within a week to meet the use needs of the smart campus access control system.

[0068] Furthermore, the data storage unit 40 of the smart campus access control system can be configured as a cloud database, and the access control punching data of the smart campus access control system can be stored in the cloud based on the cloud database, so that the smart campus access control system can store access control punching information for multiple months, thereby improving the traceability of the smart campus access control system and thus improving the management reliability of the campus.

[0069] The embodiment of the present invention provides an intelligent campus access control system, which performs image detection and recognition on the persons to be detected, and conducts a preliminary assessment of the health status of the persons to be detected in conjunction with image processing. While managing the entry and exit of campus-related personnel, it can also perform health checks on the people entering and leaving the campus, thereby improving the reliability of intelligent management of campus students and health management.

[0070] Embodiment 2:

[0071] Figure 3 A flow chart of a method for monitoring access control of an intelligent campus access control system in an embodiment of the present invention is shown. The method for monitoring access control of an intelligent campus access control system includes:

[0072] S11: Obtaining image information of the human body appearance of the person to be detected.

[0073] Specifically, the smart campus access control system is provided with an image detection unit, and the image detection unit includes an infrared detection component and a camera component. When the infrared detection component is in a working state, it identifies whether there is a person to be detected in the detection area of ​​the camera component of the smart campus access control system based on the infrared detection component. When the person to be detected enters the shooting detection area of ​​the camera component and the infrared detection component identifies the person to be detected, the infrared detection component sends a trigger signal to the selection switch, so that the selection switch can switch the branch conduction state, so that the branch where the infrared detection component is located is in a disconnected state, and the branch where the camera component is located is in a conducting state, that is, the infrared detection component is switched from a working state to a closed state, and the camera component is switched from a closed state to a working state.

[0074] Furthermore, the camera assembly is used to photograph the person to be detected to obtain image information of the person's human appearance.

[0075] The camera component is provided with a subject recognition module, and subject detection and recognition is performed on the image information obtained by the shooting component based on the subject recognition module, so that the camera component can identify the person to be detected in the image, ensure that the person to be detected exists in the detection area of ​​the smart campus access control system, and at the same time improve the accuracy of the image detection unit in identifying the person to be detected in the detection area of ​​the smart campus access control system.

[0076] The subject recognition module of the camera component segments the image based on the watershed algorithm and performs an opening operation on the image taken by the camera component, that is, by first corroding and then dilating the image, the noise in the image is removed through the opening operation, thereby reducing the interference of the image's environmental noise on subject recognition.

[0077] The denoised image is morphologically processed to extract the image boundary, and the detection area of ​​the intelligent campus access control system is set so that the detection area satisfies the shooting of the shooting component and reduces the interference of external environmental characteristics on the shooting area. The subject image frame boundary is further limited through morphological processing so that the shooting component can identify the shooting subject in the image, that is, identify the person to be detected in the image.

[0078] Specifically, the subject recognition module extracts the subject object in the image based on the distance transformation function, calculates the distance from any point in the image to the nearest background point based on the distance transformation function cv2.distanceTransform(), and obtains the distance relationship between each pixel point and the background based on the distance transformation function, thereby obtaining the outline of the subject in the image and achieving the effect of extracting the subject.

[0079] Furthermore, based on the relative fixity of the shooting detection position of the smart campus access control system, the image background acquired by the shooting component is relatively fixed, thereby improving the accuracy of subject recognition and extraction by the subject recognition module.

[0080] S12: Determine the identity information of the person to be detected.

[0081] Specifically, a data storage unit and an image comparison unit are provided in the smart campus access control system. The identity information and class information of campus-related personnel are entered into the data storage unit in advance, so that the data storage unit can record the information of campus-related personnel, thereby meeting the automated and intelligent entry and exit management of campus-related personnel.

