Design And Implementation Of Surveillance Video Image Quality Evaluation System

With the continuous improvement monitoring technology,more and more video surveillance systems have also appeared,followed by a doubling of the number of video surveillance and monitoring growth also increasingly wide range,while monitoring the video image quality problems also caused People pay attention to it.Traditional monitoring video quality evaluation often takes an artificial way and judges abnormal types based on human subjectivity.This way will cause a huge workload,and this way is affected by many factors,such as observer the psychological activity or knowledge background,etc.,these will affect the accuracy rate.Therefore,it is very important to use objective video image quality evaluation methods to detect abnormal types of video images in surveillance video systems.Objective video image quality evaluation methods can greatly improve detection efficiency and reduce costs.When quality problems occur in the surveillance video images,the failure to perform timely maintenance will also cause losses.Therefore,in order to quickly find video image quality problems,it is necessary to monitor the video system to maintain the video image quality in a timely manner.Based on the above situation,this thesis designs and implements a monitoring video image quality evaluation system,which can automatically diagnose the quality of video images.According to the actual needs of the monitoring video image quality evaluation system,the system is mainly divided into a data management module,an online and quality inspection module,and a result storage module.In the data management module,it mainly manages the monitoring equipment and its health status information,and manages the online plan and quality diagnosis plan;in the online and quality detection module,it mainly realizes the online detection and quality diagnosis of the monitoring equipment,in the quality diagnosis module Mainly diagnose the image blur abnormality and snowflake noise abnormality.By studying the fuzzy evaluation algorithm and snowflake noise evaluation algorithm,the two algorithms are integrated into the monitoring video image quality evaluation system,so as to carry out quality diagnosis on the monitoring video image,finally the monitoring equipment information and test results are saved in the database for query and display.This thesis designs and implements various functional modules and tests the system.The test results show that the system has practical value.Diagnosing fuzzy anomalies and snowflake anomalies has a high accuracy rate,which basically meets the expected goals.