Approximate Steerability of Gabor Filters for Feature Detection

  • I. Kalliomäki
  • J. Lampinen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3540)

Abstract

We discuss the connection between Gabor filters and steerable filters in pattern recognition. We derive optimal steering coefficients for Gabor filters and evaluate the accuracy of the approximative orientation steering numerically. Gabor filters can be well steerable, but the error of the approximation depends heavily on the parameters. We show how a rotation invariant feature similarity measure can be obtained using steerability.

Keywords

Shape Parameter Feature Detection Gabor Filter Rotation Invariance Tight Wavelet Frame 
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

  • I. Kalliomäki
    • 1
  • J. Lampinen
    • 1
  1. 1.Laboratory of Computational EngineeringHelsinki University of TechnologyEspooFinland

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