Image Segmentation Using Co-EM Strategy

Inspired by the idea of multi-view, we proposed an image segmentation algorithm using co-EM strategy in this paper. Image data are modeled using Gaussian Mixture Model (GMM), and two sets of features, i.e. two views, are employed using co-EM strategy instead of conventional single view based EM to estimate the parameters of GMM. Compared with the single view based GMM-EM methods, there are several advantages with the proposed segmentation method using co-EM strategy. First, imperfectness of single view can be compensated by the other view in the co-EM. Second, employing two views, co-EM strategy can offer more reliability to the segmentation results. Third, the drawback of local optimality for single view based EM can be overcome to some extent. Fourth, the convergence rate is improved. The average time is far less than single view based methods. We test the proposed method on large number of images with no specified contents. The experimental results verify the above advantages, and...

• Type: Conference
• Year: 2007
• Where: ACCV
• Authors: Zhenglong Li, Jian Cheng, Qingshan Liu, Hanqing Lu
• Keywords: ACCV 2007, Co-EM Strategy, Computer Vision, Single View, View Based Em