A Novel Approach to Object/Background Segmentation Based on the Probabilistic Graphical Model
Graph cut as a powerful optimization technique for minimizing MRF (Markov Random Field) 12 energy functions has been successfully applied to image segmentation. In this paper, we adopt an MRF model for object/background segmentation. The theoretical framework is based on maximum a posterior estimation via the graph-cut energy optimization method. Parameters are estimated with a novel parameter estimation algorithm. The novel parameter estimation algorithm is a variant of the expectation maximization (EM) algorithm 1, 5 with prior influence factors. Characteristic features related to the information in color, texture and position are extracted for each pixel. Experimental results demonstrate the effectiveness of our approach.
Qiuxu Li Jieyu Zhao
Research Institute of Computer Science and Technology, Ningbo University, Ningbo 315211, China
国际会议
The Fifth International Conference on Image and Graphics(第五届国际图像图形学学术会议 ICIG 2009)
西安
英文
162-167
2009-09-20（万方平台首次上网日期，不代表论文的发表时间）