A substation management identification method and system based on face recognition

Abstract

The application provides a substation management identification method and system based on face recognition; wherein the method comprises: acquiring a first image of a verification area, obtaining first feature data of a person to be verified according to the first image; performing first matching processing on the first feature data, determining a face recognition scheme according to the result of the first matching processing; acquiring a second image of the verification area, obtaining second feature data of the person to be verified from the second image according to the face recognition scheme; performing second matching processing on the second feature data, obtaining a face recognition result according to the result of the second matching processing; and determining a release decision according to the face recognition result. The scheme of the application improves the automation level of substation personnel management on one hand, and can also determine the best face recognition scheme during the process that the person to be verified gradually approaches the verification point, thereby significantly improving the efficiency of face recognition.

Description

Technical Field

[0001] This invention relates to the field of personnel management technology, and more specifically, to a substation management identification method, system, electronic device, and computer storage medium based on facial recognition. Background Technology

[0002] A substation is a location where voltage is changed. To transmit electricity generated by a power plant to distant locations, the voltage must be increased to high voltage, and then reduced as needed near the user. This voltage adjustment process is performed by substations. Substations can be mainly classified as: hub substations, terminal substations; step-up substations, step-down substations; power system substations, industrial and mining substations, railway substations (25kV, 50Hz); substations with voltage levels of 500kV, 330kV, 220kV, 110kV, 66kV, 35kV, 10kV, and 6.3kV; 10kV switching stations; and prefabricated substations. Regardless of the type, substations house numerous high-voltage electrical devices, posing a high degree of danger and requiring highly specialized operation skills.

[0003] However, existing substations lack effective management of personnel entering the working area of ​​substation electrical equipment, and mainly rely on manual management of personnel entry and exit, which poses significant safety hazards and urgently needs improvement. Summary of the Invention

[0004] In order to at least solve the technical problems existing in the background art, the present invention provides a substation management identification method, system, electronic device and computer storage medium based on face recognition.

[0005] The first aspect of the present invention provides a substation management identification method based on face recognition, comprising the following steps:

[0006] Acquire the first image of the verification area, and extract the first feature data of the person to be verified based on the first image;

[0007] Perform a first matching process on the first feature data, and determine a face recognition scheme based on the result of the first matching process;

[0008] A second image of the verification area is acquired, and the second feature data of the person to be verified is extracted from the second image according to the face recognition scheme.

[0009] The second feature data is subjected to a second matching process, and the face recognition result is obtained based on the result of the second matching process.

[0010] The decision to allow passage is made based on the facial recognition results;

[0011] The first image is a distant view, and the second image is a close-up view.

[0012] Further, the step of performing a first matching process on the first feature data and determining a face recognition scheme based on the result of the first matching process includes:

[0013] The first feature data and the pre-stored template data are compared for similarity. If there is pre-stored template data with similarity greater than or equal to a threshold, the face recognition scheme is determined according to the first level of refinement; otherwise, the face recognition scheme is determined according to the second level of refinement.

[0014] The first level of precision is lower than the second level of precision.

[0015] Further, determining the face recognition scheme based on the first level of precision includes:

[0016] The number of pre-stored template data with similarity greater than or equal to a threshold is determined, and the first level of precision is determined based on the number; wherein, the first level of precision is positively correlated with the number.

[0017] The face recognition scheme is determined based on the first level of precision.

[0018] Further, acquiring the second image of the verification area includes:

[0019] Based on the first image, third feature data related to the motion state of the person to be verified is extracted;

[0020] The set time period is calculated based on the third feature data, and the second image of the verification area is acquired within the set time period.

[0021] Further, acquiring the second image within the set time period includes:

[0022] Acquire a set number of third images within the set time period;

[0023] A fourth image that meets the set conditions is selected from the set number of third images, and the fourth image is used as the second image;

[0024] The setting conditions are based on image clarity and face area size.

[0025] Furthermore, the set quantity is determined in the following manner:

[0026] The interval between the acquisition time of the first image and the start time of the set time period is calculated based on the third feature data, and the set quantity is determined based on the interval.

[0027] The set quantity is negatively correlated with the interval duration.

[0028] Furthermore, determining the release decision based on the facial recognition result includes:

[0029] If the face recognition result is a single match, then the access permission is determined based on the face data corresponding to the single match, and the access permission is used to make a decision to allow passage.

[0030] If the face recognition result shows multiple matches, a reminder message will be output.

[0031] A second aspect of the present invention provides a substation management identification system based on facial recognition, comprising an acquisition module, a processing module, and a storage module; the processing module is connected to the acquisition module and the storage module.

[0032] The storage module is used to store executable computer program code;

[0033] The acquisition module is used to acquire image data and transmit it to the processing module;

[0034] The processing module is configured to execute the method described in the preceding one by invoking the executable computer program code in the storage module.

