Personnel information detection method, system and electronic equipment applied to industrial Internet

Abstract

The present application provides a personnel information detection method, device, computer-readable medium and electronic device applied to the industrial Internet. The personnel information detection method applied to the industrial Internet includes: obtaining a facial image of the person to be inspected, detecting the facial image to determine the area ratio of the area corresponding to the facial image to the entire facial area, if the area ratio is greater than or equal to a set threshold, then performing image enhancement on the facial image to obtain an enhanced image, performing feature extraction on the enhanced image to obtain the facial features of the person to be inspected, comparing the facial features with pre-stored features in the database, and determining the identity information of the person to be inspected. By automatically obtaining the facial image of the person and performing face detection on the image to determine the identity information of the person, the automation efficiency and accuracy of identity detection are improved, thereby improving the operating efficiency of the industrial Internet.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and more specifically, to a personnel information detection method, device, computer-readable medium, and electronic device applied to the industrial Internet. Background Art

[0002] Industrial production processes often require identity verification at each entrance to authenticate personnel and manage their identities. With the development of the Industrial Internet, many personnel verification methods rely solely on physical methods like swiping cards. This approach is inefficient and costly, making it difficult to implement rigorous data and identity management, thus impacting normal industrial production. Summary of the Invention

[0003] The embodiments of the present application provide a personnel information detection method, device, computer-readable medium and electronic device applied to the industrial Internet, which can improve the accuracy of personnel information detection at least to a certain extent.

[0004] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by practice of the present application.

[0005] According to one aspect of the present application, a personnel information detection method applied to the industrial Internet is provided, comprising:

[0006] Obtaining a facial image of the person to be inspected;

[0007] Detecting the facial image to determine the ratio of the area corresponding to the facial image to the entire facial area;

[0008] If the area ratio is greater than or equal to a set threshold, performing image enhancement on the facial image to obtain an enhanced image;

[0009] Performing feature extraction on the enhanced image to obtain facial features of the person to be examined;

[0010] The facial features are compared with pre-stored features in a database to determine the identity information of the person to be inspected.

[0011] In the present application, based on the aforementioned solution, the acquisition of facial images of the person to be inspected includes: in an industrial Internet environment, based on a collection device preset at each gate, collecting facial images of the person to be inspected.

[0012] In the present application, based on the aforementioned scheme, the facial image is detected to determine the area ratio of the area corresponding to the facial image to the entire facial area, including: performing grayscale processing on the facial image to generate a grayscale image; extracting edge information in the grayscale image, and determining the area of ​​a first region corresponding to the facial image based on the edge information; predicting the area of ​​a second region not presented in the facial image based on the edge information; and determining the area ratio of the area corresponding to the facial image to the entire facial area based on the area of ​​the first region and the area of ​​the second region.

[0013] In the present application, based on the aforementioned scheme, the extraction of edge information in the grayscale image includes: detecting and extracting pixel information in the grayscale image; calculating the pixel difference parameter between the pixel point and its neighboring pixel points; and taking the information of the pixel point corresponding to the pixel difference parameter being greater than or equal to the difference threshold as the edge information.

[0014] In the present application, based on the aforementioned scheme, if the area ratio is greater than or equal to a set threshold, the facial image is enhanced to obtain an enhanced image, including: if the area ratio is greater than or equal to the set threshold, the grayscale mean and image parameters are determined based on the grayscale values ​​corresponding to each pixel in the grayscale image; the area in the grayscale image whose grayscale value is greater than or equal to the grayscale mean is detected as the target area; and the part of the facial image corresponding to the target area is enhanced based on the image parameters to obtain an enhanced image.

[0015] In the present application, based on the aforementioned scheme, the feature extraction of the enhanced image to obtain the facial features of the person to be examined includes: detecting feature points in the enhanced image, and extracting parameters between the feature points as the facial features of the person to be examined.

[0016] In the present application, based on the aforementioned solution, the method further includes: based on the location information of the image acquisition device and the identity information, identifying whether the person to be inspected has the authority to enter.

