A shadow removal algorithm for vehicle detection based on reflectance ratio and edge density

Automatic vehicle detection systems in urban and inter-urban traffic using computer vision are frequently based on background subtraction methods. Moving shadows represent a serious difficulty for these methods, as they will appear as part of the segmented foreground vehicles. Shadow removal algorithms usually rely on exploiting color properties. However, the use of image color information, when available, is more computationally demanding and it may compromise many real-time implementations. This paper proposes a shadow removal algorithm, suitable for background subtraction methods, where only grayscale information is required. The method is based on edge density computation on a quotient image, obtained from the current frame and the background model. Experimental results from various traffic scenes are provided in order to prove the validity of the proposed method.