DocumentCode :
1544964
Title :
Image Segmentation Using Active Contours With Normally Biased GVF External Force
Author :
Wang, Yuanquan ; Liu, Lixiong ; Zhang, Hua ; Cao, Zuoliang ; Lu, Shaopei
Author_Institution :
Beijing Lab. of Intell. Inf. Technol., Beijing Inst. of Technol. (BIT), Beijing, China
Volume :
17
Issue :
10
fYear :
2010
Firstpage :
875
Lastpage :
878
Abstract :
Gradient vector flow (GVF) is an effective external force for active contours, but its isotropic nature handicaps its performance. The recently proposed NGVF model is anisotropic since it only keeps the diffusion along the normal direction of the isophotes; however, it is sensitive to noise and could erase weak boundaries. In this letter, the normally biased GVF (NBGVF) external force is proposed for snake models, which keeps the diffusion along the tangential direction of the isophotes and biases that along the normal direction. The biasing weight approaches zero at boundaries and is 1 in homogeneous regions. Consequently, the NBGVF snake can preserve weak edges and smooth out noise while maintaining other desirable properties of GVF and NGVF snakes such as enlarged capture range, insensitivity to initialization and convergence to u-shape concavity. These properties are evaluated on synthetic and real images.
Keywords :
gradient methods; image segmentation; NBGVF external force; NGVF model; active contours; gradient vector flow; image segmentation; normally biased GVF external force; u-shape concavity; Active contours; Anisotropic magnetoresistance; Convergence; Educational technology; Image restoration; Image segmentation; Information technology; Level set; Partial response channels; Solid modeling; Active contour; NGVF; gradient vector flow; image segmentation; normally biased gradient vector flow;
fLanguage :
English
Journal_Title :
Signal Processing Letters, IEEE
Publisher :
ieee
ISSN :
1070-9908
Type :
jour
DOI :
10.1109/LSP.2010.2060482
Filename :
5518389
Link To Document :
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