Research And Realization Of Vehicle Detection Algorithm In Intelligent Transportation

Moving object detection is an important research area in video surveillance, computer vision and pattern recognition and it has broad application prospects in security monitoring, intelligent transportation, military, navigation, etc.In recent years, intelligent video surveillance system has become a new research hot spot in public safety. It is quite different from the traditional surveillance system since it not only replaces the human eyes with camera, but also builds an automatic or semi-automatic video understanding and analysis system in the use of computer software. It can offer accurate analysis result. With the development of the social economy, the number of cars increases dramatically, which makes it difficult to control and manage the vehicular traffic. The emergence of the intelligent transportation system relieves the traffic pressure, so the intelligent transportation system is an important component of the intelligent transportation system.This thesis does research on the moving object detection algorithm in fixed-scenes video surveillance system. This article focuses on the following aspects.(1) At first, the article mainly include background model, the innovation of background update, and solve the problem of creating background in heavy traffic.(2) A shadow detection algorithm based on cross-correlation function and Canny edge detection.(3) Compare the characteristic and application value of several motion detection algorithms. Finding the advantage and disadvantage of every method.(4) The traffic detection in night. Using different method by the light.The experimental results show that the algorithm can effectively solve the problem in the intelligent transportation system.