A new active contour model: Curvature gradient vector flow

被引：0

作者：

Ning, JF ^{[1
]}

Wu, CK

Liu, SG

Wen, PZ

机构：

[1] Xidian Univ, Natl Key Lab ISN, Xian 710071, Peoples R China

[2] NW A&F Univ, Coll Informat Engn, Yangling 712100, Peoples R China

来源：

COMPUTER VISION - ACCV 2006, PT I | 2006年 / 3851卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：633 / 642

页数：10

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