Generalized gradient vector flow external forces for active contours

被引:479
作者
Xu, CY [1 ]
Prince, JL [1 ]
机构
[1] Johns Hopkins Univ, Dept Elect & Comp Engn, Image Anal & Commun Lab, Baltimore, MD 21218 USA
关键词
D O I
10.1016/S0165-1684(98)00140-6
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Active contours, or snakes, are used extensively in computer vision and image processing applications, particularly to locate object boundaries. A new type of external force for active contours, called gi adient vector flow (GVF) was introduced recently to address problems associated with initialization and poor convergence to boundary concavities. GVF is computed as a diffusion of the gradient vectors of a gray-level or binary edge map derived from the image. In this paper, we generalize the GVF formulation to include two spatially varying weighting functions. This improves active contour convergence to long, thin boundary indentations, while maintaining other desirable properties of GVF, such as an extended capture range. The original GVF is a special case of this new generalized GVF (GGVF) model. An error analysis for active contour results on simulated test images is also presented. (C) 1998 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:131 / 139
页数:9
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