InforLorV4, Main, Exploration, bibRecordById, Pascal:14-0239569

Knot segmentation in 3D CT images of wet wood

Identifieur interne : 000E39 ( Main/Exploration ); précédent : 000E38; suivant : 000E40

Knot segmentation in 3D CT images of wet wood

Auteurs : Adrien Kr Henbühl [France] ; Bertrand Kerautret [France] ; Isabelle Debled-Rennesson [France] ; Frédéric Mothe [France] ; Fleur Longuetaud [France]

Source :

Pattern recognition [ 0031-3203 ] ; 2014.

RBID : Pascal:14-0239569

Descripteurs français

Pascal (Inist)
- Segmentation, Image tridimensionnelle, Tomographie numérique, Radiographie RX, Scanneur, Mesure automatique, Algorithme, Estimation robuste, Détection forme, Estimation paramètre, Etat actuel, Traitement en ligne, Géométrie discrète.

English descriptors

KwdEn :
- Algorithm, Automatic measurement, Computerized tomography, Discrete geometry, On line processing, Parameter estimation, Robust estimation, Scanner, Segmentation, Shape detection, State of the art, Tridimensional image, X ray radiography.
mix :
- Curvature estimators, Discrete geometry, Segmentation, Wood knot, X-ray CT scanner.

Abstract

This paper proposes a fully automatic method to segment wood knots from images obtained by an X-ray Computed Tomography scanner. Wood knot segmentation is known to be a difficult problem in the presence of sapwood because of the quite similar density of knots and wet sapwood. Classical segmentation techniques produce unsatisfactory results due to the very weak distinction between these two intensities. To overcome this limitation caused by physical characteristics, we propose to exploit the geometric properties of both the knot shapes and knot-sapwood interface. Based on previous work related to automatic knot detection, a new segmentation algorithm is proposed that uses a robust curvature estimation of 2D digital contours. The segmentation process is fast, easily parallelizable and produces better segmentation results than other state-of-the-art algorithms. It may be reproduced from the precise description given here or from source code available online.

Url:

https://hal.inria.fr/hal-01062639

Affiliations:

Le document en format XML

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<front><div type="abstract" xml:lang="en">This paper proposes a fully automatic method to segment wood knots from images obtained by an X-ray Computed Tomography scanner. Wood knot segmentation is known to be a difficult problem in the presence of sapwood because of the quite similar density of knots and wet sapwood. Classical segmentation techniques produce unsatisfactory results due to the very weak distinction between these two intensities. To overcome this limitation caused by physical characteristics, we propose to exploit the geometric properties of both the knot shapes and knot-sapwood interface. Based on previous work related to automatic knot detection, a new segmentation algorithm is proposed that uses a robust curvature estimation of 2D digital contours. The segmentation process is fast, easily parallelizable and produces better segmentation results than other state-of-the-art algorithms. It may be reproduced from the precise description given here or from source code available online.</div>
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Serveur d'exploration sur la recherche en informatique en Lorraine

Knot segmentation in 3D CT images of wet wood

Knot segmentation in 3D CT images of wet wood

Source :

Descripteurs français

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri

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