Title :
Snakes, shapes, and gradient vector flow
Author :
Xu, Chenyang ; Prince, Jerry L.
Author_Institution :
Dept. of Electr. & Comput. Eng., Johns Hopkins Univ., Baltimore, MD, USA
fDate :
3/1/1998 12:00:00 AM
Abstract :
Snakes, or active contours, are used extensively in computer vision and image processing applications, particularly to locate object boundaries. Problems associated with initialization and poor convergence to boundary concavities, however, have limited their utility. This paper presents a new external force for active contours, largely solving both problems. This external force, which we call gradient vector flow (GVF), is computed as a diffusion of the gradient vectors of a gray-level or binary edge map derived from the image. It differs fundamentally from traditional snake external forces in that it cannot be written as the negative gradient of a potential function, and the corresponding snake is formulated directly from a force balance condition rather than a variational formulation. Using several two-dimensional (2-D) examples and one three-dimensional (3-D) example, we show that GVF has a large capture range and is able to move snakes into boundary concavities
Keywords :
computer vision; convergence of numerical methods; edge detection; image representation; image segmentation; linear differential equations; minimisation; partial differential equations; active contour; binary edge map; boundary concavities; computer vision applications; convergence; edge detection; external force; force balance condition; gradient vector flow; gradient vectors diffusion; gray-level map; image processing applications; image segmentation; image shape representation; initialization; large capture range; linear partial differential equations; minimization; object boundaries location; snakes; Active contours; Application software; Computer vision; Convergence; Deformable models; Image edge detection; Image processing; Image segmentation; Shape; Two dimensional displays;
Journal_Title :
Image Processing, IEEE Transactions on