Improved Shadow Removal Algorithm for Vehicle Classification in Traffic Surveillance System

Abstract

Shadows are among the most critical problems for traffic surveillance systems (TSSs). In a TSS, shadow regions significantly affect the extraction of vehicles’ attributes for vehicle detection, classification and tracking. Although many methods have been proposed to address this key problem, the dilemma of accurate shadow removal with vehicles’ boundaries recovery and real-time processing still poses as a great challenge. In this paper, we propose a new method for shadow removal that utilizes edge features to eliminate shadows, and to refine vehicles’ images regardless of the changes in illumination and shadow orientations. Experiments were done on real-world data to compare the results of our method with previous ones. Thorough investigation shows that our method gets rid of vehicles’ shadows more accurately and significantly restores conveyances’ images from shadow separation. In addition, our method is real-time.