Large scale on-line handwritten Chinese character recognition using successor method based on stochastic regular grammar

Kazuhiro Kuroda, Ken Harada, Masafumi Hagiwara

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

In this paper, we propose an original method for the recognition of on-line handwritten Chinese characters using the successor method based on the stochastic regular grammar. We use Kohonen's self-organizing feature map for feature extraction to get optimal sets of prototypical waveforms of peaks from sample data automatically. The strings of symbols are converted into matrices using the stochastic successor method, and are analyzed by simple calculation between matrices. In order to symbolize and analyze input patterns efficiently and accurately in a large scale, we employ a hierarchical approach. Using unrestricted handwritten characters, we obtained 94.34% recognition rate for the test patterns.

Original languageEnglish
Pages (from-to)1307-1315
Number of pages9
JournalPattern Recognition
Volume32
Issue number8
DOIs
Publication statusPublished - 1999 Aug

Keywords

  • Grammatical inference
  • Kohonen's self-organizing feature map
  • On-line handwriting recognition
  • Rough classification
  • Stochastic regular grammar
  • Subnetworks
  • Successor attribute matrix
  • Successor method

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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