[0082] The image comparison unit performs data matching in the data storage unit according to the facial image information to obtain the campus class information and identity information of the person to be detected. The data storage unit stores the relevant identity information and class information of students, teachers and school staff on campus. Based on the facial image information obtained by the shooting component, the facial information of the campus-related personnel stored in the data storage unit can be matched to obtain the identity information and class information of the person to be detected, so as to register the entry and exit of the campus-related personnel.

[0083] Furthermore, for visitors entering the campus for the first time, the visitor's facial information is obtained based on the campus access control system, and the visitor's scheduled visit information is queried based on the visitor's facial information. If the facial information of the person to be tested matches the facial data reserved in the scheduled visit information, the identity authentication of the person to be tested is completed.

[0084] If the visitor's facial information cannot be matched in the smart campus access control system, the smart campus access control system will send a notification message to relevant staff so that campus staff can quickly perform manual intervention to improve the intelligence and reliability of campus management.

[0085] S13: Perform image analysis on the image information of the human body appearance.

[0086] Specifically, the image comparison unit queries the historical image information recorded in the data storage unit based on the acquired identity information. The data storage unit also records the detection image data of campus-related personnel entering and leaving the campus recently, so that the smart campus access control system can archive and record the entry and exit operations of campus-related personnel, so that the smart campus access control system can continuously monitor and observe the physical health status of campus-related personnel.

[0087] Specifically, the historical image information is compared with the human appearance image information of the person to be detected to obtain a first comparison value. The intelligent campus access control system extracts the historical image data corresponding to the person to be detected in the data storage unit based on the human appearance image information obtained by the image detection unit, and compares the historical image data with the human appearance image information of the person to be detected to obtain the recent changes in the physical condition of the person to be detected.

[0088] Furthermore, based on the comparison between the historical image data of the person to be detected and the image information of the human body appearance of the person to be detected, the difference positions of the two groups of images are obtained and converted into the difference rate of the two groups of images as the first comparison value.

[0089] Specifically, the standard image information is obtained from the data storage unit, and the standard image information is compared with the human body appearance image information of the person to be detected to obtain a second comparison value. The human body appearance image information is segmented to divide the facial feature image and the hand feature image in the human body appearance image, and the standard image information of the corresponding part is extracted from the standard image information of the data storage unit according to the division of the human body parts.

[0090] Furthermore, based on the comparison between the standard image information and the human body appearance image information, a difference value between the two is obtained, thereby obtaining the second comparison value.

[0091] Furthermore, the corresponding standard image data in the data storage unit is extracted according to the human body part, the healthy state image data is extracted from the standard image data as the first part of the image, and the pathological image data is extracted from the standard image data as the second part of the image, and the image information is compared and analyzed based on the first part of the image and the second part of the image, which can improve the accuracy of the image comparison unit in recognizing the human body appearance image data.

[0092] Furthermore, by comparing the first part of the image with the human body appearance image information, the difference between the image state of the person to be detected and the standard image of the healthy state is detected, so as to make a preliminary judgment on the appearance state of the person to be detected and mark the body parts.

[0093] Furthermore, based on the marked parts, image data of corresponding parts are extracted from the second part of the image, and the marked parts of the human body appearance image information are screened based on the second part of the image, which can improve the efficiency and accuracy of image detection of the health status of the person to be detected.

[0094] Specifically, the image comparison unit is provided with an analysis component, and the first comparison value and the second comparison value are analyzed and processed based on the analysis component to output the health status information of the person to be detected.

[0095] The analysis component is used to analyze and process the first contrast value and the second contrast value, perform integrated analysis in combination with the first contrast value and the second contrast value, and calculate the health assessment coefficient of the person to be tested based on the analysis component. If the health assessment coefficient is greater than a preset standard threshold, the health status of the person to be tested is marked as abnormal, so that the information output unit can output the corresponding access control punch-in information and notify the corresponding campus administrator so that the campus administrator can conduct efficient and standardized management of the relevant personnel on campus.

[0096] Specifically, the calculation formula of the health assessment coefficient is:

[0097]

[0098] in, is the health assessment coefficient, γ1 is the first comparison value, γ2 is the second comparison value, a and b are weight coefficients.

