Automatic Vehicle Detection Using Pixelwise Classification Approach

We present a system to detect and track moving vehicles based on the pixelwise classification approach. In this approach escapes some of the existing frameworks for detection vehicles in traffic monitoring systems. So many researchers and intelligent minds are introduces so many technique but not provided the accurate results. Proposed technique uses designed pixel wise classification method, canny edge detection techniques and back ground color subtraction method that leads to accurate results in vehicle detection rate. Pixel wise classification provides not only region wise but also sliding window also detected the vehicles. The feature extraction performed in both training and detection stages. The classification purpose we use dynamic Bayesian networks and in this network vehicle and non vehicle are identify purpose used a support vector machine. The classification of vehicles and non vehicles are identification purpose used a color histogram algorithm. When we performed all the methods easily identify the vehicles and provides accuracy results to compare the previous approaches. In experimental results are shown in different videos are taken at different cameras and different heights in surveillance systems.