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

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Combinatorial Image Analysis (IWCIA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4040))

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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.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Faculty of Informatics, University of Debrecen, PO Box 12, 4010, Debrecen, Hungary

    Benedek Nagy

  2. Research Group on Mathematical Linguistics, Rovira i Virgili University, Tarragona, Spain

    Benedek Nagy

  3. Centre for Image Analysis, Uppsala University, Lägerhyddsvägen 3, SE-75237, Uppsala, Sweden

    Robin Strand

Authors
  1. Benedek Nagy
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  2. Robin Strand
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Editor information

Editors and Affiliations

  1. Institute for Transport Research, German-Aerospace Center (DLR), Rutherfordstr. 2, 12489, Berlin, Germany

    Ralf Reulke

  2. Fachbereich Mathematik, Universität Hamburg, Bundesstr. 55, 20146, Hamburg

    Ulrich Eckardt

  3. Dresden University of Technology,  

    Boris Flach

  4. Institut für Informatik, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099, Berlin, Germany

    Uwe Knauer

  5. FU Berlin, Arnimallee 3, 14195, Berlin, Germany

    Konrad Polthier

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© 2006 Springer-Verlag Berlin Heidelberg

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Nagy, B., Strand, R. (2006). Approximating Euclidean Distance Using Distances Based on Neighbourhood Sequences in Non-standard Three-Dimensional Grids. In: Reulke, R., Eckardt, U., Flach, B., Knauer, U., Polthier, K. (eds) Combinatorial Image Analysis. IWCIA 2006. Lecture Notes in Computer Science, vol 4040. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11774938_8

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  • DOI: https://doi.org/10.1007/11774938_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-35153-5

  • Online ISBN: 978-3-540-35154-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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