Hidden Markov models for character recognition

J. A. Vlontzos, S. Y. Kung

Research output: Contribution to journalConference article

2 Scopus citations

Abstract

The authors present a hierachical system for character recognition with hidden Markov model knowledge sources that solve both the context sensitivity problem and the character instantiation problem. The system achieves 97 to 99% accuracy using a two-level architecture and has been implemented using a systolic array, thus permitting real-time (1 ms per character) multifont and multisize printed character recognition as well as handwriting recognition.

Original languageEnglish (US)
Pages (from-to)1719-1722
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume3
StatePublished - Dec 1 1989
Externally publishedYes
Event1989 International Conference on Acoustics, Speech, and Signal Processing - Glasgow, Scotland
Duration: May 23 1989May 26 1989

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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