Knot Detection in X-Ray CT Images of Wood

Adrien Krähenbühl (1) , Bertrand Kerautret (1) , Isabelle Debled-Rennesson (1) , Fleur Longuetaud (2) , Frédéric Mothe (2)

1 ADAGIO - Applying Discrete Algorithms to Genomics and Imagery
2 LERFoB - Laboratoire d'Etudes des Ressources Forêt-Bois

This paper presents an original problem of knot detection in 3D X-ray Computer Tomography images of wood stems. This image type is very different from classical medical images and presents specific geometric structures. These ones are characteristic of wood stems na- ture. The contribution of this work is to exploit the original geometric structures in a simple and fast algorithm to automatically detect and analyze the wood knots. The proposed approach is robust to different wood qualities, like moisture or noise, and more simple to implement than classical deformable models approaches.

Mots clés: 3D Knot detection; wood images

Domaines: Traitement des images [eess.IV]

Adrien Krähenbühl, Bertrand Kerautret, Isabelle Debled-Rennesson, Fleur Longuetaud, Frédéric Mothe. Knot Detection in X-Ray CT Images of Wood. ISVC - 8th International Symposium on Visual Computing - 2012, Jul 2012, Rethymnon, Greece. pp.209-218, ⟨10.1007/978-3-642-33191-6_21⟩. ⟨hal-00780731⟩