Handwritten chinese character recognition: Alternatives to nonlinear normalization

被引:0
|
作者
Liu, CL [1 ]
Sako, H [1 ]
Fujisawa, H [1 ]
机构
[1] Hitachi Ltd, Cent Res Lab, Kokubunji, Tokyo 1858601, Japan
关键词
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暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Nonlinear normalization (NLN) by line density equalization has. been popularly used in handwritten Chinese character recognition (HCCR). To overcome the intensive computation of local line density and the excessive shape distortion of NLN, we tested some alternative methods based on. global transformation, including a moment-based linear transformation and two nonlinear methods based on quadratic curve fitting. The alternative methods are simpler in computation and the transformed images have more natural shapes. In experiments of HCCR on large databases, the alternative methods have yielded comparable or higher accuracies to the traditional NLN.
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页码:524 / 528
页数:5
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