Squelette Euclidien Discret Connecté (DECS) résistant au bruit pour l'appariement de formes basé graphes

Aurélie Leborgne 1 Julien Mille 1 Laure Tougne 2, 1
1 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
2 M2DisCo - Geometry Processing and Constrained Optimization
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : The skeleton is an essential shape descriptor providing a compact representation of a shape that can be used in real object recognition context. However, due to the discretization, the required properties to use it for graph matching - homotopy to the shape, consequently connectivity, thinness, robustness to noise - may become difficult to obtain simultaneously. In this paper, we propose a new skeletonization algorithm having all this properties, based on the Euclidean distance map. More precisely, the algorithm combines in a clever manner the centers of maximal balls included in the shape and the ridges of the distance map. A post-processing is then applied to thin and prune the resulting skeleton. We compare the proposed method to three fairly recent methods and show its good properties.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01283912
Contributor : Aurélie Leborgne <>
Submitted on : Monday, March 7, 2016 - 9:55:51 AM
Last modification on : Tuesday, February 26, 2019 - 3:52:28 PM

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  • HAL Id : hal-01283912, version 1

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Aurélie Leborgne, Julien Mille, Laure Tougne. Squelette Euclidien Discret Connecté (DECS) résistant au bruit pour l'appariement de formes basé graphes. CORESA 2014, Nov 2014, Reims, France. ⟨hal-01283912⟩

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