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A Generalized Preimage for the Standard and Supercover Digital Hyperplane Recognition

  • Martine Dexet
  • Eric Andres
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4245)

Abstract

A new digital hyperplane recognition method is presented. This algorithm allows the recognition of Standard and Supercover hyperplanes by incrementally computing in a dual space the generalized preimage of a given hypervoxel set. Each point in this preimage corresponds to a Euclidean hyperplane which intersects all given hypervoxels. An advantage of the generalized preimage is that it does not depend on the hypervoxel locations. Moreover, the proposed recognition algorithm does not require the hypervoxels to be connected or ordered in any way.

Keywords

Recognition Algorithm Dual Transformation Discrete Apply Mathematic Plane Recognition Digital Point 
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

  • Martine Dexet
    • 1
  • Eric Andres
    • 1
  1. 1.Laboratoire SICUniversité de PoitiersFuturoscope ChasseneuilFrance

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