DocumentCode :
1936323
Title :
Active Contour Model based on Dynamic Extern Force and Gradient Vector Flow
Author :
Hongguang Fu ; Rongqiu Wu ; Weimin Wang
Author_Institution :
Sch. of Comput. Sci. & Eng., UESTC, Chengdu
Volume :
1
fYear :
2008
fDate :
27-30 May 2008
Firstpage :
863
Lastpage :
867
Abstract :
Active contour model, or snakes, are used extensively in digital image processing, particularly to locate object boundary, the model include geometric and parametric active models. Problems associated with initialization and convergence restrict their utility, which have been solved by Xu, who proposed gradient vector flow. However, parametric active models still face the problem that the whole curve may evolve into only a side of the true boundary. This paper presents a new approach based on the parametric active models with generalized gradient vector flow (GGVF) and dynamic extern force, which decreases when iterative number increases and thus makes terminal contour less dependent on the initial curve and it can speed up the iterate process. The image edge and the field that point to round from center decide the initial extern force, which can prevent curve evolution from possible wrong segmentation. The tongue edge can be detected faster and more accurately than ever in the tongue image experiments.
Keywords :
edge detection; gradient methods; image segmentation; medical image processing; object detection; active contour model; digital image processing; dynamic extern force; generalized gradient vector flow; image segmentation; iterative number; object boundary detection; parametric active models; snakes model; tongue edge detection; Active contours; Biomedical engineering; Computer applications; Digital images; Equations; Gray-scale; Image edge detection; Image segmentation; Solid modeling; Tongue;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
BioMedical Engineering and Informatics, 2008. BMEI 2008. International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-0-7695-3118-2
Type :
conf
DOI :
10.1109/BMEI.2008.252
Filename :
4548794
Link To Document :
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