The Bayes-Optimal Feature Extraction Procedure for Pattern Recognition Using Genetic Algorithm

  • Marek Kurzynski
  • Edward Puchala
  • Aleksander Rewak
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4131)


The paper deals with the extraction of features for statistical pattern recognition. Bayes probability of correct classification is adopted as the extraction criterion. The problem with complete probabilistic information is discussed and Bayes-optimal feature extraction procedure is presented in detail. The case of recognition with learning is also considered. As method of solution of optimal feature extraction a genetic algorithm is proposed. A numerical example demonstrating capability of proposed approach to solve feature extraction problem is presented.


Genetic Algorithm Feature Extraction Statistical Pattern Recognition Bhattacharyya Distance Feature Extraction Procedure 
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 2006

Authors and Affiliations

  • Marek Kurzynski
    • 1
  • Edward Puchala
    • 1
  • Aleksander Rewak
    • 1
  1. 1.Faculty of Electronics, Chair of Systems and Computer NetworksWroclaw University of TechnologyWroclawPoland

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