Abstract: According to the requirements of vehicle classification, this paper presents a vehicle type recognition algorithm based on error ellipse. It uses background differential method to remove the uncorrelated background of vehicle image, so to get the target image. Vehicle recognition and contour extraction is done by image analysis. A 2D coordinate uncorrelated variance matrix is got by translating, rotating and zoom operating the vehicle outlines. The uncorrelated variance matrix is used to compare with the vehicle classification template in advance and a vehicle is classified to the right type. Experimental results show that the algorithm can obtain good classification results, and meet the requirement of real-time.
vehicle type recognition,
Intelligent Transportation System(ITS),