A new active contour model: curvature gradient vector flow

Authors:
Jifeng Ning;Chengke Wu;Shigang Liu;Peizhi Wen
Affiliations:
National Key Laboratory of ISN, Xidian University, Xi’an, China;National Key Laboratory of ISN, Xidian University, Xi’an, China;National Key Laboratory of ISN, Xidian University, Xi’an, China;National Key Laboratory of ISN, Xidian University, Xi’an, China
Venue:
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Year:
2006

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Abstract

The paper presents a new external force field for active contour model, which is called CGVF (Curvature Gradient Vector Flow). CGVF improves on classical GVF by simplifying the formulas and increasing the item of curvature, so that the edge information can be kept well and diffused more quickly. Several standard images are used to segmenting experiments, and the results show that CGVF has obvious advantages compared with GVF in the iteration number of force field, the evolvement number of curve and the accuracy of convergence. In particular, when the initial curve is far from the edge of object, the convergence will be more superior.