Work card false use identification method based on camera identification and UWB indoor positioning technology

Abstract

The invention relates to a work card false use identification method based on camera identification and UWB indoor positioning technology, and the method comprises the steps: deploying a camera and a UWB positioning system in a designated region; recognizing the human face through a camera, and generating a human face recognition result set; personnel are positioned through a UWB positioning system, and a personnel positioning label set is generated; comparing and calculating the difference between the personnel positioning tag set and the face recognition result set within a specific time; according to the method, the camera is used for recognizing the human face, the UWB indoor positioning technology is combined for positioning the personnel, and the difference between the personnel positioning label set and the human face recognition result set is compared and calculated, so that the recognition of the false use of the work card is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of work badge fraud identification, and specifically provides a work badge fraud identification method based on camera recognition and UWB indoor positioning technology. Background Art

[0002] In some workplaces, employees are often required to wear ID badges to ensure safety and management. However, ID badge misuse is a problem, where someone uses another person's ID badge to enter sensitive areas. To address this issue, manual inspections are often used, which can be prone to omissions and requires a lot of work. Summary of the Invention

[0003] The purpose of this section is to summarize some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the abstract and title of this application to avoid obscuring the purpose of this section, the abstract and the title of the invention, and such simplifications or omissions should not be used to limit the scope of the present invention.

[0004] In view of the following technical problems in the prior art: the existing manual inspection method is prone to omissions and is time-consuming and labor-intensive.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for identifying work badge fraud based on camera recognition and UWB indoor positioning technology, comprising:

[0006] Deploy cameras and UWB positioning systems in designated areas;

[0007] Recognize faces through cameras and generate face recognition result sets;

[0008] Use the UWB positioning system to locate personnel and generate a personnel positioning tag set;

[0009] Compare and calculate the difference between the person location label set and the face recognition result set within a specific time;

[0010] Based on the differences, determine the person who has used the location tag to impersonate the work badge.

[0011] As an optimal technical solution for the method of identifying work badge fraud based on camera recognition and UWB indoor positioning technology, the camera uses a deep learning algorithm for face recognition.

[0012] As an optimal technical solution for the method of identifying work badge fraud based on camera recognition and UWB indoor positioning technology, the UWB positioning system realizes personnel positioning by measuring the time delay of ultra-wideband signals.

[0013] As the preferred technical solution for the work badge fraud identification method based on camera recognition and UWB indoor positioning technology, the comparative calculation difference includes calculating the number and duration of tags that exist in the personnel positioning tag set but do not exist in the face recognition result set.

[0014] As the preferred technical solution for the work badge fraud identification method based on camera recognition and UWB indoor positioning technology, the facial image is preprocessed before the comparison calculation, including face detection, facial feature extraction and facial feature matching.

[0015] As an optimal technical solution for the method of identifying work badge fraud based on camera recognition and UWB indoor positioning technology, the personnel labels are preprocessed before the comparison calculation, including personnel label recognition and personnel label feature extraction.

[0016] As an optimal technical solution for the method of identifying work badge fraud based on camera recognition and UWB indoor positioning technology, the UWB positioning system includes an RFID reader and a positioning sensor.

[0017] As an optimal technical solution for the identification method of work badge fraud based on camera recognition and UWB indoor positioning technology, the camera is also equipped with a distance sensor and an angle sensor.

[0018] The beneficial effects of the present invention are as follows: the present invention uses a camera to recognize faces and combines UWB indoor positioning technology to locate personnel. By comparing and calculating the difference between the personnel positioning label set and the face recognition result set, the identification of the fraudulent use of work badges can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort. Among them:

[0020] Figure 1 Schematic diagram of the framework of the identification method of the present invention; DETAILED DESCRIPTION

[0021] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0022] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0023] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0024] Furthermore, the present invention is described in detail with reference to schematic diagrams. For ease of illustration, when describing the embodiments of the present invention, cross-sectional views illustrating device structures may be partially enlarged and not to scale. Furthermore, the schematic diagrams are merely illustrative and should not limit the scope of protection of the present invention. Furthermore, in actual production, the three-dimensional dimensions of length, width, and depth should be included.

[0025] Example 1

[0026] Reference Figure 1 ,This embodiment provides a method for identifying work badge fraud based on camera recognition and UWB indoor positioning technology, including deploying cameras and UWB positioning systems in a designated area;

[0027] Recognize faces through cameras and generate face recognition result sets;

[0028] Use the UWB positioning system to locate personnel and generate a personnel positioning tag set;

[0029] Compare and calculate the difference between the person location label set and the face recognition result set within a specific time;

[0030] Based on the differences, determine the person who has used the location tag to impersonate the work badge.

