CN115171328A - Firework identification method, device, equipment and medium based on video compression coding - Google Patents
Firework identification method, device, equipment and medium based on video compression coding Download PDFInfo
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/12—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions
- G08B17/125—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions by using a video camera to detect fire or smoke
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B7/00—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00
- G08B7/06—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00 using electric transmission, e.g. involving audible and visible signalling through the use of sound and light sources
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/60—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
- H04N19/625—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding using discrete cosine transform [DCT]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
The invention discloses a firework identification method, a firework identification device, firework identification equipment and firework identification media based on video compression coding, wherein the firework identification method comprises the steps of obtaining two images at the same position from video monitoring resource data of a transformer substation at a first moment and a second moment, and respectively carrying out difference on the two images to obtain a pixel value difference matrix between the two images; respectively performing DCT conversion processing on the pixel value difference value matrixes between the two images, namely two DCT coefficient matrixes; quantizing the two DCT coefficient matrixes respectively to obtain two quantization matrixes; and performing difference on the two quantization matrixes, and judging that an abnormality occurs when the number of pixel blocks with the difference value exceeding a first set threshold exceeds a second set threshold. The invention only needs to obtain the pictures of video interval in the station for a certain time, and carries out conversion calculation on the image pictures for comparison. The algorithm is simple, and the rapid and efficient abnormity identification is realized.
Description
Technical Field
The invention belongs to the technical field of image processing, and particularly relates to a firework identification method, device, equipment and medium based on video compression coding.
Background
The industrial video monitoring system installed in the transformer substation is mainly used for monitoring the running condition of equipment in the transformer substation, generally comprises a front-end monitoring system, a video control platform and the like, and mainly monitors image videos in the transformer substation, for example, the front-end system acquires required image video resource data through deployed video and data acquisition equipment such as a digital camera, a sensor and an NVR (noise, vibration and harshness), and transmits the data to the video control platform.
The existing industrial video monitoring system usually has a large number of cameras for monitoring, and when a power grid fails to operate, the monitoring system performs identification through a carried intelligent identification algorithm, for example, an artificial intelligence algorithm and the like. However, in the existing anomaly identification method, a large number of learning target samples are needed to form a set of sample library, and the result can be obtained only in the comparison process of the detection target in the samples, so that the algorithm is complex, and long-time training and learning are needed.
Disclosure of Invention
The invention aims to provide a firework identification method, a firework identification device, firework identification equipment and firework identification media based on video compression coding, and aims to solve the problems that a large number of learning target samples are needed, long-time training is needed, and an algorithm is complex in an abnormal identification method in the prior art.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect of the present invention, a method for identifying an anomaly based on video compression coding is provided, which includes the following steps:
acquiring two images at the same position from video monitoring resource data of a transformer substation at a first moment, wherein the two images are a first image and a second image respectively;
acquiring two images at the same position from video monitoring resource data of the transformer substation at a second moment, wherein the two images are respectively a third image and a fourth image;
making a difference between pixel blocks of the first image and the second image to obtain a pixel value difference value matrix between the first images;
making a difference between pixel blocks of the third image and the fourth image to obtain a pixel value difference value matrix between the second images;
performing DCT conversion processing on the first inter-image pixel value difference matrix and the second inter-image pixel value difference matrix respectively to obtain a first DCT coefficient matrix and a second DCT coefficient matrix;
quantizing the first DCT coefficient matrix and the second DCT coefficient matrix respectively to obtain a first quantization matrix and a second quantization matrix;
and performing difference on the first quantization matrix and the second quantization matrix, and judging that abnormality occurs when the number of pixel blocks with difference values exceeding a first set threshold exceeds a second set threshold.
As an alternative of the invention, the interval between the first and second moments is 5s.
As an alternative of the present invention, in the step of quantizing the first DCT coefficient matrix and the second DCT coefficient matrix respectively, the method of quantizing is:
dividing the first and second DCT coefficient matrices by a constant, respectively;
rounding the obtained value corresponding to the pixel point to get the whole.
As an alternative of the invention, the first, second, third and fourth images have a size of 1024 × 768.