[0017] According to one aspect of the present application, a personnel information detection system for industrial Internet is provided, comprising:

[0018] An acquisition unit, used for acquiring a facial image of the person to be inspected;

[0019] a ratio unit, configured to detect the facial image and determine the ratio of the area corresponding to the facial image to the entire facial area;

[0020] an enhancement unit, configured to perform image enhancement on the facial image to obtain an enhanced image if the area ratio is greater than or equal to a set threshold;

[0021] A feature unit, configured to extract features from the enhanced image to obtain facial features of the person to be examined;

[0022] The comparison unit is used to compare the facial features with pre-stored features in the database to determine the identity information of the person to be examined.

[0023] In the present application, based on the aforementioned solution, the acquisition of facial images of the person to be inspected includes: in an industrial Internet environment, based on a collection device preset at each gate, collecting facial images of the person to be inspected.

[0024] In the present application, based on the aforementioned scheme, the facial image is detected to determine the area ratio of the area corresponding to the facial image to the entire facial area, including: performing grayscale processing on the facial image to generate a grayscale image; extracting edge information in the grayscale image, and determining the area of ​​a first region corresponding to the facial image based on the edge information; predicting the area of ​​a second region not presented in the facial image based on the edge information; and determining the area ratio of the area corresponding to the facial image to the entire facial area based on the area of ​​the first region and the area of ​​the second region.

[0025] In the present application, based on the aforementioned scheme, the extraction of edge information in the grayscale image includes: detecting and extracting pixel information in the grayscale image; calculating the pixel difference parameter between the pixel point and its neighboring pixel points; and taking the information of the pixel point corresponding to the pixel difference parameter being greater than or equal to the difference threshold as the edge information.

[0026] In the present application, based on the aforementioned scheme, if the area ratio is greater than or equal to a set threshold, the facial image is enhanced to obtain an enhanced image, including: if the area ratio is greater than or equal to the set threshold, the grayscale mean and image parameters are determined based on the grayscale values ​​corresponding to each pixel in the grayscale image; the area in the grayscale image whose grayscale value is greater than or equal to the grayscale mean is detected as the target area; and the part of the facial image corresponding to the target area is enhanced based on the image parameters to obtain an enhanced image.

[0027] In the present application, based on the aforementioned scheme, the feature extraction of the enhanced image to obtain the facial features of the person to be examined includes: detecting feature points in the enhanced image, and extracting parameters between the feature points as the facial features of the person to be examined.

[0028] In the present application, based on the aforementioned solution, the method further includes: based on the location information of the image acquisition device and the identity information, identifying whether the person to be inspected has the authority to enter.

[0029] According to one aspect of the present application, a computer-readable medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the personnel information detection method applied to the industrial Internet as described in the above embodiment is implemented.

[0030] According to one aspect of the present application, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the personnel information detection method applied to the industrial Internet as described in the above embodiments.

[0031] According to one aspect of the present application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the personnel information detection method for the Industrial Internet provided in any of the aforementioned optional implementations.

[0032] In the technical solution of the present application, a facial image of the person to be inspected is obtained, and the facial image is detected to determine the area ratio of the area corresponding to the facial image to the entire facial area. If the area ratio is greater than or equal to a set threshold, the facial image is enhanced to obtain an enhanced image, and the enhanced image is subjected to feature extraction to obtain the facial features of the person to be inspected. The facial features are compared with pre-stored features in a database to determine the identity information of the person to be inspected. By automatically obtaining a facial image of a person and performing face detection on the image to determine the identity information of the person, the automation efficiency and accuracy of identity detection are improved, thereby improving the operating efficiency of the Industrial Internet.

[0033] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The accompanying drawings are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and those skilled in the art can derive other drawings based on these drawings without inventive effort.

[0035] Figure 1 A flowchart of a personnel information detection method applied to the industrial Internet according to an embodiment of the present application is schematically shown.

[0036] Figure 2 The flowchart of determining the area ratio according to one embodiment of the present application is schematically shown.

[0037] Figure 3 A schematic diagram of a personnel information detection system applied to the industrial Internet according to an embodiment of the present application is schematically shown.

[0038] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing an electronic device according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0039] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art.

