Geodesic active contours

Vicent Caselles, Ron Kimmel, Guillermo Sapiro

Research output: Contribution to conferencePaperpeer-review

727 Scopus citations

Abstract

A novel scheme for the detection of object boundaries is presented. The technique is based on active contours deforming according to intrinsic geometric measures of the image. The evolving contours naturally split and merge, allowing the simultaneous detection of several objects and both interior and exterior boundaries. The proposed approach is based on the relation between active contours and the computation of geodesics or minimal distance curves. The minimal distance curve lays in a Riemannian space whose metric is defined by the image content. This geodesic approach for object segmentation allows to connect classical 'snakes' based on energy minimization and geometric active contours based on the theory of curve evolution. Previous models of geometric active contours are improved as showed by a number of examples. Formal results concerning existence, uniqueness, stability, and correctness of the evolution are presented as well.

Original languageEnglish (US)
Pages694-699
Number of pages6
StatePublished - 1995
Externally publishedYes
EventProceedings of the 5th International Conference on Computer Vision - Cambridge, MA, USA
Duration: Jun 20 1995Jun 23 1995

Conference

ConferenceProceedings of the 5th International Conference on Computer Vision
CityCambridge, MA, USA
Period6/20/956/23/95

All Science Journal Classification (ASJC) codes

  • General Engineering

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