Vehicle counting method based on digital image processing algorithms

Abstract

Vehicle counting process provides appropriate information about traffic flow, vehicle crash occurrences and traffic peak times in roadways. An acceptable technique to achieve these goals is using digital image processing methods on roadway camera video outputs. This paper presents a vehicle counter-classifier based on a combination of different video-image processing methods including object detection, edge detection, frame differentiation and the Kalman filter. An implementation of proposed technique has been performed using C++ programming language. The method performance for accuracy in vehicle counts and classify was evaluated, which resulted in about 95 percent accuracy for classification and about 4 percent error in vehicle detection targets.