Abstract
A novel external force field for active contours, called gradient vector flow based on anisotropic diffusion (ADGVF), is proposed in this paper. The generation of ADGVF contains an anisotropic diffusion process that the diffusion in the tangent and normal directions to the isophote lines has different diffusion speeds which are locally adjusted according the local structures of the image. The proposed method can address the problem associated with poor convergence of gradient vector flow in the normal direction (NGVF) to the long, thin boundary indentations and the openings of the boundaries. It can improve active contour convergence to these positions. In its numerical implementation, an efficient numerical schema is used to ensure sufficient numerical accuracy. Experimental results demonstrate that ADGVF has better performance in terms of accuracy, efficiency and robustness that that of NGVF.
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Yu, X., Wu, C., Chen, D., Zhou, T., Jia, T. (2012). Gradient Vector Flow Based on Anisotropic Diffusion. In: Wang, J., Yen, G.G., Polycarpou, M.M. (eds) Advances in Neural Networks – ISNN 2012. ISNN 2012. Lecture Notes in Computer Science, vol 7368. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31362-2_19
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DOI: https://doi.org/10.1007/978-3-642-31362-2_19
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