As an alternative of the present invention, in the step of performing DCT conversion on the first inter-image pixel value difference matrix and the second inter-image pixel value difference matrix, DCT conversion is performed according to the following formula:
in the above formula, f (i, j) is a spatial domain two-dimensional vector element, i, j =0,1,2,3 \8230 \ 8230and N-1, f (u, v) is a transform coefficient array element, N is the total number of f (i, j), and c (u), c (v) are constants.
As an alternative of the present invention, after the step of determining that an abnormality occurs when the number of pixel blocks whose difference values exceed the first set threshold exceeds the second set threshold, the abnormality signal is sent to a background management center.
As an alternative of the invention, after the step of determining that an abnormality occurs when the number of pixel blocks with the difference value exceeding the first set threshold exceeds the second set threshold, an acousto-optic alarm is performed in the substation.
In a second aspect of the present invention, an anomaly recognition apparatus based on video compression coding is provided, including:
the first acquisition module is used for acquiring two images at the same position from video monitoring resource data of a transformer substation at a first moment, wherein the two images are a first image and a second image respectively;
the second acquisition module is used for acquiring two images at the same position from the video monitoring resource data of the transformer substation at a second moment, wherein the two images are respectively a third image and a fourth image;
the first difference module is used for making a difference between the pixel blocks of the first image and the second image to obtain a pixel value difference matrix between the first images;
the second difference module is used for making a difference between pixel blocks of the third image and the fourth image to obtain a pixel value difference matrix between the second images;
the first conversion module is used for respectively performing DCT conversion processing on the first inter-image pixel value difference matrix and the second inter-image pixel value difference matrix to obtain a first DCT coefficient matrix and a second DCT coefficient matrix;
the second conversion module is used for quantizing the first DCT coefficient matrix and the second DCT coefficient matrix respectively to obtain a first quantization matrix and a second quantization matrix;
and the third difference module is used for making a difference between the first quantization matrix and the second quantization matrix, and judging that an abnormality occurs when the number of the pixel blocks with the difference value exceeding the first set threshold exceeds the second set threshold.
In a third aspect of the present invention, an electronic device is provided, which includes a processor and a memory, wherein the processor is configured to execute a computer program stored in the memory to implement the above-mentioned video compression coding-based anomaly identification method.
In a fourth aspect of the present invention, a computer-readable storage medium is provided, which stores at least one instruction, and the at least one instruction when executed by a processor implements the above-mentioned video compression coding-based anomaly identification method.
The invention has the following beneficial effects:
the anomaly identification method provided by the invention comprises the steps of acquiring two images at the same position from video monitoring resource data of a transformer substation at a first moment, wherein the two images are respectively a first image and a second image; acquiring two images at the same position from video monitoring resource data of the transformer substation at a second moment, wherein the two images are respectively a third image and a fourth image; making a difference between pixel blocks of the first image and the second image to obtain a pixel value difference value matrix between the first images; performing difference on pixel blocks of the third image and the fourth image to obtain a pixel value difference value matrix between second images; performing DCT conversion processing on the first inter-image pixel value difference matrix and the second inter-image pixel value difference matrix respectively to obtain a first DCT coefficient matrix and a second DCT coefficient matrix; quantizing the first DCT coefficient matrix and the second DCT coefficient matrix respectively to obtain a first quantization matrix and a second quantization matrix; and performing difference on the first quantization matrix and the second quantization matrix, and judging that abnormality occurs when the number of pixel blocks with difference values exceeding a first set threshold exceeds a second set threshold. The invention only needs to acquire the pictures of the video interval in the station for a certain time, and carries out conversion calculation on the image pictures for comparison. The identification method obtains the abnormal type by analyzing and calculating the interval pictures, can identify various abnormal types such as personnel, smoke and fire, foreign matter entering and the like, has simple algorithm and realizes quick and efficient abnormal identification.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a flowchart of a firework identification method based on video compression coding according to an embodiment of the present invention.
FIG. 2 is a schematic diagram of a matrix before and after DCT transformation according to an embodiment of the present invention. Wherein, (a) is an 8 x 8 image block, and (b) is a coefficient matrix after DCT conversion.
Fig. 3 is a schematic diagram of matrix quantization before and after the embodiment of the present invention. Fig. 3 (a) shows a DCT coefficient matrix before quantization, and fig. 3 (b) shows a DCT coefficient matrix after quantization.