[0099] Furthermore, the weight coefficient is set according to the experience of the staff. In this embodiment, the weight coefficient a of the first comparison value involved in the smart campus access control system is 0.2, and the weight coefficient b of the second comparison value is 0.5.

[0100] S14: Output access control punch-in information.

[0101] The smart campus access control system also includes an information output unit, which generates access control punch-in information in combination with the identity information and the health assessment coefficient of the person to be detected, and outputs the access control punch-in information based on the information output unit.

[0102] The embodiment of the present invention provides an intelligent campus access control system, which performs image detection and recognition on the persons to be detected, and conducts a preliminary assessment of the health status of the persons to be detected in conjunction with image processing. While managing the entry and exit of campus-related personnel, it can also perform health checks on the people entering and leaving the campus, thereby improving the reliability of intelligent management of campus students and health management.

[0103] In addition, the embodiments of the present invention are described in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. An intelligent campus access control system, characterized in that: The intelligent campus access control system comprises: an image detection unit, an image comparison unit and an information output unit; The image detection unit is used to obtain the human body appearance image information of the person to be detected, and mark the face image information in the human body appearance image information; The image comparison unit is used to perform identity recognition based on the face image information, and to perform health status detection based on the human appearance image information; The information output unit is used to organize and output access control punch-in information according to the identity recognition and health status detection results of the image comparison unit.

2. The intelligent campus access control system according to claim 1, characterized in that: The image detection unit includes: an infrared detection component and a camera component; The infrared detection component and the camera component are arranged in parallel in the same working circuit, and the branch where the infrared detection component is located is connected with the branch where the camera component is located based on a selection switch.

3. The intelligent campus access control system as claimed in claim 2, characterized in that: The camera assembly is provided with a subject recognition module, and subject detection and recognition is performed on the image information acquired by the camera assembly based on the subject recognition module; The subject recognition module extracts the subject object in the image based on the distance transformation function.

4. The intelligent campus access control system as claimed in claim 1, characterized in that: The smart campus access control system also includes a data storage unit, which is used to store the human appearance image information obtained by the image detection unit and the access control punch-in information output by the information output unit.

5. The intelligent campus access control system as claimed in claim 4, characterized in that: The image comparison unit performs data matching in the data storage unit according to the facial image information; Obtain the campus class information and identity information of the person to be tested.

6. The intelligent campus access control system as claimed in claim 5, characterized in that: The image comparison unit queries the historical image information recorded in the data storage unit according to the acquired identity information; Comparing the historical image information with the human appearance image information of the person to be detected to obtain a first comparison value; The standard image information is obtained in the data storage unit, and the standard image information is compared with the human body appearance image information of the person to be detected to obtain a second comparison value.

7. The intelligent campus access control system as claimed in claim 6, characterized in that: The image contrast unit is provided with an analysis component, based on which the first contrast value and the second contrast value are analyzed and processed, and health status information of the person to be detected is output.

8. The intelligent campus access control system as claimed in claim 7, characterized in that: Calculating the health assessment coefficient of the person to be tested based on the analysis component, and if the health assessment coefficient is greater than a preset standard threshold, marking the health status of the person to be tested as abnormal; The information output unit outputs corresponding access control punch-in information according to the evaluation result of the health status of the person to be tested, and notifies the corresponding campus administrator.

9. The intelligent campus access control system as claimed in claim 8, characterized in that: The calculation formula of the health assessment coefficient is: in, is the health assessment coefficient, γ1 is the first comparison value, γ2 is the second comparison value, a and b are weight coefficients. Furthermore, the weight coefficient is set according to the experience of the staff. In this embodiment, the weight coefficient a of the first comparison value involved in the smart campus access control system is 0.2, and the weight coefficient b of the second comparison value is 0.

5.

10. The intelligent campus access control system according to claim 1, characterized in that: The data storage unit of the smart campus access control system is configured as a local storage, or the data storage unit of the smart campus access control system is configured as a cloud database.

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