[0035] A third aspect of the present invention provides an electronic device comprising: a memory storing executable program code; a processor coupled to the memory; the processor invoking the executable program code stored in the memory to perform the method as described in any of the preceding claims.

[0036] A fourth aspect of the invention provides a computer storage medium storing a computer program that, when executed by a processor, performs the method described in any of the preceding claims.

[0037] The present invention involves acquiring a first image of the verification area, extracting first feature data of the person to be verified from the first image, performing a first matching process on the first feature data, and determining a face recognition scheme based on the result of the first matching process, acquiring a second image of the verification area, extracting second feature data of the person to be verified from the second image according to the face recognition scheme, performing a second matching process on the second feature data, and obtaining a face recognition result based on the result of the second matching process, and determining a release decision based on the face recognition result; wherein the first image is a distant view image and the second image is a close-up view image. Therefore, the present invention improves the automation level of substation personnel management on the one hand, and on the other hand, can determine the optimal face recognition scheme as the person to be verified gradually approaches the verification point, thereby significantly improving the efficiency of face recognition. Attached Figure Description

[0038] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a flowchart illustrating a substation management identification method based on facial recognition disclosed in an embodiment of the present invention.

[0040] Figure 2 This is a schematic diagram of the structure of a substation management identification system based on face recognition disclosed in an embodiment of the present invention;

[0041] Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of the present invention. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0043] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the application. The singular forms “a,” “said,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0044] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0045] It should be understood that although the terms first, second, third, etc., may be used to describe ... in the embodiments of this application, these ... should not be limited to these terms. These terms are only used to distinguish .... For example, without departing from the scope of the embodiments of this application, first ... can also be referred to as second ..., and similarly, second ... can also be referred to as first ....

[0046] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”

[0047] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a product or system comprising a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a product or system. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the product or system that includes said element.

[0048] The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0049] Example 1

[0050] Please see Figure 1 , Figure 1 This is a flowchart illustrating a substation management identification method based on facial recognition disclosed in an embodiment of the present invention. Figure 1 As shown in the figure, a substation management identification method based on face recognition according to an embodiment of the present invention includes the following steps:

[0051] Acquire the first image of the verification area, and extract the first feature data of the person to be verified based on the first image;

[0052] Perform a first matching process on the first feature data, and determine a face recognition scheme based on the result of the first matching process;

[0053] A second image of the verification area is acquired, and the second feature data of the person to be verified is extracted from the second image according to the face recognition scheme.

[0054] The second feature data is subjected to a second matching process, and the face recognition result is obtained based on the result of the second matching process.

[0055] The decision to allow passage is made based on the facial recognition results;

[0056] The first image is a distant view, and the second image is a close-up view.

[0057] In this embodiment of the invention, facial recognition technology is used to verify the identity of personnel entering and exiting a substation (especially the core and critical areas of the substation), thereby generating a reasonable access decision. The facial recognition in this invention mainly includes two parts: 1) determining a facial recognition scheme based on the first feature data of the distant view of the person to be verified; 2) extracting the second feature data of the close-up view of the person to be verified based on the determined facial recognition scheme to complete the final identity comparison. Therefore, the solution of this invention improves the automation level of substation personnel management and, moreover, can determine the optimal facial recognition scheme as the person to be verified gradually approaches the verification point, thus significantly improving the efficiency of facial recognition.

[0058] The solution of this invention can be implemented in field processing equipment located in substations or on servers located in the cloud. The field processing equipment can be a general-purpose processor, such as a central processing unit (CPU) or a network processor (NP), or other intelligent hardware devices such as smartphones, personal computers, tablets, wearable devices, and intelligent robots. The server can be a traditional server or a cloud server; no limitation is made here. Furthermore, the field processing equipment and the server can be interconnected via a communication network, which can be a data network or a wireless network. The wireless network can be a 2G network, 3G network, 4G network, 5G network, Bluetooth, Wi-Fi, etc., and no limitation is made here.

[0059] Furthermore, the verification point in this invention can be set in any suitable area inside the substation, and this invention does not limit this.

[0060] Further, the step of performing a first matching process on the first feature data and determining a face recognition scheme based on the result of the first matching process includes:

[0061] The first feature data and the pre-stored template data are compared for similarity. If there is pre-stored template data with similarity greater than or equal to a threshold, the face recognition scheme is determined according to the first level of refinement; otherwise, the face recognition scheme is determined according to the second level of refinement.

[0062] The first level of precision is lower than the second level of precision.

