Extracting Noise-resistant Skeleton on Digital Shapes for Graph Matching

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 : In order to match shapes using their skeletons, these ones should be thin, robust to noise, homotopic to the shape, consequently, connected. However, these properties are difficult to obtain simultaneously when the shape is defined on a discrete grid. In this paper, we propose a new skeletonization algorithm, which has all these properties. Based on the Euclidean distance map, the algorithm extracts the centers of maximal balls included in the shape and uses the ridges of distance map to connect them. A post-processing is then applied to thin and prune the resulting skeleton. The proposed method is compared to three fairly recent methods to highlight the good properties of the obtained skeleton.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01283905
Contributor : Aurélie Leborgne <>
Submitted on : Monday, March 7, 2016 - 9:48:25 AM
Last modification on : Tuesday, February 26, 2019 - 3:52:28 PM

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Aurélie Leborgne, Julien Mille, Laure Tougne. Extracting Noise-resistant Skeleton on Digital Shapes for Graph Matching. 10th International Symposium, ISVC 2014, Dec 2014, Las Vegas, United States. ⟨10.1007/978-3-319-14249-4_28⟩. ⟨hal-01283905⟩

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