Title :
Variational image segmentation on implicit surface using Split-Bregman method
Author :
Wang, Qi ; Wei, Weibo ; Pan, Zhenkuan
Author_Institution :
Coll. of Inf. Eng., Qingdao Univ., Qingdao, China
Abstract :
The coupling images and their underlying surfaces results in complex implementation and low computing efficiency of image segmentation on surfaces. For the piecewise constant and smooth image segmentation on surface, the traditional Chan-Vese models are transformed to variational level set models on implicit surfaces and computed by using fast Split-Bregman methods in this paper. Additionally, the Split-Bregman methods are implemented based on the corresponding globally convex models to avoid the effects of contour initialization in segmentation results. Comparisons of experiment results validate the superiority of the models and algorithms presented in this paper.
Keywords :
computer vision; image denoising; image segmentation; Chan-Vese models; Split-Bregman method; complex implementation; computing efficiency; contour initialization; convex models; coupling images; implicit surface; piecewise constant; variational image segmentation; Computer vision; Educational institutions; Image processing; Image reconstruction; Image segmentation; Level set; Minimization methods; Skin; Surface reconstruction; Surface texture; Chan-Vese model; Image segmentation; Split-Bregman method; implicit surface; variational methods;
Conference_Titel :
Image Analysis and Signal Processing (IASP), 2010 International Conference on
Conference_Location :
Zhejiang
Print_ISBN :
978-1-4244-5554-6
Electronic_ISBN :
978-1-4244-5556-0
DOI :
10.1109/IASP.2010.5476101