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Invariant Reference Points Methodology and Applications

  • Krystian Ignasiak
  • Władysław Skarbek
  • Miloud Ghuwar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1689)

Abstract

A methodology for pattern recognition based on design of invariant reference points is described. Within this framework many classical pattern classifiers can be described (e.g. the k-NN distance classifier) and few new classifiers are defined (e.g. LPCAS classifier). LPCAS is applied for handwritten digit recognition reaching performance of 99.4% of recognition rate on NIST database.

Keywords

Reference Point Recognition Rate Selection Technique Subspace Method Source Domain 
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 1999

Authors and Affiliations

  • Krystian Ignasiak
    • 1
  • Władysław Skarbek
    • 1
  • Miloud Ghuwar
    • 1
  1. 1.Multimedia Laboratory, Department of Electronics and Information TechnologyWarsaw University of TechnologyUSA

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