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
Vector flowInitializationBalanced flowBoundary (topology)Computer visionArtificial intelligenceMathematicsComputer scienceImage processingConvergence (economics)Vector fieldImage (mathematics)AlgorithmImage segmentationGeometryMathematical analysis
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Publication Info
- Year
- 1998
- Type
- article
- Volume
- 7
- Issue
- 3
- Pages
- 359-369
- Citations
- 3972
- Access
- Closed
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Cite This
Chenyang Xu,
Jerry L. Prince
(1998).
Snakes, shapes, and gradient vector flow.
IEEE Transactions on Image Processing
, 7
(3)
, 359-369.
https://doi.org/10.1109/83.661186
Identifiers
- DOI
- 10.1109/83.661186