[0040] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner.In the following description, many specific details are provided so as to provide a full understanding of the embodiments of the present application. However, it will be appreciated by those skilled in the art that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps etc. can be adopted. In other cases, known methods, devices, implementations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0041] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0042] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, while others may be combined or partially combined. Therefore, the actual execution order may vary depending on the actual situation.

[0043] The following is a detailed description of the implementation details of the technical solution of the embodiment of the present application:

[0044] Figure 1 The flowchart of the personnel information detection method applied to the industrial Internet according to one embodiment of the present application is shown. Figure 1As shown, the personnel information detection method applied to the industrial Internet includes at least steps S110 to S150, which are described in detail as follows:

[0045] In step S110, a facial image of the person to be inspected is acquired.

[0046] In the industrial Internet environment, collection devices are pre-installed at each gate and entrance to collect facial images of people to be inspected.

[0047] The acquisition device in this embodiment can be a sensor such as a camera.

[0048] In step S120, the facial image is detected to determine the area ratio of the area corresponding to the facial image to the entire facial area.

[0049] In one embodiment of the present application, after the facial image is acquired, the facial image is detected to determine the area corresponding to the facial image, and to determine the area ratio of the area to the entire facial area.

[0050] It should be noted that the full facial area in this embodiment refers to the area in the image corresponding to the entire face of the person to be examined.

[0051] In one embodiment of the present application, Figure 2 As shown, detecting the facial image and determining the area ratio of the area corresponding to the facial image to the entire facial area includes:

[0052] S210, performing grayscale processing on the facial image to generate a grayscale image;

[0053] S220, extracting edge information from the grayscale image, and determining an area of ​​a first region corresponding to the facial image based on the edge information;

[0054] S230, predicting an area of ​​a second region not present in the facial image based on the edge information;

[0055] S240: Determine, based on the area of ​​the first region and the area of ​​the second region, the area ratio of the region corresponding to the facial image to the entire facial region.

[0056] In one embodiment of the present application, extracting edge information from the grayscale image includes: detecting and extracting pixel information from the grayscale image; calculating a pixel difference parameter between a pixel point and its neighboring pixel points; and using information of the pixel point corresponding to when the pixel difference parameter is greater than or equal to a difference threshold as the edge information.

[0057] In one embodiment of the present application, a facial image is grayscale processed to generate a grayscale image corresponding to the facial image. Subsequently, edge information in the grayscale image is detected and extracted by traversing the grayscale values ​​Pix_vau corresponding to pixels in the grayscale image and the grayscale values ​​Pix_ne_i corresponding to the pixel's neighboring pixels, and calculating the pixel difference parameter Per_i between the pixel and its neighboring pixels as follows:

[0058]

[0059] Where i represents the identifier of a neighboring pixel, and there are k neighboring pixels in total. After calculating the pixel difference parameter, the information of the corresponding pixels when the pixel difference parameter is greater than or equal to the difference threshold is used as edge information. The area of ​​the region defined by the edge is then determined as the area of ​​the first region corresponding to the facial image.

[0060] After determining the edge information, the missing portion of the facial image is predicted based on the edge information to determine the area of ​​the second region not present in the facial image. The prediction method in this embodiment can be to train a prediction model based on historical images to construct a prediction model, and then determine the region not present in the facial image and the corresponding area of ​​the second region based on the prediction model.

[0061] After determining the area of ​​the first region and the area of ​​the second region, the sum is taken to determine the total facial area, and then the quotient between the area of ​​the first region and the total facial area is calculated as the area ratio of the area corresponding to the facial image to the entire facial area.

[0062] In step S130, if the area ratio is greater than or equal to a set threshold, image enhancement is performed on the facial image to obtain an enhanced image.

[0063] In one embodiment of the present application, if the area ratio is greater than or equal to a set threshold, performing image enhancement on the facial image to obtain an enhanced image includes:

[0064] If the area ratio is greater than or equal to a set threshold, determining a grayscale mean and image parameters based on the grayscale value corresponding to each pixel in the grayscale image;

[0065] Detecting an area in the grayscale image where the grayscale value is greater than or equal to the grayscale mean as a target area;

[0066] Image enhancement is performed on a portion of the facial image corresponding to the target area based on the image parameters to obtain an enhanced image.

