DocumentCode
3109219
Title
The GVF Snake with a Minimal Path Approach
Author
Sun, Chensheng ; Lam, Kin-Man
Author_Institution
Hong Kong Polytech. Univ., Hong Kong
fYear
2007
fDate
11-13 July 2007
Firstpage
223
Lastpage
228
Abstract
In this paper we propose a contour extraction method based on the active contour model, which uses the GVF snake to obtain the initial segments for a contour; and then a minimal path method for the refinement stage, to obtain an accurate and more robust result. By employing the minimal path method to find missing segments between pairs of nodes defined on the contour obtained by the GVF snake, our algorithm is able to detect deep concave parts of object boundary, and works well even when the snake initialization is not very good.
Keywords
edge detection; feature extraction; image segmentation; object detection; GVF snake method; contour extraction; edge detection; image segmentation; minimal path method; object boundary detection; Active contours; Data mining; Deformable models; Digital images; Image edge detection; Object detection; Robustness; Signal processing; Signal processing algorithms; Sun;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Information Science, 2007. ICIS 2007. 6th IEEE/ACIS International Conference on
Conference_Location
Melbourne, Qld.
Print_ISBN
0-7695-2841-4
Type
conf
DOI
10.1109/ICIS.2007.178
Filename
4276385
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