Shape Matching Using the Geodesic Eccentricity Transform - A Study

نویسندگان

  • Adrian Ion
  • Gabriel Peyré
  • Yll Haxhimusa
  • Samuel Peltier
  • Walter G. Kropatsch
  • Laurent Cohen
چکیده

This paper makes use of the continuous eccentricity transform to perform shape matching. The eccentricity transform has already been proven useful in a discrete graph-theoretic setting. We show how these ideas extend naturally to the continuous setting thus bringing a higher geometrical fidelity. The continuous eccentricity transform is used to compute multiscale descriptors for shapes. These descriptors are defined as histograms of the eccentricity transform of a scale-space representation of the shape. These multiscale descriptors are naturally invariant to euclidean motion and bending. They show promising results for shape discrimination.

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تاریخ انتشار 2007