Feature selection algorithms for the generation of multiple classifier systems and their application to handwritten word recognition

  • Authors:
  • Simon Günter;Horst Bunke

  • Affiliations:
  • Department of Computer Science, University of Bern, Neubrückstrasse 10, CH-3012 Bern, Switzerland;Department of Computer Science, University of Bern, Neubrückstrasse 10, CH-3012 Bern, Switzerland

  • Venue:
  • Pattern Recognition Letters
  • Year:
  • 2004

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Abstract

The study of multiple classifier systems has become an area of intensive research in pattern recognition recently. Also in handwriting recognition, systems combining several classifiers have been investigated. In this paper new methods for the creation of classifier ensembles based on feature selection algorithms are introduced. Those new methods are evaluated and compared to existing approaches in the context of handwritten word recognition, using a hidden Markov model recognizer as basic classifier.