Shape Matching Using the Geodesic Eccentricity Transform - A Study

Adrian Ion (1) , Gabriel Peyré (2) , Yll Haxhimusa (1) , Samuel Peltier (1) , Walter G. Kropatsch (1) , Laurent D. Cohen (2)

1 PRIP - Pattern Recognition and Image Processing Group
2 CEREMADE - CEntre de REcherches en MAthématiques de la DEcision

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.

Mots clés: Eccentricity; geodesic; fast marching; shape matching

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Adrian Ion, Gabriel Peyré, Yll Haxhimusa, Samuel Peltier, Walter G. Kropatsch, et al.. Shape Matching Using the Geodesic Eccentricity Transform - A Study. 31st annual workshop of the Austrian Association for Pattern (OAGM/AAPR), Aug 2007, Krumbach, Austria. pp.97--104. ⟨hal-00365897⟩