Fast Algorithm For Digital Video Defects Monitoring

The main content of this paper is to study on the algorithm of digital TV video defects,based on the Mpeg2 video compression technology,decoding the digital television technology research of fault phenomenon only have three kinds: black field,static frame,Mosaic.This article will detail Mpeg2 system layer,compression coding,the principle and technology,research for Mosaic the causes of defects and characteristics.Based on the digital TV to black,static frame of automatic identification has been widely used,and good results are obtained.And Mosaic image because of the complexity of the causes and characteristics,so it’s difficulty to automatically identify Mosaic defects in the video content.At present,the Mosaic image detection in digital television is a blank in domestic digital TV monitor.Mosaic is unique to digital TV video image.Black field and static frame recognition detection based on the analysis of the traditional mpeg-2 video format characteristics,namely through brightness and color difference to detect.In order to more rapid algorithm,and the detection can adapt to all kinds of video format identification test,I propose the method through the detection of gray black field and static frame.This method is greatly simplified algorithm and improved the application range of the algorithm.Based on the digital TV image Mosaic in the fault detection of the image as a research focus,in-depth analysis of Mosaic of failure,further study on reason and characteristics of the image,on the basis of looking for a detection method of image Mosaic.Mosaic detection in real-time monitoring system of image,so the detection method should not only has good detection effect,also with the realization of the fast speed.Based on image edge extraction.The paper summarizes macro-block type improvement and the existing algorithm,and put forward the best accurate algorithm using the VC++ to realize simulation.Program experiments show that the method in guarantee under the condition of low false positives,and achieve the goal of the Mosaic fault image detection.