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Conference papers

Graph signal active contours

Olivier Lézoray 1
1 Equipe Image - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen
Abstract : With the advent of data living on vertices of graphs, there is much interest in processing the so-called graph signals for partitioning tasks. As active contours have had much impact in the image processing community, their formulation on graphs is of importance to the field of graph signal processing. This paper proposes an adaptation on graphs of a model that combines the Geodesic Active Contour and the Active Contour Without Edges models. In addition, specific terms depending on graphs are introduced in the formulation. This adaptation is solved using a level set formulation with a gradient descent that can be expressed as a morphological front evolution process. Experimental results on different kinds of graphs signals show the benefit of the approach.
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Contributor : Olivier Lezoray <>
Submitted on : Tuesday, January 12, 2021 - 5:56:14 PM
Last modification on : Tuesday, January 26, 2021 - 3:27:03 AM
Long-term archiving on: : Tuesday, April 13, 2021 - 6:55:58 PM

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  • HAL Id : hal-03107668, version 1


Olivier Lézoray. Graph signal active contours. International Conference on Pattern Recognition (ICPR - IEEE), 2021, Milan, Italy. ⟨hal-03107668⟩



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