Handwritten word recognition using segmentation-free hidden Markov modeling and segmentation-based dynamic programming techniques
作者： M. Mohamed , P. Gader
DOI: 10.1109/34.494644
关键词:
摘要: A lexicon-based, handwritten word recognition system combining segmentation-free and segmentation-based techniques is described. The technique constructs a continuous density hidden Markov model for each lexicon string. uses dynamic programming to match images strings. combination module differences in classifier capabilities achieve significantly better performance.
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