Generalized Newton Method for Minimization of A Region-based Active Contour Model

摘要：

　　PED-based image segmentation based on the active contour model attracts many researchers due to the high precision of edge detection and the continuity of boundaries.Its basic idea is to define an energy functional on a dynamic curve which achieves its minimum when the curve conforms to the boundary of the objects.The most widely used optimization method is the gradient-descent method.However,the convergence of the gradient-descent method is very poor.In this paper,the effectiveness of the generalized Newton method is investigated by using it to minimize the energy functional of the RSF&CV model,which is a simple combination of the CV model and the RSF model.The experimental results show the accuracy and efficiency with robustness in noise.

关键词： generalized newton region-based active contour image segmentation

作者: Haiping Xu Meiqing Wang Choi-Hong Lai

作者单位: College of Mathematics and Computer Science Fuzhou University Fuzhou,Fujian,China School of Computing and Mathematical Sciences University of Greenwich London,UK

会议类型: 国际会议

会议名称: The 12th International Symposium on Distributed Computing and Applications to Business,Engineering and Science(DCABES 2013)(第十二届分布式计算及其应用国际学术研讨会)

会议地点: 英国伦敦

会议语种:英文

页码: 229-233

在线出版日期: 2013-09-02（万方平台首次上网日期，不代表论文的发表时间）