[0031] It should be noted that the designated area can specifically be a workplace, which is indoors. The UWB positioning system includes multiple positioning base stations arranged indoors, whose radiation range covers the entire designated area, and multiple positioning base stations cooperate with each other to measure distance to achieve the purpose of accurately locating each personnel tag in the room.

[0032] Therefore, the positioning tag set includes the number of tags (corresponding to the number of people) in the specified area, the corresponding person information in the tags, and the location of the tags (personnel) in the specified area.

[0033] The UWB positioning system includes an RFID reader and a positioning sensor.

[0034] Furthermore, the UWB positioning system realizes the positioning of personnel by measuring the time delay of ultra-wideband signals; specifically, base station A sends (or enables the personnel tag to send) and receives Gaussian single-cycle ultra-short-time pulses with strictly controlled pulse intervals through the system's built-in device, and measures the time interval, and further calculates the distance between the personnel tag and base station A. Similarly, the distance between the personnel tag and base station B, base station C, etc. can be known, and then the specific positioning of the personnel tag is calculated based on the positions of base stations A, base station B, base station C, etc. in the specified area.

[0035] Furthermore, multiple cameras are set up in the designated area, and the cameras use deep learning algorithms for face recognition; the cameras are also equipped with distance sensors and angle sensors to confirm and calculate the specific position of the detected person from the camera, and further calculate the specific position of the person captured by the camera based on the position of the camera in the designated area.

[0036] Specifically, before the comparison calculation, the facial image is preprocessed, including face detection, facial feature extraction and facial feature matching, and the information of the staff allowed to enter is recorded to form a facial information data set. Before the comparison calculation, the personnel label is preprocessed, including personnel label recognition and personnel label feature extraction, the data of the facial information data set is entered into the personnel label, and the personnel label is issued to the corresponding personnel and required to wear it; at the same time, relevant cards are set at the entrance of the designated area to detect personnel labels to ensure that all personnel entering the designated area wear personnel labels.

[0037] When the camera performs on-site facial recognition, it will compare it with the facial information dataset. The recorded personal information will be entered into the facial recognition result set, and the unrecorded information will be recorded into the face set with the label "unknown".

[0038] Finally, the personnel information recorded by the on-site tags is compared with the camera recognition information. If there is a personnel tag on the scene, but the corresponding face recognition result is unknown, there is a possibility that the person is using the work badge fraudulently.

[0039] Furthermore, the location of a single person can be carefully checked. Specifically, people at a common location located by both the positioning system and the camera can be identified, and whether the person's label information at that location matches the facial recognition information can be detected.

[0040] The comparison calculation differences include the number and duration of labels that exist in the human positioning label set but not in the face recognition result set.

[0041] By comparing, we can obtain the difference between the positioning label set and the face recognition result set, which is the number of people who have misused the label. By recording the time, we can know the time period of misuse.

[0042] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for identifying counterfeit work badges based on camera recognition and UWB indoor positioning technology, characterized by: include, Deploy cameras and UWB positioning systems in designated areas; Recognize faces through cameras and generate face recognition result sets; Use the UWB positioning system to locate personnel and generate a personnel positioning tag set; Compare and calculate the difference between the person location label set and the face recognition result set within a specific time; Based on the differences, determine the person who has used the location tag to impersonate the work badge.

2. The method for identifying fraudulent use of work badges based on camera recognition and UWB indoor positioning technology according to claim 1 is characterized by: The camera uses a deep learning algorithm to perform face recognition.

3. The method for identifying fraudulent use of work badges based on camera recognition and UWB indoor positioning technology according to claim 2, characterized in that: The UWB positioning system realizes personnel positioning by measuring the time delay of ultra-wideband signals.

4. The method for identifying fraudulent use of work badges based on camera recognition and UWB indoor positioning technology according to claim 3 is characterized by: The comparison calculation differences include the number and duration of labels that exist in the human positioning label set but not in the face recognition result set.

5. The method for identifying fraudulent use of work badges based on camera recognition and UWB indoor positioning technology according to claim 4 is characterized in that: Before the comparison calculation, the face image is preprocessed, including face detection, face feature extraction and face feature matching.

6. The method for identifying fraudulent use of work badges based on camera recognition and UWB indoor positioning technology according to claim 5, characterized in that: Before the comparison calculation, the person labels are preprocessed, including person label recognition and person label feature extraction.

7. The method for identifying fraudulent use of work badges based on camera recognition and UWB indoor positioning technology according to claim 6, characterized in that: The UWB positioning system includes an RFID reader and a positioning sensor.

8. The method for identifying fraudulent use of work badges based on camera recognition and UWB indoor positioning technology according to claim 7, characterized in that: The camera is also provided with a distance sensor and an angle sensor.

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