Title :
An Improved C-V Image Segmentation Method Based on Level Set Model
Author :
Xu, Lingling ; Xiao, Jinsheng ; Yi, Benshun ; Lou, Lijun
Author_Institution :
Sch. of Electron. Inf., Wu han Univ., Wuhan
Abstract :
Image segmentation method based on Chan-Vese level set model has wide potential application. However its complex computing restricts its application. In order to improve the speed of image segmentation, this paper presents a new level set initialization method on Chan-Vese level set model. After a simple iterative, we can separate out the outline of objects. Experiments show that the method is simple and efficient, with good separation effects.
Keywords :
image segmentation; Chan-Vese level set model; improved C-V image segmentation method; level set initialization method; Active contours; Capacitance-voltage characteristics; Computer applications; Data mining; Deformable models; Image segmentation; Intelligent networks; Intelligent systems; Level set; Solid modeling; C-V method; Level set; image processing; image segmentation;
Conference_Titel :
Intelligent Networks and Intelligent Systems, 2008. ICINIS '08. First International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3391-9
Electronic_ISBN :
978-0-7695-3391-9
DOI :
10.1109/ICINIS.2008.127
