Fuzzy Sets Theory Based Region Merging for Robust Image Segmentation

A fuzzy set theory based region merging approach is presented to tackle the issue of oversegmentation from the watershed algorithm, for achieving robust image segmentation. A novel hybrid similarity measure is proposed as the merging criterion, based on the region-based similarity and the edge-based similarity. Both similarities are obtained using the fuzzy set theory. To adaptively adjust the influential degree of each similarity to region merging, a simple but effective weighting scheme is employed with the weight varying as region merging proceeds. The proposed approach has been applied to various images, including gray-scale images and color images. Experimental results have demonstrated that the proposed approach produces quite robust segmentations.