Fig. 4 is a block diagram of an anomaly recognition apparatus based on video compression coding according to the present invention.
Fig. 5 is a block diagram of an electronic device according to the present invention.
Detailed Description
The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
The following detailed description is exemplary in nature and is intended to provide further details of the invention. Unless otherwise defined, all technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention.
Example 1
As shown in fig. 1, the present embodiment provides a firework identification method based on video compression coding, including the following steps:
s1, two images at the same position are obtained from video monitoring resource data of a transformer substation at a first moment and are respectively a first image and a second image. And acquiring two images of the same position from the video monitoring resource data of the transformer substation at the second moment, wherein the two images are respectively a third image and a fourth image.
Specifically, in step S1, a computer is used to extract the current intra-site industrial video picture, and two consecutive images, i.e., four images in total, are extracted at intervals of 5S.
As an example of the above-described steps, according to the actual situation, the size of the extracted image is 1024 × 768 size in the present embodiment.
S2, carrying out difference on pixel blocks of the first image and the second image to obtain a pixel value difference value matrix between the first images; and carrying out difference on pixel blocks of the third image and the fourth image to obtain a pixel value difference value matrix between the second images.
And S3, performing DCT conversion processing on the first inter-image pixel value difference matrix and the second inter-image pixel value difference matrix respectively to obtain a first DCT coefficient matrix and a second DCT coefficient matrix.
It should be noted that, in step S3, the purpose of performing DCT conversion on the first inter-image pixel value difference matrix and the second inter-image pixel value difference matrix is to transform the inter-image pixel value difference matrix to a frequency domain, so as to achieve redundancy removal and better energy aggregation of the change degree, and to aggregate more important information of the images together, thereby implementing operations in subsequent steps.
Specifically, in step S3, the DCT is performed on the first inter-image pixel value difference matrix and the second inter-image pixel value difference matrix according to the following formula:
in the above formula, f (i, j) is a spatial domain two-dimensional vector element, i, j =0,1,2,3 \8230 \ 8230and N-1, f (u, v) is a transform coefficient array element, N is the total number of f (i, j), and c (u), c (v) are constants.
As shown in fig. 2, fig. 2 (a) is an 8 × 8 selected image block, and it can be found that after DCT transformation, a large amount of energy is concentrated in the low-frequency coefficient portion at the upper left corner of the 8 × 8 image block, as shown in fig. 2 (b), little energy is concentrated in the high-frequency coefficient at the lower right corner, and the energy fluctuation distribution of the difference matrix is obtained.
S4, quantizing the first DCT coefficient matrix and the second DCT coefficient matrix respectively to obtain a first quantization matrix and a second quantization matrix;
specifically, in step S4, in the step of quantizing the first DCT coefficient matrix and the second DCT coefficient matrix, the quantization method is: dividing the first and second DCT coefficient matrices by a constant, respectively; rounding the obtained value corresponding to the pixel point to get the whole. The quantization process is actually dividing the transformed DCT coefficient by a constant and then rounding, and the result of the quantization is an integer multiple of the quantization or more zero values, thereby achieving the purpose of compression, as shown in fig. 3, where fig. 3 (a) is the DCT coefficient matrix before quantization and fig. 3 (b) is the DCT coefficient matrix after quantization.
And S5, making a difference between the first quantization matrix and the second quantization matrix, and judging that abnormality occurs when the number of pixel blocks with the difference value exceeding a first set threshold exceeds a second set threshold.
Specifically, in step S5, pixels corresponding to the first quantization matrix and the second quantization matrix are subtracted to obtain a difference value of each pixel, if the difference value of the pixels exceeds a first set threshold, the pixel is considered to be abnormal, and when the number of the pixels exceeding the first set threshold exceeds a second set threshold, it is determined that the monitoring position in the substation is abnormal.
As an example, in step S5, the first set threshold may be set to 10, and the second set threshold may be set to a ratio of the abnormal pixel to all the pixels, for example, the ratio may be set to 30%, 50%, or the like.
In other embodiments, after the step of determining that an abnormality occurs when the number of pixel blocks with the difference value exceeding the first set threshold exceeds the second set threshold, the abnormality signal is sent to a background management center, and meanwhile, an acousto-optic alarm is carried out in the substation.