[0067] In one embodiment of the present application, after calculating the area ratio, if the area ratio is greater than or equal to a set threshold, it means that a relatively complete face image has been captured. Then, based on the grayscale value corresponding to each pixel in the grayscale image, the grayscale mean value Ave_vau is determined as:

[0068]

[0069] Where n represents the pixel ID, and there are m pixels in total. In this embodiment, the grayscale mean is calculated to determine the pixel levels in the grayscale image. After calculating the grayscale mean, regions in the grayscale image with grayscale values ​​greater than or equal to the grayscale mean are detected as target regions, and targeted enhancement processing is performed on the target regions to improve image contrast.

[0070] Based on the grayscale value corresponding to each pixel in the grayscale image, the image parameter Par_ena is determined as:

[0071]

[0072] Wherein, α represents a preset image factor. The image parameters are calculated by the grayscale value of the image. The image parameters are used to enhance the pixel values ​​in the target area, and the corresponding enhanced pixel values ​​are obtained as follows:

[0073] Ave_ena_n=(1+Par_ena)·Pix_vau_

[0074] After image enhancement is performed on the target area to obtain corresponding enhanced pixel values, an enhanced image is generated based on the pixel values ​​corresponding to the non-target area and the enhanced pixel values ​​corresponding to the target area.

[0075] In step S140, feature extraction is performed on the enhanced image to obtain facial features of the person to be examined.

[0076] In one embodiment of the present application, after generating an enhanced image, feature points in the enhanced image are detected, such as pixels corresponding to features such as the corners of the eyes and mouth, and their positions. Parameters between the feature points, such as distance and distance ratio, are extracted as facial features of the person to be examined.

[0077] In step S150, the facial features are compared with pre-stored features in a database to determine the identity information of the person to be inspected.

[0078] In one embodiment of the present application, pre-stored features of each person are pre-stored in the database. After the facial features are extracted, the above facial features are compared with the predicted special diagnosis, for example, the similarity between the features is calculated to determine the identity information of the person to be examined.

[0079] In the technical solution of the present application, a facial image of the person to be inspected is obtained, and the facial image is detected to determine the area ratio of the area corresponding to the facial image to the entire facial area. If the area ratio is greater than or equal to a set threshold, the facial image is enhanced to obtain an enhanced image, and the enhanced image is subjected to feature extraction to obtain the facial features of the person to be inspected. The facial features are compared with pre-stored features in a database to determine the identity information of the person to be inspected. By automatically obtaining a facial image of a person and performing face detection on the image to determine the identity information of the person, the automation efficiency and accuracy of identity detection are improved, thereby improving the operating efficiency of the Industrial Internet.

[0080] The following describes an embodiment of the device of the present application, which can be used to execute the personnel information detection method applied to the industrial Internet in the above-mentioned embodiment of the present application. It can be understood that the device can be a computer program (including program code) running on a computer device, for example, the device is an application software; the device can be used to execute the corresponding steps in the method provided in the embodiment of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the personnel information detection method applied to the industrial Internet in the above-mentioned embodiment of the present application.

[0081] Figure 3 A block diagram of a personnel information detection system applied to the industrial Internet according to an embodiment of the present application is shown.

[0082] Reference Figure 3 As shown, a personnel information detection system applied to the industrial Internet according to one embodiment of the present application includes:

[0083] An acquisition unit 310 is configured to acquire a facial image of a person to be examined;

[0084] A ratio unit 320 is used to detect the facial image and determine the ratio of the area corresponding to the facial image to the entire facial area;

[0085] an enhancing unit 330 configured to perform image enhancement on the facial image to obtain an enhanced image if the area ratio is greater than or equal to a set threshold;

[0086] A feature unit 340 is used to extract features from the enhanced image to obtain facial features of the person to be examined;

[0087] The comparison unit 350 is used to compare the facial features with pre-stored features in the database to determine the identity information of the person to be examined.

