A coarse classification scheme on printed Chinese characters by encoding the feature points

Ming Gang Wen, Chin Chuan Han, Kuo Chin Fan, Da Way Tang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this paper a coarse classification scheme is proposed to speed up the recognition process of machine printed Chinese character. Simple and stable features are extracted by encoding feature points into a codeword of length 16. Geometrically, the codeword represents the distribution of feature points among character strokes. Using these simple features to do coarse classification can eliminate a large number of impossible candidates. Only few surviving candidates need be re-checked in the following more complex recognition algorithms. This scheme will simplify the design of the classifier algorithm and reduce the recognition time. Some experimental results are given to show the validity and efficiency of our proposed methods.

Original languageEnglish
Pages (from-to)555-570
Number of pages16
JournalJournal of Information Science and Engineering
Volume19
Issue number4
StatePublished - Jul 2003

Keywords

  • Coarse classification
  • Codeword encoding
  • Feature point extraction
  • Optical character recognition
  • Threshold-based selection

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