Title :
A variable-domain approach for image segmentation based on statistical models
Author :
Gao, Xiaoliang ; Liu, Jiwei ; Wang, Zhiliang ; Wang, Xiao
Author_Institution :
Sch. of Inf. Eng., Univ. of Sci. & Technol. Beijing, Beijing, China
Abstract :
In this paper, a novel variable-domain approach to curve evolution for image segmentation was proposed, being based on a statistical active contour model using level sets. The essential idea is to re-define the computing domain in image repeatedly, by separating the segmentation procedure into several individual phases, for images composed of an infinite number of regions. By our algorithm, the work can be done automatically without manual intervention. Moreover, the accuracy and rapidity can be enhanced effectively for the objects with complicated topology.
Keywords :
curve fitting; image segmentation; set theory; statistical analysis; curve evolution; image segmentation; level sets; manual intervention; segmentation procedure; statistical active contour model; statistical models; variable-domain approach; Active contours; Biomedical imaging; Computed tomography; Electronic mail; Gold; Image segmentation; Level set; Magnetic resonance imaging; Statistics; Topology; active contour; image segmentation; level sets; neighborhood replacement; statistical models; variable-domain;
Conference_Titel :
Advanced Computer Control (ICACC), 2010 2nd International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-5845-5
DOI :
10.1109/ICACC.2010.5486955