[0063] In this embodiment of the invention, the present invention pre-stores pre-stored template data of all personnel in the personnel management system of the substation. The pre-stored template data includes associated first feature data and second feature data, wherein the first feature data can be human body contour data, and the second feature data is facial feature data. Therefore, the present invention can first determine whether there is a matching result for the human body contour of the person to be verified in the distance based on the human body contour data. If so, a facial recognition scheme is determined with a lower first level of precision; otherwise, a facial recognition scheme is determined with a higher second level of precision. The first and second levels of precision can be the number of sampling feature points (i.e., the second feature data) used for facial comparison, or the resolution of the image used to extract the second feature points.

[0064] Therefore, the solution of the present invention can determine a reasonable face recognition scheme based on the fuzzy judgment of whether the person to be verified is an authorized person. That is, when it is fuzzy judged that the person is an authorized person, face recognition is performed with a lower processing load, and otherwise, face recognition is performed in a higher and more refined way, thereby improving the efficiency of face recognition while ensuring the accuracy of face recognition.

[0065] It should be noted that the similarity involved can be calculated using any suitable similarity algorithm in the prior art, and this invention does not limit it.

[0066] Further, determining the face recognition scheme based on the first level of precision includes:

[0067] The number of pre-stored template data with similarity greater than or equal to a threshold is determined, and the first level of precision is determined based on the number; wherein, the first level of precision is positively correlated with the number.

[0068] The face recognition scheme is determined based on the first level of precision.

[0069] In this embodiment of the invention, when a face recognition scheme is generated using a lower first level of precision, the more pre-stored template data is matched, the more common the human body contour of the person to be verified is. In this case, a relatively higher first level of precision is needed to collect the second feature data in order to accurately distinguish the correct face from multiple matched pre-stored face data. Obviously, the more pre-stored templates are matched, the more precision of the second feature data extraction should be increased.

[0070] Therefore, the present invention, based on the adoption of high / low precision face recognition schemes respectively, further fine-tunes the low precision scheme, which can further improve the efficiency of face recognition.

[0071] Further, acquiring the second image of the verification area includes:

[0072] Based on the first image, third feature data related to the motion state of the person to be verified is extracted;

[0073] The set time period is calculated based on the third feature data, and the second image of the verification area is acquired within the set time period.

[0074] In this embodiment of the invention, to reduce the number of times the second image is acquired and processed, the second image is acquired within a set time period. This set time period can be determined based on the motion data of the person to be verified, i.e., the third feature data. For example, the set time period is the time when the person to be verified is predicted to reach the optimal position for the camera to capture the second image based on their position, direction of movement, and speed. Furthermore, because the acquisition method of the second image is determined in advance, this invention can also reduce the waiting time for the person to be verified in front of the camera, thereby improving the verification experience.

[0075] Further, acquiring the second image within the set time period includes:

[0076] Acquire a set number of third images within the set time period;

[0077] A fourth image that meets the set conditions is selected from the set number of third images, and the fourth image is used as the second image;

[0078] The setting conditions are based on image clarity and face area size.

[0079] In this embodiment of the invention, when the set time period is reached, i.e., when the person to be verified enters the designated location, several third images can be acquired. Images whose image clarity and face area size meet the set conditions are selected as second images for extracting second feature data.

[0080] Furthermore, the set quantity is determined in the following manner:

[0081] The interval between the acquisition time of the first image and the start time of the set time period is calculated based on the third feature data, and the set quantity is determined based on the interval.

[0082] The set quantity is negatively correlated with the interval duration.

[0083] In this embodiment of the invention, the faster the person to be verified arrives at the designated location, the greater the deceleration required. This can lead to instability and result in unclear third images, potentially preventing the selection of second images that meet the set criteria. Therefore, this invention determines the number of third images to be captured based on a negative correlation between the speed at which the person arrives at the designated location (i.e., the length of the time interval). The faster the person arrives, the more third images are captured, allowing for higher shutter speeds and increasing the likelihood of selecting second images that meet the criteria. Conversely, fewer third images are needed.

[0084] Furthermore, determining the release decision based on the facial recognition result includes:

[0085] If the face recognition result is a single match, then the access permission is determined based on the face data corresponding to the single match, and the access permission is used to make a decision to allow passage.

[0086] If the face recognition result shows multiple matches, a reminder message will be output.

[0087] In this embodiment of the invention, a face recognition result can be obtained according to the aforementioned face recognition scheme. Based on the face data corresponding to the face recognition result and the preset relationship, the access permission of the person to be verified can be determined, and thus, it can be determined whether to allow them to pass. There can be one or multiple face recognition results. If there are multiple results, a reminder message is output to remind the administrator to check the actual situation of the person to be verified, adjust the face recognition algorithm, or re-perform face recognition.

