Cursive handwritten word recognition by integrating multiple classifiers

被引：0
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作者：
Maruyama, Kenichi [1 ,3 ]
Kobayashi, Makoto [1 ,3 ]
Yamada, Hirobumi [2 ,4 ]
Nakano, Yasuaki [1 ]
机构：
[1] Dept. of Information Engineering, Shinshu University, Nagano, 380-8553, Japan
[2] Faculty of Engineering, Toyohashi University of Technology, Toyohashi, 441-8580, Japan
[3] Shinshu University
[4] Shinshu University, Toyohasni University of Technology
来源：
| 1600年 / Scripta Technica Inc, New York, NY, United States卷 / 31期
关键词：
Feature extraction - Image analysis - Pattern matching - Word processing;
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学科分类号：
摘要：
This paper proposes a method for cursive handwritten word recognition. In the traditional research, cursive handwritten word recognition used a single method for character recognition. Our research proposes a method that integrates multiple classifiers in order to improve the word recognition rate by combining their results. Our experiment demonstrates that two classifiers outperform the word recognition rate of any single character classifier.
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