Feature space based image segmentation via density modification

Feature space based approaches have been the most popular ones among those used to perform image segmentation. In this paper, a density modification framework is proposed in order to aid feature space based segmentation in images. The framework embeds a position-dependent property associated with each sample in the feature space of an image into the corresponding density map and hence modifies it. The property association and embedding operations in the framework is implemented using a fuzzy set theory based system devised with cue from beam theory of solid mechanics and the appropriateness of this approach is established. Experimental results of segmentation in images are given to demonstrate the effectiveness of the proposed framework.