Alternatives to variable duration HMM in handwriting recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 20, Issue 11, 1998, Pages 1275-1280

  Kundu, Amlan ^a   He, Yang ^b   Chen, Mou Yen ^c  

^a US West Advanced Technologies   (United States)

^b XEROX CORPORATION   (United States)

^c INDUSTRIAL TECHNOLOGY RESEARCH INSTITUTE   (Taiwan)

Author keywords

Adaptive length viterbi algorithm (alva); Model discriminant hmm (md hmm); Nonergodic hmm (nehmm); Path discriminant hmm (pd hmm); Variable duration hmm (vdhmm); Variable sequence length hmm (vslhmm)

Indexed keywords

ADAPTIVE ALGORITHMS; MARKOV PROCESSES; MATHEMATICAL MODELS; STATISTICAL METHODS;

ADAPTIVE LENGTH VITERBI ALGORITHM; HANDWRITTEN WORD RECOGNITION (HWR); HIDDEN MARKOV MODEL (HMM); VARIABLE SEQUENCE LENGTH HMM;

PATTERN RECOGNITION;

EID: 0032206573     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/34.730561     Document Type: Article

References (5)

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4. M. Mohamed and P. Gader, "Handwritten Word Recognition Using Segmentation Free Hidden Markov Modeling and Segmentation Based Dynamic Programming Techniques," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 18, no. 5, pp. 548-554, May 1996.
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