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A New Efficient Method for Producing Global Affine Invariants

  • Esa Rahtu
  • Mikko Salo
  • Janne Heikkilä
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3617)

Abstract

This paper introduces a new efficient way for computing affine invariant features from gray-scale images. The method is based on a novel image transform which produces infinitely many different invariants, and is applicable directly to isolated image patches without further segmentation. Among methods in this class only the affine invariant moments have as low complexity as our method, but as known they also possess many considerable weaknesses, including sensitivity to noise and occlusions. According to performed experiments it turns out that our novel method is more robust against these nonaffine distortions observed in image acquisition process, and even in practice its computation time is equivalent to that of the affine invariant moments. It is also observed that already a small subset of these new features is enough for successful classification.

Keywords

Machine Intelligence Projective Transformation Invariant Moment Image Acquisition Process Vertical Center Line 
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 2005

Authors and Affiliations

  • Esa Rahtu
    • 1
  • Mikko Salo
    • 2
  • Janne Heikkilä
    • 1
  1. 1.Machine Vision Group, Department of Electrical and Information EngineeringUniversity of OuluFinland
  2. 2.Rolf Nevanlinna Institute, Department of Mathematics and StatisticsUniversity of HelsinkiFinland

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