Robust Object Segmentation using Adaptive Thresholding

This paper proposes a robust object segmentation algorithm that tackles problems that arise in environments in which the foreground and background colours are similar and there is light reflection in the shadow areas. The proposed algorithm bases its efficiency on a novel RGB colour detection process with adaptive threshold and edge detection, which are combined in order to obtain a foreground map containing objects and shadows. Subsequently, edge information is used to remove the shadow regions that are out of the edge bounding boxes. Finally, a post-processing procedure is applied and, for offline detection, a temporal filter is included in order to retrieve the misclassified pixels. The experimental results demonstrate the superior performance of our algorithm in comparison to other existing methods.