A modified color image segmentation method based on FCM and region merging

A new color image segmentation algorithm based on histogram, FCM clustering, and region merging is proposed in this paper. First, the RGB space is transformed to HSV space, and the image is divided into non-singular points and singular points in accordance with the saturation. Second, characteristics of the image pixel are mapped to the one-dimensional histogram, we can determine the number of the cluster and the initial cluster center thought peaks selection algorithm, non-singular points and singular points are separately clustering by FCM,. Finally, we merger regions by image spatial information to eliminate the scattered small area after clustering, which overcomes the over-segmentation problem in FCM, and increases the ability of anti-noise. Experimental results show that this method not only can make the partition consistent with the human visual psychology, but also overcome the singularity of HSV space, and significantly reduce computational complexity and greatly improve the speed of the algorithm, realize automatically dividing images without manual intervention.