[0088] In the present application, based on the aforementioned solution, the acquisition of facial images of the person to be inspected includes: in an industrial Internet environment, based on a collection device preset at each gate, collecting facial images of the person to be inspected.

[0089] In the present application, based on the aforementioned scheme, the facial image is detected to determine the area ratio of the area corresponding to the facial image to the entire facial area, including: performing grayscale processing on the facial image to generate a grayscale image; extracting edge information in the grayscale image, and determining the area of ​​a first region corresponding to the facial image based on the edge information; predicting the area of ​​a second region not presented in the facial image based on the edge information; and determining the area ratio of the area corresponding to the facial image to the entire facial area based on the area of ​​the first region and the area of ​​the second region.

[0090] In the present application, based on the aforementioned scheme, the extraction of edge information in the grayscale image includes: detecting and extracting pixel information in the grayscale image; calculating the pixel difference parameter between the pixel point and its neighboring pixel points; and taking the information of the pixel point corresponding to the pixel difference parameter being greater than or equal to the difference threshold as the edge information.

[0091] In the present application, based on the aforementioned scheme, if the area ratio is greater than or equal to a set threshold, the facial image is enhanced to obtain an enhanced image, including: if the area ratio is greater than or equal to the set threshold, the grayscale mean and image parameters are determined based on the grayscale values ​​corresponding to each pixel in the grayscale image; the area in the grayscale image whose grayscale value is greater than or equal to the grayscale mean is detected as the target area; and the part of the facial image corresponding to the target area is enhanced based on the image parameters to obtain an enhanced image.

[0092] In the present application, based on the aforementioned scheme, the feature extraction of the enhanced image to obtain the facial features of the person to be examined includes: detecting feature points in the enhanced image, and extracting parameters between the feature points as the facial features of the person to be examined.

[0093] In the present application, based on the aforementioned solution, the method further includes: based on the location information of the image acquisition device and the identity information, identifying whether the person to be inspected has the authority to enter.

[0094] In the technical solution of the present application, a facial image of the person to be inspected is obtained, and the facial image is detected to determine the area ratio of the area corresponding to the facial image to the entire facial area. If the area ratio is greater than or equal to a set threshold, the facial image is enhanced to obtain an enhanced image, and the enhanced image is subjected to feature extraction to obtain the facial features of the person to be inspected. The facial features are compared with pre-stored features in a database to determine the identity information of the person to be inspected. By automatically obtaining a facial image of a person and performing face detection on the image to determine the identity information of the person, the automation efficiency and accuracy of identity detection are improved, thereby improving the operating efficiency of the Industrial Internet.

[0095] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing an electronic device according to an embodiment of the present application is shown.

[0096] It should be noted that Figure 4 The computer system 400 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0097] like Figure 4 As shown, the computer system 400 includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 402 or the program loaded from the storage part 408 into the random access memory (RAM) 403, such as executing the method described in the above embodiment. Various programs and data required for system operation are also stored in the RAM 403. The CPU 401, ROM 402 and RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0098] The following components are connected to the I / O interface 405: an input section 406 including a keyboard, a mouse, and the like; an output section 407 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 408 including a hard disk and the like; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. Removable media 411, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 410 as needed, so that computer programs read therefrom can be installed into the storage section 408 as needed.

[0099] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 409, and / or installed from a removable medium 411. When the computer program is executed by the central processing unit (CPU) 401, the various functions defined in the system of the present application are executed.

[0100] It should be noted that the computer-readable medium shown in the embodiments of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable computer program. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0101] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0102] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. In some cases, the names of these units do not constitute limitations on the units themselves.

[0103] According to one aspect of the present application, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in the various optional implementations described above.

[0104] As another aspect, the present application further provides a computer-readable medium, which may be included in the electronic device described in the above embodiments, or may exist independently without being incorporated into the electronic device. The computer-readable medium carries one or more programs, and when the one or more programs are executed by the electronic device, the electronic device implements the method described in the above embodiments.

[0105] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiment of the application, the features and functions of two or more modules or units described above can be concretized in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be concretized.

[0106] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present application.

