Fuzzy-Decision-based Segmentation Approach for Detecting Region of Interest

Many clustering strategies have been used, such as the hard clustering scheme and the fuzzy clustering scheme, each of which has its own special characteristics. The conventional hard clustering method restricts each point of the data set to exclusively just one cluster. As a consequence, with this approach the segmentation results are often very crisp, i.e., each pixel of the image belongs to exactly just one class. In this paper we have considered the fuzzy decision based clustering approach for finding the objects of interest. The methodology is basically the parameter based clustering where the regions are divided based on the parameter value which develops the regions of interest. The proposed methodology is test on the benchmark datasets and evaluated with different measures for performance analysis.