[0088] Example 2

[0089] Please see Figure 2 , Figure 2 This is a schematic diagram of the structure of a substation management identification system based on facial recognition, as disclosed in an embodiment of the present invention. Figure 2 As shown, a substation management identification system based on face recognition according to an embodiment of the present invention includes an acquisition module (101), a processing module (102), and a storage module (103); the processing module (102) is connected to the acquisition module (101) and the storage module (103);

[0090] The storage module (103) is used to store executable computer program code;

[0091] The acquisition module (101) is used to acquire image data and transmit it to the processing module (102);

[0092] The processing module (102) is configured to execute the method described in the preceding one by invoking the executable computer program code in the storage module (103).

[0093] The specific functions of the substation management identification system based on face recognition in this embodiment are the same as those in Embodiment 1 above. Since the system in this embodiment adopts all the technical solutions of the above embodiments, it has at least all the beneficial effects brought about by the technical solutions of the above embodiments, which will not be described in detail here.

[0094] Example 3

[0095] Please see Figure 3 , Figure 3 This invention discloses an electronic device comprising: a memory storing executable program code; a processor coupled to the memory; the processor calling the executable program code stored in the memory to execute the method described in Embodiment 1.

[0096] Example 4

[0097] This invention also discloses a computer storage medium storing a computer program, which is executed by a processor as described in Embodiment 1.

[0098] The computer storage medium of this invention can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. For example, a computer-readable storage medium can be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, system, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, system, or device.

[0099] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit programs for use by or in conjunction with an instruction execution system, system, or device.

[0100] The program code contained on a computer-readable medium may be transmitted using any suitable medium, including, but not limited to, wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0101] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0102] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, all of which fall within the scope of protection of the present invention.

Claims

1. A substation management identification method based on facial recognition, characterized in that, Includes the following steps: Acquire the first image of the verification area, and extract the first feature data of the person to be verified based on the first image; Perform a first matching process on the first feature data, and determine a face recognition scheme based on the result of the first matching process; A second image of the verification area is acquired, and the second feature data of the person to be verified is extracted from the second image according to the face recognition scheme. The second feature data is subjected to a second matching process, and the face recognition result is obtained based on the result of the second matching process. The decision to allow passage is made based on the facial recognition results; The first image is a distant view, and the second image is a close-up view. The first matching process for the first feature data, and the determination of a face recognition scheme based on the result of the first matching process, includes: The first feature data and the pre-stored template data are compared for similarity. If there is pre-stored template data with similarity greater than or equal to a threshold, the face recognition scheme is determined according to the first level of refinement; otherwise, the face recognition scheme is determined according to the second level of refinement. The first level of precision is lower than the second level of precision.

2. The substation management identification method based on face recognition according to claim 1, characterized in that: Determining the face recognition scheme based on a first level of precision includes: The number of pre-stored template data with similarity greater than or equal to a threshold is determined, and the first level of precision is determined based on the number; wherein, the first level of precision is positively correlated with the number. The face recognition scheme is determined based on the first level of precision.

3. The substation management identification method based on face recognition according to any one of claims 1-2, characterized in that: The acquisition of the second image of the verification area includes: Based on the first image, third feature data related to the motion state of the person to be verified is extracted; The set time period is calculated based on the third feature data, and the second image of the verification area is acquired within the set time period.

4. The substation management identification method based on face recognition according to claim 3, characterized in that: Acquiring the second image within the set time period includes: Acquire a set number of third images within the set time period; A fourth image that meets the set conditions is selected from the set number of third images, and the fourth image is used as the second image; The setting conditions are based on image clarity and face area size.

5. The substation management identification method based on face recognition according to claim 4, characterized in that: The set quantity is determined in the following way: The interval between the acquisition time of the first image and the start time of the set time period is calculated based on the third feature data, and the set quantity is determined based on the interval. The set quantity is negatively correlated with the interval duration.

6. The substation management identification method based on face recognition according to claim 1 or 5, characterized in that: The step of determining the release decision based on the facial recognition result includes: If the face recognition result is a single match, then the access permission is determined based on the face data corresponding to the single match, and the access permission is used to make a decision to allow passage. If the face recognition result shows multiple matches, a reminder message will be output.

7. A substation management identification system based on facial recognition, comprising an acquisition module, a processing module, and a storage module; the processing module is connected to the acquisition module and the storage module; The storage module is used to store executable computer program code; The acquisition module is used to acquire image data and transmit it to the processing module; Its features are: The processing module is configured to execute the method as described in any one of claims 1-6 by calling the executable computer program code in the storage module.

8. An electronic device, comprising: Memory containing executable program code; A processor coupled to the memory; The characteristic feature is that the processor calls the executable program code stored in the memory to execute the method as described in any one of claims 1-6.

9. A computer storage medium storing a computer program, characterized in that: The computer program is executed by the processor to perform the method as described in any one of claims 1-6.

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