Vehicle detection under heterogonous environment using different Classification Techniques
Vehicle Detection can result in great value in relations of monitoring of vehicles and identification of vehicle based on vehicle appearance. Some challenges for detection under heterogeneous environment are image acquisition, differences in lights and climate, blockings, shadows, reflections, huge diversity of vehicles, addition/deletion of vehicles’ models over time, etc. Many different classifiers are available and none of these classifiers perform best in all different types of applications. In this paper we have discussed a vehicle detection system with few classification techniques along with their strengths and weaknesses which help to select the classification technique to solve the problem of detection the vehicle under heterogonous environment.