DocumentCode :
3278677
Title :
The improvement of GAC model for image segmentation
Author :
Qiang Wang
Author_Institution :
Sch. Of Software, Univ. of Sci. & Technol. Liao Ning, Anshan, China
fYear :
2013
fDate :
23-25 May 2013
Firstpage :
1021
Lastpage :
1024
Abstract :
An Adaptive image segmentation algorithm based on geometric active contour (GAC) model was presented in this paper in order to solve the problem that tradition GAC model can not segment adaptively. By combining the regional information to construct energy functional description area information. We propose an improved adaptive image segmentation algorithm, This algorithm combines the advantages of GAC model and C-V model effectively, Regional energy functional could determine the evolution speed to replace the constant evolution speed in traditional GAC model. Experimental results showed that the proposed algorithm is feasible, and reaches an obvious effect in terms of boundary leaking.
Keywords :
computational geometry; image segmentation; GAC model; adaptive image segmentation algorithm; energy functional description area information; geometric active contour model; regional energy function; Gold; Boundary leaking; GAC model; Image segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2013 4th IEEE International Conference on
Conference_Location :
Beijing
ISSN :
2327-0586
Print_ISBN :
978-1-4673-4997-0
Type :
conf
DOI :
10.1109/ICSESS.2013.6615480
Filename :
6615480
Link To Document :
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