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Handwritten Word Recognition Using Multi-view Analysis

  • J. J. de OliveiraJr.
  • C. O. de A. Freitas
  • J. M. de Carvalho
  • R. Sabourin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5856)

Abstract

This paper brings a contribution to the problem of efficiently recognizing handwritten words from a limited size lexicon. For that, a multiple classifier system has been developed that analyzes the words from three different approximation levels, in order to get a computational approach inspired on the human reading process. For each approximation level a three-module architecture composed of a zoning mechanism (pseudo-segmenter), a feature extractor and a classifier is defined. The proposed application is the recognition of the Portuguese handwritten names of the months, for which a best recognition rate of 97.7% was obtained, using classifier combination.

Keywords

Hide Markov Model Perceptual Feature Word Context Word Image Forward Algorithm 
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 2009

Authors and Affiliations

  • J. J. de OliveiraJr.
    • 1
  • C. O. de A. Freitas
    • 2
  • J. M. de Carvalho
    • 3
  • R. Sabourin
    • 4
  1. 1.UFRN - Universidade Federal do Rio Grande do Norte 
  2. 2.PUC-PR - Pontíficia Universidade Católica do Paraná 
  3. 3.UFCG - Universidade Federal de Campina Grande 
  4. 4.ÉTS - École de Technologie Supérieure 

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