The method is verified by tests, and the in-station video is detected in real time by the method, so that the safety in the transformer substation can be guaranteed to the maximum extent. During the test, by simulating the form of fire, the method can quickly and efficiently detect the result and give warning to workers
Example 2
As shown in fig. 4, in a second aspect of the present invention, there is provided an abnormality recognition apparatus based on video compression coding, including:
the first acquisition module is used for acquiring two images at the same position from video monitoring resource data of the transformer substation at a first moment, wherein the two images are respectively a first image and a second image.
And the second acquisition module is used for acquiring two images at the same position from the video monitoring resource data of the transformer substation at the second moment, wherein the two images are respectively a third image and a fourth image.
In the first acquisition module and the second acquisition module, the size of the acquired image is 1024 × 768.
And the first difference module is used for performing difference on the pixel blocks of the first image and the second image to obtain a pixel value difference matrix between the first images.
And the second difference module is used for making a difference between the pixel blocks of the third image and the fourth image to obtain a pixel value difference matrix between the second images.
And the first conversion module is used for respectively performing DCT conversion processing on the first inter-image pixel value difference matrix and the second inter-image pixel value difference matrix to obtain a first DCT coefficient matrix and a second DCT coefficient matrix.
In the first conversion module, the inter-image pixel value difference matrix and the inter-image pixel value difference matrix are subjected to DCT conversion according to the following formula:
in the above formula, f (i, j) is a spatial domain two-dimensional vector element, i, j =0,1,2,3 \8230, N-1, f (u, v) is a transform coefficient array element, N is the total number of f (i, j), and c (u), c (v) are constants.
And the second conversion module is used for quantizing the first DCT coefficient matrix and the second DCT coefficient matrix respectively to obtain a first quantization matrix and a second quantization matrix.
In the second conversion module, in the step of quantizing the first DCT coefficient matrix and the second DCT coefficient matrix respectively, the quantization method is: dividing the first and second DCT coefficient matrices by a constant, respectively; rounding the obtained value corresponding to the pixel point to get the whole.
And the third difference module is used for making a difference between the first quantization matrix and the second quantization matrix, and judging that an abnormality occurs when the number of the pixel blocks with the difference value exceeding the first set threshold exceeds the second set threshold.
Example 3
As shown in fig. 5, the present invention further provides an electronic device 100 implementing the firework identification method based on video compression coding according to embodiment 1; the electronic device 100 comprises a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on the at least one processor 102, and at least one communication bus 104. The memory 101 may be used to store a computer program 103, and the processor 102 may implement the firework identification method steps of embodiment 1 based on video compression coding by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101. The memory 101 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data) created according to the use of the electronic apparatus 100, and the like. In addition, the memory 101 may include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other non-volatile solid state storage device.
The at least one Processor 102 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The processor 102 may be a microprocessor or the processor 102 may be any conventional processor or the like, and the processor 102 is the control center of the electronic device 100 and connects the various parts of the entire electronic device 100 using various interfaces and lines.
The memory 101 in the electronic device 100 stores a plurality of instructions to implement a video compression coding based smoke and fire identification method, and the processor 102 may execute the plurality of instructions to implement:
acquiring two images at the same position from video monitoring resource data of a transformer substation at a first moment, wherein the two images are a first image and a second image respectively;
acquiring two images of the same position from video monitoring resource data of the transformer substation at a second moment, wherein the two images are respectively a third image and a fourth image;
making a difference between pixel blocks of the first image and the second image to obtain a pixel value difference value matrix between the first images;
making a difference between pixel blocks of the third image and the fourth image to obtain a pixel value difference value matrix between the second images;
performing DCT conversion processing on the first inter-image pixel value difference matrix and the second inter-image pixel value difference matrix respectively to obtain a first DCT coefficient matrix and a second DCT coefficient matrix;
quantizing the first DCT coefficient matrix and the second DCT coefficient matrix respectively to obtain a first quantization matrix and a second quantization matrix;
and performing difference on the first quantization matrix and the second quantization matrix, and judging that abnormality occurs when the number of pixel blocks with difference values exceeding a first set threshold exceeds a second set threshold.
