A robust approach for background subtraction with shadow removal for moving object detection

Abstract

Background subtraction is the primary step that can be applied in numerous applications, including object tracking, surveillance, robot vision, object-based coding, image database and video teleconferencing. However, background subtraction approaches are very sensitive to dynamic scene changes. This paper aims to investigate ways to exploit the characteristics of the wavelet domain to improve moving object segmentation using background subtraction for object tracking applications. In this paper, we also innovate by using a high frequency sub-band to neutralise the negative influences caused by cast shadow, without using any colour information. The state-of-theart performance of the proposed approach is illustrated by using both indoor and outdoor video sequences.