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The Scientific World Journal
Volume 2013, Article ID 479675, 8 pages
Research Article

Improved Algorithm for Gradient Vector Flow Based Active Contour Model Using Global and Local Information

1School of Computer, Wuhan University, Wuhan, Hubei 430072, China
2Suzhou Institute of Wuhan University, Suzhou, Jiangsu 215123, China
3Department of Neurosurgery, University of Pittsburgh, Pittsburgh, PA 15213, USA

Received 1 August 2013; Accepted 20 August 2013

Academic Editors: C.-C. Chang and F. Yu

Copyright © 2013 Jianhui Zhao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Active contour models are used to extract object boundary from digital image, but there is poor convergence for the targets with deep concavities. We proposed an improved approach based on existing gradient vector flow methods. Main contributions of this paper are a new algorithm to determine the false part of active contour with higher accuracy from the global force of gradient vector flow and a new algorithm to update the external force field together with the local information of magnetostatic force. Our method has a semidynamic external force field, which is adjusted only when the false active contour exists. Thus, active contours have more chances to approximate the complex boundary, while the computational cost is limited effectively. The new algorithm is tested on irregular shapes and then on real images such as MRI and ultrasound medical data. Experimental results illustrate the efficiency of our method, and the computational complexity is also analyzed.