Research And Application Of The Video Detection Technology In The Snapshot System For Cars Running Red Light

With the development of the technology, the research and application of the video detection technology in Intelligent Transportation Systems has drawn increasing attention, which is mainly based on the video image processing and analyzing. It has so many advantages such as intuitive, easy installation, low maintenance cost, that it can on behalf of the vehicle detector development. The video detection technology has already become one of the important research topics in Intelligent Transportation Field.At present, a great number of modern urban traffic control systems are built in more and more cities in our country, and this will play a key role in the improvement of urban traffic congestion and reduction of traffic accidents.How to ensure the video detection system will detect the target accurately in a variety of complex environments and conditions(such as shelter, light change, etc) ,has become the common focus among the researchers, which also is a urgent problem to be solved in practical application.Combined with the"Design of Intelligent Transportation System in HeFei economic developing-area"project, this paper has made extensive and in-depth research towards the video detection technology in the snapshot system for cars running red light. Specifically including the following aspects:1. Fully illustration of the feasibility and advantage of the video detection technology in the snapshot system for cars running red light;2. Detailed explanation of the project design, and determination that applying the video detection technology as the illegal vehicle detection method in the system.3. Comparisons between current video detection algorithms was made, and through their respective strengths, weaknesses, and the related fields, the conclusion was summarized.; the description of the video-based frame differential detection technology ,which is popular in the system ,was proposed. And its shortcomings was also stated.4. Based on the frame differential algorithm, the improvement of the algorithm was proposed. and the optimization was also made in the difference and binaryzation in the video image post processing, which provided a great improvement in actual effect of snapshot compared with before.