Vahid Heidari - Department of Electrical and Computer Engineering Isfahan University of Technology, IUT Isfahan, Iran
Mohammad Reza Ahmadzadeh - Department of Electrical and Computer Engineering Isfahan University of Technology, IUT Isfahan, Iran

This paper presents a new method to classify vehicles with resolving vehicle occlusions in traffic images. Moving objects are detected in an image sequence using aprobability-based background extraction and object segmentation algorithm. The partially occluded vehicles are detected by evaluating the convexity of the moving objects andsplit by the so-called dividing line of the occlusion region. Then the divided objects are classified by evaluating their normalizedsize. If the object is not partially occluded, its width and the ratio between length and width is extracted to detect if it is a fullocclusion and classify it by developing a hierarchical classifier. The proposed method has been evaluated to see if the results are satisfying. Experimental results exhibit that the method is efficiently able to classify vehicles and process occlusions

Vision based traffic monitoring, vehicle detection,vehicle classification, occlusion detection, occlusion resolving