Abstract：To overcome the over segmentation phenomenon of edgeflow-driven anisotropic diffusion (EFD) and the high computational complexity of normalized cut (NCut) , a color image segmentation algorithm based on EFD and NCut is presented. EFD is applied to the image to get a preliminary result. Then, the segmented regions are taken as nodes to construct a weighted undirected graph G, and the NCut is applied to perform globally optimized clustering. Segmentation results are achieved after proper post-process. The graph structure is based on segmented regions instead of image pixels, and thus the proposed algorithm requires lower computational complexity. In addition, EFD focuses on local detail while NCut captures global property, so this algorithm combines both advantages. Experimental results show that this algorithm can get appropriate segmentation results.
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2010, Vol. 23 
