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Robust Knot Segmentation by Knot Pith Tracking in 3D Tangential Images

  • Adrien KrähenbühlEmail author
  • Jean-Romain Roussel
  • Bertrand KerautretEmail author
  • Isabelle Debled-Rennesson
  • Frédéric Mothe
  • Fleur Longuetaud
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9972)

Abstract

This paper proposes a fast, accurate and automatic method to segment wood knots from images obtained by X-Ray Computed Tomography scanner. The wood knot segmentation is a classical problem where the most popular segmentation techniques produce unsatisfactory results. In a previous work, a method was developed to detect knot areas and an approach was proposed to segment the knots. However this last step is not entirely satisfactory in the presence of sapwood. This paper presents a novel approach for knot segmentation, based on the original idea considering slices tangential to the growth rings. They allow to track the knot from the log pith to the bark. Knots are then segmented by detecting discrete ellipses in each slice. A complete implementation is proposed on the TKDetection software available online.

Keywords

Segmentation Quality Angular Sector Major Radius Annual Growth Ring Vertical Inclination 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Adrien Krähenbühl
    • 1
    Email author
  • Jean-Romain Roussel
    • 4
  • Bertrand Kerautret
    • 1
    Email author
  • Isabelle Debled-Rennesson
    • 1
  • Frédéric Mothe
    • 2
    • 3
  • Fleur Longuetaud
    • 2
    • 3
  1. 1.LORIA, UMR CNRS 7503, Université de LorraineVandœuvre-les-nancyFrance
  2. 2.INRA, UMR1092 LERFoBChampenouxFrance
  3. 3.AgroParisTech, UMR1092 LERFoBNancyFrance
  4. 4.CRMR, Départ. des sciences du bois et de la foretLavalCanada

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