Automatic Image Segmentation Incorporating Shape Priors via Graph Cuts
In recent years, graph cut has been regarded as an effective discrete optimization method and received increasing attentions in vision community. However, many existing graph cut segmentation algorithms require interactive operations, which are not appropriate for automatic applications. In this paper, we propose an automatic segmentation algorithm via graph cut. Firstly, the data term in traditional graph cut energy is redefined to counteract illumination change. Secondly, shape priors are introduced into segmentation process, which help to obtain more robust results. Finally, an automatic segmentation strategy is presented. Experiments demonstrate that our segmentation algorithm can provide promising results, even when object suffering pixel intensity variation and continuously shape deformation.
Xianpeng Lang Feng Zhu Yingming Hao Qingxiao Wu
Shenyang Institute of Automation,Chinese Academy of Sciences,110016,P.R.China Graduate School of the Shenyang Institute of Automation,Chinese Academy of Sciences,110016,P.R.China
国际会议
2009 IEEE International Conference on Information and Automation(2009年 IEEE信息与自动化国际学术会议)
珠海、澳门
英文
192-195
2009-06-22（万方平台首次上网日期，不代表论文的发表时间）