Boundary Segmentation Based on Improved GVF Snake Model

Wen Bo Huang; Yang Yan; Yun Ji Wang

doi:10.4028/www.scientific.net/AMR.756-759.3920

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 756-759Boundary Segmentation Based on Improved GVF Snake...

Boundary Segmentation Based on Improved GVF Snake Model

Abstract:

The gradient vector flow (GVF) Snake models are active contour models: they lock onto nearby edges, localizing them accurately. GVF refers to the definition of a bidirectional external force that can capture the object boundaries from either sides and can deal with concave regions. However, we find that there is a main disadvantage of GVF Snakes---- there are some critical points in the model, the critical points must be included in the initial contour or must not be contained internal, and otherwise, it could not converge to the correct boundary. To solve this problem, we propose an improved GVF Snake model: we construct a new driving force to improve the initialization of contour. The experimental result shows that the new model we proposed not only avoid the critical points of the initial contour, but also converge to the concave boundary better.

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Periodical:

Advanced Materials Research (Volumes 756-759)

Pages:

3920-3923

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.756-759.3920

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Online since:

September 2013

Authors:

Wen Bo Huang, Yang Yan, Yun Ji Wang

Keywords:

Active Contour Models, Concavities Boundary Detection, Gradient Vector Flow (GVF) Snake, Image Segmentation

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