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Approximating Euclidean Distance Using Distances Based on Neighbourhood Sequences in Non-standard Three-Dimensional Grids

  • Benedek Nagy
  • Robin Strand
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4040)

Abstract

In image processing, it is often of great importance to have small rotational dependency for distance functions. We present an optimization for distances based on neighbourhood sequences for the face-centered cubic (fcc) and body-centered cubic (bcc) grids. In the optimization, several error functions are used measuring different geometrical properties of the balls obtained when using these distances.

Keywords

Grid Point Distance Function Error Function Mathematical Linguistics Neighbourhood Relation 
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

  • Benedek Nagy
    • 1
    • 2
  • Robin Strand
    • 3
  1. 1.Department of Computer Science, Faculty of InformaticsUniversity of DebrecenDebrecenHungary
  2. 2.Research Group on Mathematical LinguisticsRovira i Virgili UniversityTarragonaSpain
  3. 3.Centre for Image AnalysisUppsala UniversityUppsalaSweden

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