CN107959850B - video quality diagnosis method based on image analysis - Google Patents
video quality diagnosis method based on image analysis Download PDFInfo
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- CN107959850B CN107959850B CN201711340455.8A CN201711340455A CN107959850B CN 107959850 B CN107959850 B CN 107959850B CN 201711340455 A CN201711340455 A CN 201711340455A CN 107959850 B CN107959850 B CN 107959850B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N17/00—Diagnosis, testing or measuring for television systems or their details
- H04N17/004—Diagnosis, testing or measuring for television systems or their details for digital television systems
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Abstract
the invention discloses a video quality diagnosis method based on image analysis, and relates to the technical field of video analysis. The method comprises the following steps: the method comprises the following steps that firstly, video quality problem points are located through a network video monitoring platform of a background management service center; step two, acquiring video data to be diagnosed through a forwarding server; diagnosing all indexes of the video data to be diagnosed through a video detection and analysis server; and step four, storing the detection result, giving out early warning and informing maintenance personnel. The invention positions the video data to be diagnosed through the network monitoring platform, acquires the corresponding video data, detects various indexes of the video data, and finally provides a detection method of three common factors which have the greatest influence on video quality diagnosis, so that fault points can be found effectively in time, the conditions of the fault points can be mastered, the labor pressure of people is reduced, and the normal operation of each system is ensured.
Description
Technical Field
The invention belongs to the technical field of video analysis, and particularly relates to a video quality diagnosis method based on image analysis.
Background
The security system plays an important role in protecting the life and property safety of people, the video monitoring system is an important component of the security system, and in some emergency situations, people often need to call video data for image analysis so as to obtain related information, the problems of picture freezing, noise interference, picture blurring and the like of the video data may occur, so that all monitoring points in the monitoring system need to be polled constantly, fault points can be timely and effectively mastered, the people can repair the video data effectively in time, and the normal and orderly work of the security system is ensured.
disclosure of Invention
The invention aims to provide a video quality diagnosis method based on image analysis, which is characterized in that video data to be diagnosed are positioned through a network monitoring platform, corresponding video data are obtained, various indexes of the video data are detected, and finally, a method for detecting three common factors which have the largest influence on video quality diagnosis is provided, so that the problems that the existing video quality diagnosis method is low in efficiency and cannot timely and effectively feed back fault points are solved.
in order to solve the technical problems, the invention is realized by the following technical scheme:
The invention relates to a video quality diagnosis method based on image analysis, which comprises the following steps:
The method comprises the following steps that firstly, video quality problem points are located through a network video monitoring platform of a background management service center;
Step two, acquiring video data to be diagnosed through a forwarding server;
diagnosing all indexes of the video data to be diagnosed through a video detection and analysis server;
And step four, storing the detection result, giving out early warning and informing maintenance personnel.
further, the network video monitoring platform comprises a polling server, and the polling server regularly inquires each monitoring network point.
Further, the indexes include a picture gain imbalance degree, a picture definition, a picture color bias degree, a contrast ratio, a video loss rate, a noise size, a horizontal stripe superposition degree, a picture freezing degree, a picture dithering degree, a view screen interference degree and a picture dramatic change degree.
further, the method for detecting the video interference degree comprises the following steps: and calculating the gray difference of two adjacent frames by using a gray difference method to further obtain the total frame difference, and comparing the total frame difference with a preset threshold value to obtain whether the video is interfered.
Further, the method for detecting the video definition comprises the following steps: and providing an image definition detection model according to an image definition detection algorithm of the edge transition width by using the image edge information and the related knowledge of probability, and verifying the algorithm model.
Further, the method for detecting the magnitude of the video noise comprises the following steps: the method is based on an image noise detection algorithm of directional operators, and utilizes eight operators in different directions to preliminarily judge noise points, and then carries out secondary judgment on the detected noise points through a local fuzzy membership function.
The invention has the following beneficial effects:
According to the invention, through acquiring the video data at the video quality problem point and diagnosing various indexes of the video data, the detection methods of three common factors are provided, the efficiency of video quality diagnosis is improved, people can conveniently and effectively know the condition of the video to be diagnosed in time, the normal operation of a video system is ensured, and the labor pressure of people is reduced to a certain extent.
of course, it is not necessary for any product in which the invention is practiced to achieve all of the above-described advantages at the same time.
