Unsupervised foreground segmentation using background elimination and graph cut techniques

Abstract

A simple and unsupervised approach to segmenting foreground regions is proposed. This is a novel method for extracting foreground regions from still images by background elimination and graph cut techniques. To extract foreground regions effectively, a new method of background elimination is proposed to detect candidate object regions and a graph cut is used to extract exact foregrounds from the candidate object regions. Experimental results have shown that the proposed method achieves better performance of foreground extraction than existing methods under various environments containing multiple objects and clutter backgrounds in natural images.