[0107] Those skilled in the art will readily conceive of other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present application that follow the general principles of this application and include common knowledge or customary techniques in the art that are not disclosed herein.

[0108] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A personnel information detection method applied to the industrial Internet, characterized in that: include: Obtaining a facial image of the person to be inspected; Detecting the facial image to determine the ratio of the area corresponding to the facial image to the entire facial area; If the area ratio is greater than or equal to a set threshold, performing image enhancement on the facial image to obtain an enhanced image; Performing feature extraction on the enhanced image to obtain facial features of the person to be examined; Comparing the facial features with pre-stored features in a database to determine the identity information of the person to be inspected; The step of obtaining a facial image of the person to be inspected includes: In the industrial Internet environment, facial images of people to be inspected are collected based on the collection devices preset at each gate; Detecting the facial image to determine the ratio of the area corresponding to the facial image to the entire facial area includes: Performing grayscale processing on the facial image to generate a grayscale image; extracting edge information from the grayscale image, and determining an area of ​​a first region corresponding to the facial image based on the edge information; predicting an area of ​​a second region not present in the facial image based on the edge information; Determining, based on the area of ​​the first region and the area of ​​the second region, a ratio of the area corresponding to the facial image to the entire facial area; The extracting edge information from the grayscale image includes: Detect and extract pixel information from grayscale images; Calculate the pixel difference parameter between a pixel and its neighboring pixels; The information of the pixel points corresponding to when the pixel difference parameter is greater than or equal to the difference threshold is used as the edge information.

2. The method according to claim 1, characterized in that If the area ratio is greater than or equal to a set threshold, performing image enhancement on the facial image to obtain an enhanced image includes: If the area ratio is greater than or equal to a set threshold, determining a grayscale mean and image parameters based on the grayscale value corresponding to each pixel in the grayscale image; Detecting an area in the grayscale image where the grayscale value is greater than or equal to the grayscale mean as a target area; Image enhancement is performed on a portion of the facial image corresponding to the target area based on the image parameters to obtain an enhanced image.

3. The method according to claim 1, characterized in that Performing feature extraction on the enhanced image to obtain facial features of the person to be examined includes: Feature points in the enhanced image are detected, and parameters between the feature points are extracted as facial features of the person to be examined.

4. The method according to claim 1, wherein The method further comprises: Based on the position information of the image acquisition device and the identity information, it is determined whether the person to be inspected has the right to enter.

5. A personnel information detection system applied to the industrial Internet, characterized in that: include: An acquisition unit is configured to acquire a facial image of the person to be inspected; the acquisition of the facial image of the person to be inspected comprises: in the industrial Internet environment, based on a preset acquisition device at each gate, acquiring the facial image of the person to be inspected; a ratio unit, configured to detect the facial image and determine the ratio of the area corresponding to the facial image to the entire facial area; the detecting the facial image and determining the ratio of the area corresponding to the facial image to the entire facial area comprises: performing grayscale processing on the facial image to generate a grayscale image; extracting edge information from the grayscale image and determining the area of ​​a first area corresponding to the facial image based on the edge information; predicting the area of ​​a second area not present in the facial image based on the edge information; and determining the ratio of the area corresponding to the facial image to the entire facial area based on the area of ​​the first area and the area of ​​the second area; the extracting edge information from the grayscale image comprises: detecting and extracting pixel information from the grayscale image; Calculating a pixel difference parameter between a pixel point and its neighboring pixel points; and using information of the pixel point corresponding to when the pixel difference parameter is greater than or equal to a difference threshold as the edge information; an enhancement unit, configured to perform image enhancement on the facial image to obtain an enhanced image if the area ratio is greater than or equal to a set threshold; A feature unit, configured to extract features from the enhanced image to obtain facial features of the person to be examined; The comparison unit is used to compare the facial features with pre-stored features in the database to determine the identity information of the person to be examined.

6. A computer-readable medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the personnel information detection method applied to the industrial Internet as described in any one of claims 1 to 4 is implemented.

7. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the one or more processors to implement the personnel information detection method applied to the industrial Internet as described in any one of claims 1 to 4.

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