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Representing Orientation in n-Dimensional Spaces

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Computer Analysis of Images and Patterns (CAIP 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2756))

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Abstract

In this paper we present new insights in methods to solve the orientation representation problem in arbitrary dimensions. The gradient structure tensor is one of the most used descriptors of local structure in multi-dimensional images. We will relate its properties to the double angle method in 2D and the Knutsson mapping in three or higher dimensions. We present a general scheme to reduce the dimensionality of the mappings needed to solve the orientation representation problem and derive some properties of these reduced mappings.

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References

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Author information

Authors and Affiliations

  1. Pattern Recognition Group, Delft University of Technology, Lorentzweg 1, 2628 CJ, Delft, The Netherlands

    B. Rieger & L. J. van Vliet

Authors
  1. B. Rieger
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  2. L. J. van Vliet
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Editor information

Editors and Affiliations

  1. Institute of Mathematics and Computing Science, University of Groningen, P.O.Box 800, 9700 AV, Groningen, The Netherlands

    Nicolai Petkov

  2. Institute of Mathematics and Computing Science, University of Groningen, Blauwborgje 3, 9747 AC, Groningen, The Netherlands

    Michel A. Westenberg

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© 2003 Springer-Verlag Berlin Heidelberg

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Rieger, B., van Vliet, L.J. (2003). Representing Orientation in n-Dimensional Spaces. In: Petkov, N., Westenberg, M.A. (eds) Computer Analysis of Images and Patterns. CAIP 2003. Lecture Notes in Computer Science, vol 2756. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45179-2_3

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  • DOI: https://doi.org/10.1007/978-3-540-45179-2_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40730-0

  • Online ISBN: 978-3-540-45179-2

  • eBook Packages: Springer Book Archive

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