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Applicability of Motion Estimation Algorithms for an Automatic Detection of Spiral Grain in CT Cross-Section Images of Logs

  • Karl Entacher
  • Christian Lenz
  • Martin Seidel
  • Andreas Uhl
  • Rudolf Weiglmaier
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4673)

Abstract

Techniques for an automatic detection of spiral grain in cross-section CT images of logs are proposed and evaluated on sets of natural and artificial cross-section images. Explicit analysis of global rotation, block matching, and optical flow techniques are compared. Experimental results seem to indicate that spiral grain in fact cannot be modeled by a circular motion of luminance values in gray scale images.

Keywords

Mean Square Error Motion Vector Automatic Detection Block Match Motion Estimation Algorithm 
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-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Karl Entacher
    • 1
  • Christian Lenz
    • 2
  • Martin Seidel
    • 2
  • Andreas Uhl
    • 2
  • Rudolf Weiglmaier
    • 2
  1. 1.Salzburg University of Applied SciencesAustria
  2. 2.Department of Computer Sciences, Salzburg UniversityAustria

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