Drawings
in order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a method for video quality diagnosis based on image analysis according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, the present invention is a video quality diagnosis method based on image analysis, comprising the following steps:
The method comprises the following steps that firstly, video quality problem points are located through a network video monitoring platform of a background management service center;
Step two, acquiring video data to be diagnosed through a forwarding server;
Diagnosing all indexes of the video data to be diagnosed through a video detection and analysis server;
and step four, storing the detection result, sending out early warning, and informing maintenance personnel, so that the fault point can be maintained timely and effectively, and the normal operation of the monitoring system is ensured.
The network video monitoring platform comprises a polling server which inquires each monitoring network point at regular time and sends the position of the video quality problem point to the network video monitoring platform, so that a background management service center can take corresponding measures in time.
the indexes comprise picture gain unbalance degree, picture definition, picture deflection degree, contrast, video loss rate, noise size, horizontal stripe superposition degree, picture freezing degree, picture dithering degree, video screen interference degree and picture dramatic change degree, which are detection targets of a video detection and analysis server, and the video interference degree, the video definition and the video noise size are three common video quality influence factors.
The method for detecting the video interference degree comprises the following steps: the gray difference of two adjacent frames is calculated by using a gray difference method, so that the total frame difference is obtained, and the total frame difference is compared with a preset threshold value to obtain whether the video is interfered.
the video definition detection method comprises the following steps: and providing an image definition detection model according to an image definition detection algorithm of the edge transition width by using the image edge information and the related knowledge of probability, and verifying the algorithm model.
The detection method of the video noise magnitude comprises the following steps: the method is based on an image noise detection algorithm of directional operators, and utilizes eight operators in different directions to preliminarily judge noise points, and then carries out secondary judgment on the detected noise points through a local fuzzy membership function.
in the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
the preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise embodiments disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (1)
1. A video quality diagnosis method based on image analysis is characterized in that: the method comprises the following steps:
Firstly, a network video monitoring platform of a background management service center positions video quality problem points through a polling server;
Step two, acquiring video data to be diagnosed through a forwarding server;
Diagnosing all indexes of the video data to be diagnosed through a video detection and analysis server;
Wherein, each index comprises picture gain unbalance degree, video definition, picture deflection degree, contrast, video loss rate, noise size, horizontal stripe superposition degree, picture freezing degree, picture dithering degree, video interference degree and picture dramatic change degree;
The video definition detection method comprises the following steps: providing an image definition detection model according to an image definition detection algorithm of the edge transition width by using the image edge information and the related knowledge of probability, and verifying the algorithm model;
The detection method of the noise magnitude comprises the following steps: the method comprises the steps that an image noise detection algorithm based on directional operators preliminarily judges noise points by utilizing eight operators in different directions, and then secondarily judges the detected noise points through a local fuzzy membership function;
the method for detecting the video interference degree comprises the following steps: calculating the gray difference between two adjacent frames by using a gray difference method to obtain a total frame difference, and comparing the total frame difference with a preset threshold value to obtain whether the video is interfered;
and step four, storing the diagnosis result, sending out early warning and informing maintenance personnel.
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| CN107959850B true CN107959850B (en) | 2019-12-06 |
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| CN102395043A (en) * | 2011-11-11 | 2012-03-28 | 北京声迅电子股份有限公司 | Video quality diagnosing method |
| CN105306925A (en) * | 2015-10-09 | 2016-02-03 | 福州市超智电子科技有限公司 | Monitoring system and monitoring method for video monitoring front-end equipment |
| CN106534845A (en) * | 2016-11-28 | 2017-03-22 | 四川长虹电器股份有限公司 | Television screen based on artificial intelligence and screen assembly diagnostic system and method |
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Patent Citations (5)
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| CN101527867A (en) * | 2009-03-20 | 2009-09-09 | 广州杰赛科技股份有限公司 | Television network monitoring system and monitoring method thereof |
| CN102387038A (en) * | 2011-10-20 | 2012-03-21 | 赛特斯网络科技(南京)有限责任公司 | Network video fault positioning system and method based on video detection and comprehensive network management |
| CN102395043A (en) * | 2011-11-11 | 2012-03-28 | 北京声迅电子股份有限公司 | Video quality diagnosing method |
| CN105306925A (en) * | 2015-10-09 | 2016-02-03 | 福州市超智电子科技有限公司 | Monitoring system and monitoring method for video monitoring front-end equipment |
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Effective date of registration: 20200511 Address after: 1101, floor 11, building 1, No. 28, Pingguoyuan Road, Shijingshan District, Beijing 100000 Patentee after: Lilou Technology (Beijing) Co., Ltd Address before: 230000 Mount Huangshan road Anhui city Hefei province high tech Zone No. 616 iFLYTEK No. 1 building three layer Patentee before: HEFEI VRVIEW INFORMATION TECHNOLOGY Co.,Ltd. |