Image analysis – Pattern recognition – Unconstrained handwriting
Patent
1995-04-19
1997-07-01
Mancuso, Joseph
Image analysis
Pattern recognition
Unconstrained handwriting
382187, 382228, G06K 918
Patent
active
056446527
ABSTRACT:
An automatic handwriting recognition system wherein each written (chirographic) manifestation of each character is represented by a statistical model (called a hidden Markov model). The system implements a method which entails sampling a pool of independent writers and deriving a hidden Markov model for each particular character (allograph) which is independent of a particular writer. The HMMs are used to derive a chirographic label alphabet which is independent of each writer. This is accomplished during what is described as the training phase of the system. The alphabet is constructed using supervised techniques. That is, the alphabet is constructed using information learned in the training phase to adjust the result according to a statistical algorithm (such as a Viterbi alignment) to arrive at a cost efficient recognition tool. Once such an alphabet is constructed a new set of HMMs can be defined which more accurately reflects parameter typing across writers. The system recognizes handwriting by applying an efficient hierarchical decoding strategy which employs a fast match and a detailed match function, thereby making the recognition cost effective.
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Bellegarda Eveline Jeannine
Bellegarda Jerome Rene
Nahamoo David
Nathan Krishna Sundaram
International Business Machines - Corporation
Mancuso Joseph
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