Snakes, shapes, and gradient vector flow

Chenyang Xu, Jerry L. Prince

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)359-369
Number of pages11
JournalIEEE Transactions on Image Processing
Volume7
Issue number3
DOIs
StatePublished - Dec 1 1998

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Keywords

  • Active contour models
  • Deformable surface models
  • Edge detection
  • Gradient vector flow
  • Image segmentation
  • Shape representation and recovery
  • Snakes

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

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