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The Eccentricity Transform (of a Digital Shape)

  • Walter G. Kropatsch
  • Adrian Ion
  • Yll Haxhimusa
  • Thomas Flanitzer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4245)

Abstract

Eccentricity measures the shortest length of the paths from a given vertex v to reach any other vertex w of a connected graph. Computed for every vertex v it transforms the connectivity structure of the graph into a set of values. For a connected region of a digital image it is defined through its neighbourhood graph and the given metric. This transform assigns to each element of a region a value that depends on it’s location inside the region and the region’s shape. The definition and several properties are given. Presented experimental results verify its robustness against noise, and its increased stability compared to the distance transform. Future work will include using it for shape decomposition, representation, and matching.

Keywords

Root Mean Square Error Short Path Noisy Image Connected Region Pepper Noise 
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 2006

Authors and Affiliations

  • Walter G. Kropatsch
    • 1
  • Adrian Ion
    • 1
  • Yll Haxhimusa
    • 1
  • Thomas Flanitzer
    • 1
  1. 1.Pattern Recognition and Image Processing GroupVienna University of TechnologyViennaAustria

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