Abstract
A hierarchical system for character recognition with hidden Markov model knowledge sources which solve both the context sensitivity problem and the character instantiation problem is presented. The system achieves 97-99% 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.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Keywords
Hidden Markov modelComputer scienceCharacter recognitionCharacter (mathematics)Artificial intelligencePattern recognition (psychology)Markov modelMarkov processMarkov chainSpeech recognitionMathematicsMachine learningImage (mathematics)Statistics
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Publication Info
- Year
- 1992
- Type
- article
- Volume
- 1
- Issue
- 4
- Pages
- 539-543
- Citations
- 55
- Access
- Closed
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Cite This
J.A. Vlontzos,
Sun‐Yuan Kung
(1992).
Hidden Markov models for character recognition.
IEEE Transactions on Image Processing
, 1
(4)
, 539-543.
https://doi.org/10.1109/83.199925
Identifiers
- DOI
- 10.1109/83.199925