Image Segmentation Based on GC-CV

In this article, an integrated method, named GC-CV, was developed and applied to image segmentation. The proposed method combines graph cut method and the simplified Mumford-Shah model (C-V model), and takes the advantages of both. In this paper, the proposed GC-CV method is put to test in its three different operational modes. The first mode is the segmentation of binary images using GC-CV directly. The second mode is the segmentation of multi-region images by recursive GC-CV. The last one is segmentation of color images and gray images by combining GC-CV with EM algorithm, and using YCbCr color space for color image segmentation. The feasibility and effectiveness of the proposed GC-CV method is verified by a serious of experiments. Experimental results show that the speed of segmentation can be greatly improved and the number of iterations can be considerably reduced with GC-CV in comparison with C-V model. Experimental results reveal that GC-CV can be a promising approach to image segmentation.