Off-line handwritten word recognition (HWR) using a single contextual hidden Markov model
作者： M.-Y. Chen , A. Kundu , J. Zhou
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摘要: A complete scheme for totally unconstrained handwritten word recognition based on a single contextual hidden Markov model (HMM) is proposed. The includes morphology- and heuristics-based segmentation algorithm modified Viterbi that searches the (l+1)st globally best path previous l paths. results of detailed experiments which overall rate up to 89.4% are reported. >
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