Scale Filtered Euclidean Medial Axis

  • Michał Postolski
  • Michel Couprie
  • Marcin Janaszewski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7749)


We propose an Euclidean medial axis filtering method which generates subsets of Euclidean medial axis were filtering rate is controlled by one parameter. The method is inspired by Miklos’, Giesen’s and Pauly’s scale axis method which preserves important features of an input object from shape understanding point of view even if they are at different scales. Our method overcomes the most important drawback of scale axis: scale axis is not, in general, a subset of Euclidean medial axis. It is even not necessarily a subset of the original shape. The method and its properties are presented in 2D space but it can be easily extended to any dimension. Experimental verification and comparison with a few previously introduced methods are also included.


Filtered medial axis discrete scale axis shape representation image analysis stability 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Michał Postolski
    • 1
    • 2
  • Michel Couprie
    • 1
  • Marcin Janaszewski
    • 2
  1. 1.LIGM, Equipe A3SI, ESIEE, Cité DESCARTESUniversité Paris-EstNoisy le Grand CedexFrance
  2. 2.Institute of Applied Computer ScienceLodz University of TechnologyPoland

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