A technique of three-level thresholding based on probability partition andfuzzy 3-partition

Thresholding is a commonly used technique in image segmentation. Selecting the correct thresholds is a critical issue. In this paper, the relationship between a probability partition (PP) and a fuzzy c-partition (FP) in thres holding is given. This relationship and the entropy approach are used to de rive a thresholding technique to select the best fuzzy c-partition. The mea sure of the selection quality is the compatibility between the FP and the P P generated by the problem. An entropy function defined by the PP and FP is used to measure the compatibility. A necessary condition of the entropy fu nction arriving at a maximum is derived. Based on this condition, an effici ent algorithm for three-level thresholding is deduced. Experiments to verif y the efficiency of the proposed method and comparison to some existing tec hniques are also presented. The experiment results show that our proposed m ethod gives the best performance in three-level thresholding using fuzzy c- partition.