Segmentation and geometric analysis: application to CT images of wood.
Identifieur interne : 000772 ( Hal/Checkpoint ); précédent : 000771; suivant : 000773Segmentation and geometric analysis: application to CT images of wood.
Auteurs : Adrien Kr Henbühl [France]Source :
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Abstract
he non-destructive study of wood from X-Ray CT scanners requires to imagine new solutions adapted to analysis of images. Relating both agronomic research and industrial sector of sawmills, segmentation of wood knots is a major challenge in terms of robustness to specificities of each species and to image acquisition conditions. The works carried out in this thesis allow to propose a segmentation process in two phases. It first isolates each knot in a reduced area then it segments the unique knot of each area. Proposed solutions for each phase allow to integrate knowledges about internal organization of trunk and mechanisms inherent to its growth, through classical tools of image analysis and processing. The first phase is essentially based on a movement detection principle borrowed from video analysis and revisited. Two segmentation approaches are then proposed, considering for one the initial CT slices and for the other news slices resampled for each knot orthogonally to its trajectory. The complete process has been implemented in a software dedicated both for experimentation and validation of approach, and to interdisciplinary dialogs.The applicative support of wood emphasizes the specialization abilities of generic image analysis and processing algorithms, and the relevance to integrate priori knowledges in this perspective.
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Relating both agronomic research and industrial sector of sawmills, segmentation of wood knots is a major challenge in terms of robustness to specificities of each species and to image acquisition conditions. The works carried out in this thesis allow to propose a segmentation process in two phases. It first isolates each knot in a reduced area then it segments the unique knot of each area. Proposed solutions for each phase allow to integrate knowledges about internal organization of trunk and mechanisms inherent to its growth, through classical tools of image analysis and processing. The first phase is essentially based on a movement detection principle borrowed from video analysis and revisited. Two segmentation approaches are then proposed, considering for one the initial CT slices and for the other news slices resampled for each knot orthogonally to its trajectory. The complete process has been implemented in a software dedicated both for experimentation and validation of approach, and to interdisciplinary dialogs.The applicative support of wood emphasizes the specialization abilities of generic image analysis and processing algorithms, and the relevance to integrate priori knowledges in this perspective.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">Segmentation and geometric analysis: application to CT images of wood.</title><title xml:lang="fr">Segmentation et analyse géométrique : application aux images tomodensitométriques de bois.</title><author role="aut"><persName><forename type="first">Adrien</forename><surname>Krähenbühl</surname></persName><email>adrien.krahenbuhl@loria.fr</email><ptr type="url" target="http://www.loria.fr/~krahenbu/"></ptr><idno type="idhal">akrah</idno><idno type="halauthor">800228</idno><affiliation ref="#struct-206036"></affiliation></author><editor role="depositor"><persName><forename>Adrien</forename><surname>Krähenbühl</surname></persName><email>adrien.krahenbuhl@labri.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2016-01-26 11:00:35</date><date type="whenModified">2016-01-28 01:10:51</date><date type="whenReleased">2016-01-26 16:33:01</date><date type="whenProduced">2014-12-12</date><date type="whenEndEmbargoed">2016-01-26</date><ref type="file" target="https://hal.archives-ouvertes.fr/tel-01262056/document"><date notBefore="2016-01-26"></date></ref><ref type="file" n="1" target="https://hal.archives-ouvertes.fr/tel-01262056/file/DDOC_T_2014_0276_KRAHENBUHL.pdf"><date notBefore="2016-01-26"></date></ref></edition><respStmt><resp>contributor</resp><name key="178062"><persName><forename>Adrien</forename><surname>Krähenbühl</surname></persName><email>adrien.krahenbuhl@labri.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">tel-01262056</idno><idno type="halUri">https://hal.archives-ouvertes.fr/tel-01262056</idno><idno type="halBibtex">krahenbuhl:tel-01262056</idno><idno type="halRefHtml">Géométrie algorithmique [cs.CG]. 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Relating both agronomic research and industrial sector of sawmills, segmentation of wood knots is a major challenge in terms of robustness to specificities of each species and to image acquisition conditions. The works carried out in this thesis allow to propose a segmentation process in two phases. It first isolates each knot in a reduced area then it segments the unique knot of each area. Proposed solutions for each phase allow to integrate knowledges about internal organization of trunk and mechanisms inherent to its growth, through classical tools of image analysis and processing. The first phase is essentially based on a movement detection principle borrowed from video analysis and revisited. Two segmentation approaches are then proposed, considering for one the initial CT slices and for the other news slices resampled for each knot orthogonally to its trajectory. The complete process has been implemented in a software dedicated both for experimentation and validation of approach, and to interdisciplinary dialogs.The applicative support of wood emphasizes the specialization abilities of generic image analysis and processing algorithms, and the relevance to integrate priori knowledges in this perspective.</abstract><abstract xml:lang="fr">L’étude non destructive du bois à partir de scanners à rayons X nécessite d’imaginer de nouvelles solutions adaptées à l’analyse des images. Préoccupation à la fois de la recherche agronomique et du milieu industriel des scieries, la segmentation des nœuds de bois est un défi majeur en termes de robustesse aux spécificités de chaque espèce et aux conditions d’acquisition des images. Les travaux menés dans cette thèse permettent de proposer un processus de segmentation en deux phases. Il isole d’abord chaque nœud dans une zone réduite puis segmente le nœud unique de chaque zone. Les solutions proposées pour chaque phase permettent d’intégrer les connaissances sur l’organisation interne du tronc et les mécanismes inhérents à sa croissance, à travers des outils classiques du traitement et de l’analyse d’image. La première phase repose en grande partie sur un principe de détection du mouvement emprunté à l’analyse vidéo et revisité. Deux approches de segmentation sont ensuite proposées, considérant pour l’une les coupes tomographiques initiales, et pour l’autre de nouvelles coupes ré-échantillonnées pour chaque nœud, orthogonalement à sa trajectoire. L’intégralité du processus a été implémenté dans un logiciel dédié aussi bien à l’expérimentation et la validation de l’approche qu’aux échanges interdisciplinaires.Le support applicatif du bois souligne la capacité de spécialisation des algorithmes génériques du traitement et de l’analyse d’image, et la pertinence de l’intégration de connaissances a priori dans cette optique.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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