A New Color Image Segmentation Algorithm Combining Mean Shift and Hierarchical Clustering ?

A new color image segmentation method combining mean shift and hierarchical clustering algorithm is presented in this paper. The proposed algorithm preprocesses an input image by mean shift algorithm to form segmented regions that preserve the desirable discontinuity characteristics of image. The number of segmented regions, instead of the number of image pixels, is considered as the input data scale of hierarchical clustering algorithm. On the stage of hierarchical clustering, the average of the color vectors in each region is considered as a cluster. The proximity between each cluster is calculated to form the proximity matrix, and then ward algorithm is employed to obtain the final segmentation results. Experimental results illustrate that the proposed algorithm has superior performance and less computational costs compared to the traditional clustering algorithm.