Large scale on-line handwritten Chinese character recognition using improved syntactic pattern recognition

Kazuhiro Kuroda, Ken Harada, Masafumi Hagiwara

Research output: Contribution to journalConference articlepeer-review

5 Citations (Scopus)


In this paper, we propose an original method for the recognition of on-line handwritten Chinese characters using an improved syntactic pattern recognition. Syntactic pattern recognition is a method that converts a pattern into a string of symbols using a finite set of features and then analyzes them structurally using grammar. So it is effective for such patterns as structurally constructed Chinese characters. 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 which express features of the successors, and are analyzed by simple calculations between matrices. Moreover in order to symbolize and analyze efficiently and accurately in a large scale, we employ hierarchical approach for the proposed method. Using free writing characters, we obtained 99.49% recognition rate for training patterns and 94.34% for test patterns.

Original languageEnglish
Pages (from-to)4530-4535
Number of pages6
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Publication statusPublished - 1997 Dec 1
EventProceedings of the 1997 IEEE International Conference on Systems, Man, and Cybernetics. Part 1 (of 5) - Orlando, FL, USA
Duration: 1997 Oct 121997 Oct 15

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Hardware and Architecture


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