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Multilevel Recognition of Structured Handprinted Documents - Probabilistic Approach

  • Jerzy Sas
  • Marek Kurzynski
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 30)

Abstract

In the paper the multilevel probabilistic approach to handprinted form recognition is described. The form recognition is decomposed into three levels: character recognition, word recognition and form contents recognition. On the word and form contents level the probabilistic lexicons are available. The decision on the word level is performed using probabilistic properties of character classifier and the contents of probabilistic lexicon. The novel approach to combining these two sources of information about classes (words) probabilities is proposed, which is based on lexicons and accuracy assessment of local character classifiers. Some experimental results and examples of practical applications of recognition method are also briefly described.

Keywords

Word Recognition Recognition Quality Character Classifier Word Level Word Classifier 
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 2005

Authors and Affiliations

  • Jerzy Sas
    • 1
  • Marek Kurzynski
    • 2
  1. 1.Institute of Applied InformaticsWroclaw University of TechnologyWroclawPoland
  2. 2.Faculty of Electronics, Chair of Systems and Computer NetworksWroclaw University of TechnologyWroclawPoland

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