A Variable-Domain Approach for Image Segmentation Based on Statistical Models

摘要：

In this paper, a novel variable-domain approach to curve evolution for image segmentation was proposed, being based on a statistical active contour model using level sets. The essential idea is to re-define the computing domain in image repeatedly, by separating the segmentation procedure into several individual phases, for images composed of an infinite number of regions. By our algorithm, the work can be done automatically without manual intervention. Moreover, the accuracy and rapidity can be enhanced effectively for the objects with complicated topology.

关键词： active contour variable-domain statistical models neighborhood replacement image segmentation level sets

作者: Xiaoliang Gao Jiwei Liu Zhiliang Wang Xiao Wang

作者单位: School of Information Engineering University of Science and Technology Beijing Beijing China

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 144-147

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）