Handwritten word recognition using segmentation-free hidden Markov modeling and segmentation-based dynamic programming techniques

被引:96
|
作者
Mohamed, M
Gader, P
机构
[1] Department of Electrical and Computer Engineering, University of Missouri, Columbia
关键词
hidden Markov models; dynamic programming; handwritten word recognition; character recognition; neural networks; character segmentation;
D O I
10.1109/34.494644
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A lexicon-based, handwritten word recognition system combining segmentation-free and segmentation-based techniques is described. The segmentation-free technique constructs a continuous density hidden Markov model for each lexicon string. The segmentation-based technique uses dynamic programming to match word images and strings. The combination module uses differences in classifier capabilities to achieve significantly better performance.
引用
收藏
页码:548 / 554
页数:7
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