Advection-Enhanced Gradient Vector Flow for Active-Contour Image Segmentation

Advection-Enhanced Gradient Vector Flow for Active-Contour Image Segmentation

Year:    2019

Communications in Computational Physics, Vol. 26 (2019), Iss. 1 : pp. 206–232

Abstract

In this paper, we propose a new gradient vector flow model with advection enhancement, called advection-enhanced gradient vector flow, for calculating the external force employed in the active-contour image segmentation. The proposed model is mainly inspired by the functional derivative of an adaptive total variation regularizer whose minimizer is expected to be able to effectively preserve the desired object boundary. More specifically, by incorporating an additional advection term into the usual gradient vector flow model, the resulting external force can much better help the active contour to recover missing edges, to converge to a narrow and deep concavity, and to preserve weak edges. Numerical experiments are performed to demonstrate the high performance of the newly proposed model.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/cicp.OA-2018-0068

Communications in Computational Physics, Vol. 26 (2019), Iss. 1 : pp. 206–232

Published online:    2019-01

AMS Subject Headings:    Global Science Press

Copyright:    COPYRIGHT: © Global Science Press

Pages:    27

Keywords:    Image segmentation active contour gradient vector flow external force.

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