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