Auto-segmentation based on graphcut and template

Hong Zhang; Wei Zuo; Ying Mu

doi:10.1117/12.751267

15 November 2007 Auto-segmentation based on graphcut and template

Hong Zhang, Wei Zuo, Ying Mu

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67864W (2007) https://doi.org/10.1117/12.751267
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

In this paper, the main idea is to use the prior knowledge to guide the segmentation. Firstly the continuity among adjacent frames is used to create a motion template according to the Displaced Frame Difference's (DFD) higher character . And then the color template is established by using the k-means clustering. Based upon the information derived from the previous two templates, the segmentation image is defined as foreground, background and boundary regions. Then, the segmentation problem is formulated as an energy minimization problem. The hard edge of foreground is then obtained by implementing graph-cut algorithm. Experimental results demonstrate the effectiveness of proposed algorithm.

Citation Download Citation

Hong Zhang, Wei Zuo, and Ying Mu "Auto-segmentation based on graphcut and template", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67864W (15 November 2007); https://doi.org/10.1117/12.751267

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