DocumentCode
1563237
Title
Hidden Markov models for character recognition
Author
Vlontzos, J.A. ; Kung, S.Y.
Author_Institution
Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
fYear
1989
Firstpage
1719
Abstract
The authors present a hierarchical 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
Keywords
Markov processes; character recognition; hierarchical systems; HMM; character instantiation problem; character recognition; context sensitivity problem; handwriting recognition; hidden Markov model knowledge sources; hierarchical system; multifont character recognition; multisize printed character recognition; systolic array; two-level architecture; Character recognition; Contracts; Handwriting recognition; Hidden Markov models; Hierarchical systems; Parallel processing; Real time systems; Speech recognition; Stochastic processes; Systolic arrays;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 1989. ICASSP-89., 1989 International Conference on
Conference_Location
Glasgow
ISSN
1520-6149
Type
conf
DOI
10.1109/ICASSP.1989.266780
Filename
266780
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