MARCH 1998 | Chenyang Xu, Student Member, IEEE, and Jerry L. Prince, Senior Member, IEEE
This paper introduces a new external force model for active contours, called Gradient Vector Flow (GVF), which addresses the limitations of traditional snake models in computer vision and image processing. GVF is computed as a diffusion of the gradient vectors of an edge map derived from the image, differing fundamentally from traditional snake external forces that are the negative gradient of a potential function. The GVF snake is formulated directly from a force balance condition rather than a variational formulation. The paper demonstrates that GVF has a large capture range and can move snakes into boundary concavities, overcoming the issues of initialization and convergence to boundary concavities. The authors provide theoretical foundations, numerical implementation details, and several examples to illustrate the effectiveness of GVF in various scenarios, including 2D and 3D images. The paper concludes with a discussion on future research directions, including the characterization of GVF's capture range and the optimization of its parameters.This paper introduces a new external force model for active contours, called Gradient Vector Flow (GVF), which addresses the limitations of traditional snake models in computer vision and image processing. GVF is computed as a diffusion of the gradient vectors of an edge map derived from the image, differing fundamentally from traditional snake external forces that are the negative gradient of a potential function. The GVF snake is formulated directly from a force balance condition rather than a variational formulation. The paper demonstrates that GVF has a large capture range and can move snakes into boundary concavities, overcoming the issues of initialization and convergence to boundary concavities. The authors provide theoretical foundations, numerical implementation details, and several examples to illustrate the effectiveness of GVF in various scenarios, including 2D and 3D images. The paper concludes with a discussion on future research directions, including the characterization of GVF's capture range and the optimization of its parameters.