Spatial improved fuzzy c-means clustering for image segmentation - Feng Zhao; Licheng Jiao (2011 International Conference on Electronic and Mechanical Engineering and Information Technology, 2011)
The generalized fuzzy c-means clustering algorithm with improved fuzzy partition (GFCM) is a new modified version of the fuzzy c-means clustering algorithm (FCM). GFCM under appropriate parameters can converge more rapidly than FCM. However, GFCM, similar to FCM, is sensitive to noise in normal gray-level images. In order to overcome this problem, a novel fuzzy segmentation algorithm called spatial improved fuzzy c-means clustering algorithm (IFCM_S) is proposed in this paper. In IFCM_S, a spatial constraint term is introduced into the objective function of GFCM, and the center and membership function update equations are also presented. Experiments on synthetic and synthetic aperture radar (SAR) images, show that the proposed method behaves well in segmentation performance and speed.