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Application of Rough Sets in Combined Handwritten Words Classifier

  • Jerzy Sas
  • Andrzej Zolnierek
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 57)

Summary

In the paper the multilevel probabilistic approach to hand printed form recognition is described. The form recognition is decomposed into two levels: character recognition and word recognition. On the letter level the rough sets approach is presented. After this level of classification, for every position in the word, we obtain either the certain or the subset of possible or the subset of impossible decision about recognized letter. After on the word 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 Decision Attribute Support Factor Letter Recognition Word Level 
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

  • Jerzy Sas
    • 1
  • Andrzej Zolnierek
    • 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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