A fuzzy clustering algorithm for image segmentation using dependable neighbor pixels

In this paper, a fuzzy clustering algorithm using dependable neighbor pixels is proposed for image segmentation. In order to enhance the segmentation performance, the proposed algortihm utilizes the local statistical information to discriminate dependable neighbor pixels from undependable neighbor pixels, and then allows the labeling of the pixel to be influenced by the dependable neighbor pixels. This algorithm has two advantages: (1) the spatial information with high reliability is incorporated into the objective function so that the segmentation accuracy is guaranteed; (2) the intensity of the spatial constraints is automatically determined by the similarity meature so that the segmentation result is adaptive to the original image. The efficiency of the proposed algorithm is demonstrated by extensive segmentation experiments using both synthetic and real images.