A new image segmentation algorithm combining region growing with C-means Clustering is proposed based on human visual model. Initial seeds are selected automatically and the similarity principle of region growing is adjusted adaptively according to human visual threshold effect. By considering the global influence of region growing to error sum of squares

as well as the local similarity information of seeds’ neighborhood

the proposed algorithm can limit seeds to grow within object boundaries. Experimental results show that the proposed method can produce better segmentation performance with less computational complexity than traditional methods.