强激光与粒子束2012，Vol.24Issue(12)：2817-2821,5.DOI:10.3788/HPLPB20122412.2817
基于C-V模型的改进快速水平集图像分割法
Improved image segmentation method based on fast level set and C-V model
摘要
Abstract
Aim at solving the problem that the high computational complexity of level set methods excludes themselves from many real-time applications, an improved image segmentation method based on the fast level set algorithm is proposed in this paper. The proposed algorithm adopts an improved fast level set with a single list to realize the curve evolution, and it uses the binary fitting terms of the C-V model to design the speed function of curve evolution, preserving the global optimization characteristic of the C-V model. In addition, a termination criterion based on the number changing of contour points in the single list is proposed to ensure that the evolving curve can automatically stop on the true boundaries of objects. Experimental results show that the proposed algorithm can significantly improve the segmentation speed and can efficiently segment the noisy images.关键词
C-V模型/单链表/快速水平集算法/图像分割Key words
C-V model/ single list/ fast level set algorithm/ image segmentation分类
信息技术与安全科学引用本文复制引用
徐东,彭真明..基于C-V模型的改进快速水平集图像分割法[J].强激光与粒子束,2012,24(12):2817-2821,5.基金项目
中国科学院光束控制重点实验室基金项目(2010LBC001) （2010LBC001）
总装预研基金项目(9140A01060108DZ02) （9140A01060108DZ02）
航空科学基金项目(20060112116) （20060112116）
中央高校基本科研业务费专项资金项目(ZYGX2010J063) （ZYGX2010J063）
