Based on Watershed Transform and Fuzzy C Means Clustering Algorithm for Color Image Segmentation
For the watershed algorithm is very sensitive to weak edges and noise,thus in the watershed algorithm is applied to image segmentation prone to over-segmentation. A new color image segmentation algorithm basing on watershed transformation and a fuzzy C mean (FCM) clustering algorithm are proposed. In this algorithm,watershed segmentation is carried on image,and then clusters and mergers the over-segmentation generated by the watershed ,during the merging process using the degree of sector differences and the region area to determine the cluster number of FCM. The advantage of this algorithm is to solve over-segmentation problems caused by watershed transformation algorithm aud meanwhile solve problems which are difficult to determine the initial value and cluster centers of FCM algorithm. Experimental results show that the algorithm can segment the target accurately and apply to automatic segmentation system.
NETL
NSTL
万方数据
维普
