Hidden Markov models for character recognition

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.<
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