Efficient contour detection based on improved snake model

Frank Y. Shih, Kai Zhang

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Active contour model, also called snake, adapts to edges in an image. A snake is defined as an energy minimizing spline - the snake's energy depends on its shape and location within the image. Problems associated with initialization and poor convergence to boundary concavities, however, have limited its utility. In this paper, we present a new external force field, named gravitation force field, for the snake model. We associate this force field with edge preserving smoothing to drive the snake for solving the problems. Our gravitation force field uses gradient values as particles to construct force field in the whole image. This force field will attract the active contour toward the edge boundary. The locations of the initial contour are very flexible, such that they can be very far away from the objects and can be inside, outside, or the mixture. The improved snake can converge toward the object boundary in a fast pace.

Original languageEnglish (US)
Pages (from-to)197-209
Number of pages13
JournalInternational Journal of Pattern Recognition and Artificial Intelligence
Volume18
Issue number2
DOIs
StatePublished - Mar 1 2004

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

Keywords

  • Active contour model
  • Edge detection
  • Edge preserving smoothing
  • Gradient vector flow
  • Image processing
  • Snake

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