Cast Shadow Detection and Removal of Moving Objects from Video Based on HSV Color Space

Abstract

In the process of segmentation and tracking of moving object, shadow area leads to false detection of object. Shadows are also reason for loss of background texture and false connectivity of independent blobs. Hence, we propose a simple method to detect a moving object’s cast shadow and remove the shadow region from video frames. Initially, we store all the background information in reference frame. The next incoming frames with object are compared with this frame. In order to extract the moving object, we used subtraction algorithm. We used homogeneity property by image division, color variation in RGB color space and statistics of intensity in V channel of HSV color space to detect the shadow region. Finally shadow removal is done based on the information from the reference frame. The most noticeable feature of our proposed method is that it can detect shadows both in indoor and outdoor scenarios and there is no harsh transition after removal of the shadow. Color information for both background subtraction and shadow detection to improve object segmentation is ensured in this paper. Experimental results show that the proposed method is simple to understand, can detect and remove shadow and extract the moving object properly.