Title :
Split Bregman method for minimization of modified Vese-Chan model for fast image segmentation
Author :
Yunyun Yang ; Yi Zhao ; Boying Wu ; Hongpeng Wang
Author_Institution :
Shenzhen Grad. Sch., Harbin Inst. of Technol., Shenzhen, China
Abstract :
In this paper we present an modified active contour model for fast multiphase image segmentation based on the piecewise constant Vese-Chan model and the split Bregman method. By applying the globally convex image segmentation technique to the piecewise constant Vese-Chan energy functional, we first define a new biconvex energy functional to guarantee fast convergence. Then we incorporate the edge information into the new energy functional with a non-negative edge detector function. Finally, we apply the split Bregman method to fast minimize the new energy functional. Our modified model has been tested with synthetic and real images. Experimental results show that the modified model can obtain similar results to the Vese-Chan model but is much more efficient. Besides, the modified model is robust in the presence of noise.
Keywords :
convex programming; edge detection; image segmentation; minimisation; Vese-Chan energy functional; biconvex energy functional; convex image segmentation technique; edge detector function; edge information; modified Vese-Chan model minimisation; piecewise constant Vese-Chan model; split Bregman method; Computational modeling; Image segmentation; Level set; Mathematical model; Minimization; Noise measurement; Numerical models;
Conference_Titel :
Image and Signal Processing and Analysis (ISPA), 2013 8th International Symposium on
Conference_Location :
Trieste
DOI :
10.1109/ISPA.2013.6703716