Improving the accuracy of a fuzzy-based single-stroke character recognizer by antecedent weighting

A. Tormási, L. T. Kóczy

Research output: Contribution to journalArticle


In this chapter we present an improved version of the fuzzy based single-stroke character recognizer introduced in previous works. The modified recognition method is able to reach higher accuracy in the character recognition without any significant effect on the computational complexity of the algorithm. Different fuzzy rule and antecedent weighting techniques were successfully used to improve the efficiency of fuzzy systems especially in classification problems. The altered recognizer reached 99.49 % average recognition rate with 26 different single-stroke symbols (based on Palm’s Graffiti alphabet) without learning userspecific parameters or modifying the rule-base. The new algorithm has the same computational complexity as the original system does.

Original languageEnglish
Pages (from-to)165-179
Number of pages15
JournalStudies in Fuzziness and Soft Computing
Publication statusPublished - Jan 1 2014


ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computational Mathematics

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