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Orientation Fields Filtering by Derivates of a Gaussian

  • Josef Bigun
  • Tomas Bigun
  • Kenneth Nilsson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2749)

Abstract

We suggest a set of complex differential operators, symmetry derivatives, that can be used for matching and pattern recognition. We present results on the invariance properties of these. These show that all orders of symmetry derivatives of Gaussians yield a remarkable invariance : they are obtained by replacing the original differential polynomial with the same polynomial but using ordinary scalars. Moreover, these functions are closed under convolution and they are invariant to the Fourier transform. The revealed properties have practical consequences for local orientation based feature extraction. This is shown by two applications: i) tracking markers in vehicle tests ii) alignment of fingerprints.

Keywords

Pattern Recognition Computer Vision Feature Extraction Differential Operator Computer Graphic 
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 2003

Authors and Affiliations

  • Josef Bigun
    • 1
  • Tomas Bigun
    • 2
  • Kenneth Nilsson
    • 1
  1. 1.Halmstad UniversityHalmstadSweden
  2. 2.TietoEnator ArosTechLinkpingSweden

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