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Anisotropic Channel Filtering

  • Michael Felsberg
  • Gösta Granlund
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2749)

Abstract

Channel smoothing is an alternative to diffusion filtering for robust estimation of image features. Its main advantages are speed, stability with respect to parameter changes, and a simple implementation. However, channel smoothing becomes instable in certain situations, typically for elongated, periodic patterns like for instance fingerprints. As for the diffusion filtering an anisotropic extension is required in these cases. In this paper we introduce a new method for anisotropic channel smoothing which is comparable to coherence enhancing diffusion, but faster and easier to implement. Anisotropic channel smoothing implements an orientation adaptive non-linear filtering scheme as a special case of adaptive channel filtering. The smoothing algorithm is applied to several fingerprint images and the results are compared to those of coherence enhancing diffusion.

Keywords

Grey Level Channel Matrix Orientation Information Robust Estimator Fingerprint Image 
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

  • Michael Felsberg
    • 1
  • Gösta Granlund
    • 1
  1. 1.Computer Vision Laboratory, Department of Electrical EngineeringLinköping UniversityLinköpingSweden

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