Example 4
The integrated modules/units of the electronic device 100 may be stored in a computer-readable storage medium if implemented in the form of software functional units and sold or used as separate products. Based on such understanding, all or part of the flow in the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium and used by a processor to implement the steps of the above-described embodiments of the method. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, U.S. disk, removable hard disk, magnetic disk, optical disk, computer Memory, and Read-Only Memory (ROM).
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: although the present invention has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (10)
1. An abnormality identification method based on video compression coding is characterized by comprising the following steps:
acquiring two images at the same position from video monitoring resource data of a transformer substation at a first moment, wherein the two images are a first image and a second image respectively;
acquiring two images of the same position from video monitoring resource data of the transformer substation at a second moment, wherein the two images are respectively a third image and a fourth image;
making a difference between pixel blocks of the first image and the second image to obtain a pixel value difference value matrix between the first images;
making a difference between pixel blocks of the third image and the fourth image to obtain a pixel value difference value matrix between the second images;
performing DCT conversion processing on the first inter-image pixel value difference matrix and the second inter-image pixel value difference matrix respectively to obtain a first DCT coefficient matrix and a second DCT coefficient matrix;
quantizing the first DCT coefficient matrix and the second DCT coefficient matrix respectively to obtain a first quantization matrix and a second quantization matrix;
and performing difference on the first quantization matrix and the second quantization matrix, and judging that abnormality occurs when the number of pixel blocks with difference values exceeding a first set threshold exceeds a second set threshold.
2. The method of claim 1, wherein the interval between the first time and the second time is 5s.
3. The method of claim 1, wherein in the step of quantizing the first matrix of DCT coefficients and the second matrix of DCT coefficients, respectively, the quantization is performed by:
dividing the first and second DCT coefficient matrices by a constant, respectively;
rounding the obtained value corresponding to the pixel point to get the whole.
4. The video compression coding-based anomaly identification method according to claim 1, wherein the sizes of the first image, the second image, the third image and the fourth image are 1024 × 768.
5. The method of claim 1, wherein in the step of performing DCT transform on the first inter-image pixel value difference matrix and the second inter-image pixel value difference matrix, the DCT transform is performed according to the following formula:
in the above formula, f (i, j) is a spatial domain two-dimensional vector element, i, j =0,1,2,3 \8230 \ 8230and N-1, f (u, v) is a transform coefficient array element, N is the total number of f (i, j), and c (u), c (v) are constants.
6. The method according to claim 1, wherein after the step of determining that an abnormality occurs when the number of pixel blocks with a difference value exceeding a first set threshold exceeds a second set threshold, the abnormality signal is sent to a background management center.
7. The video compression coding-based abnormality identification method according to claim 1, wherein an acousto-optic alarm is performed in a substation after the step of determining that an abnormality occurs when the number of pixel blocks having a difference value exceeding a first set threshold exceeds a second set threshold.
8. An abnormality recognition apparatus based on video compression coding, comprising:
the first acquisition module is used for acquiring two images at the same position from video monitoring resource data of a transformer substation at a first moment, wherein the two images are a first image and a second image respectively;
the second acquisition module is used for acquiring two images at the same position from the video monitoring resource data of the transformer substation at a second moment, wherein the two images are respectively a third image and a fourth image;
the first difference module is used for making a difference between the pixel blocks of the first image and the second image to obtain a pixel value difference matrix between the first images;
the second difference module is used for making a difference between pixel blocks of the third image and the fourth image to obtain a pixel value difference matrix between the second images;
the first conversion module is used for respectively performing DCT conversion processing on the first inter-image pixel value difference matrix and the second inter-image pixel value difference matrix to obtain a first DCT coefficient matrix and a second DCT coefficient matrix;
the second conversion module is used for quantizing the first DCT coefficient matrix and the second DCT coefficient matrix respectively to obtain a first quantization matrix and a second quantization matrix;
and the third difference module is used for making a difference between the first quantization matrix and the second quantization matrix, and judging that an abnormality occurs when the number of the pixel blocks with the difference value exceeding the first set threshold exceeds the second set threshold.
9. An electronic device, comprising a processor and a memory, wherein the processor is configured to execute a computer program stored in the memory to implement the video compression coding-based anomaly identification method according to any one of claims 1 to 7.
10. A computer-readable storage medium storing at least one instruction, which when executed by a processor implements the method for identifying an abnormality based on video compression coding according to any one of claims 1 to 7.
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