Image segmentation using a fuzzy roughness measure

Abstract

Measures of uncertainty are highly useful for determining the information content of a system. In this paper, new measures of information on fuzzy approximation spaces are introduced based on divergence measures of fuzzy sets. The proposed fuzzy rough uncertainty measure is used to develop an algorithm for histogram based foreground background segmentation of a grey level image and it is experimented with twelve standard test images. It is observed that the overlapping of the foreground background pixels in the images segmented using the proposed method is lesser than those produced by OTSU and FCM methods. The segmented images are compared using their root mean square error values.