标题：Image segmentation by level set evolution with region consistency constraint
作者：Zhong Li;Zhou Yuanfeng;Zhang Xiaofeng;Guo Qiang;Zhang Caiming
作者机构：[Zhong, L] School of Computer Science and Technology, Shandong University, Jinan, 250101, China, School of Information and Electrical Engineering, Lud 更多
通讯作者地址：[Zhang, CM]Shandong Univ, Sch Comp Sci & Technol, Jinan 250101, Shandong, Peoples R China;[Zhang, CM]Ludong Univ, Sch Informat & Elect Engn, Yantai 26 更多
关键词：level set evolution;image segmentation;uniformity testing;multiple level contours;region consistency constraint
摘要：Image segmentation is a key and fundamental problem in image processing,computer graphics,and computer vision.Level set based method for image segmentation is used widely for its topology flexibility and proper mathematical formulation.However,poor performance of existing level set models on noisy images and weak boundary limit its application in image segmentation.In this paper,we present a region consistency constraint term to measure the regional consistency on both sides of the boundary,this term defines the boundary of the image within a range,and hence increases the stability of the level set model.The term can make existing level set models significantly improve the efficiency of the algorithms on segmenting images with noise and weak boundary.Furthermore,this constraint term can make edge-based level set model overcome the defect of sensitivity to the initial contour.The experimental results show that our algorithm is efficient for image segmentation and outperform the existing state-of-art methods regarding images with noise and weak boundary.