| 手写体汉字识别中小波分形分解特征的研究 |
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| 引用本文： | 袁宁,栾虹,潘玉奇,石冰,邱恺毅. 手写体汉字识别中小波分形分解特征的研究[J]. 计算机工程与设计, 2005, 26(5): 1217-1219 |
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| 作者姓名： | 袁宁 栾虹 潘玉奇 石冰 邱恺毅 |
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| 作者单位： | 济南大学,信息科学与工程学院,山东,济南,250022;山东大学,计算机科学与技术学院,山东,济南,250061;山东省智奥电算开发中心,山东,济南,250013 |
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| 基金项目： | 山东省自然科学基金项目(Y2001G03) |
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| 摘 要： | 研究了手写体汉字识别中的一种新的特征提取方法——小波分形分解特征。对手写汉字分别采用小波和分形的方法提取其结构特征和统计特征，并将提取的结构特征和统计特征组合后作为识别器的输入进行识别。实验结果表明，对训练样本可以达到98．71％识别率，对测试样本可以达到91．37％识别率。
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| 关 键 词： | 汉字识别 特征提取 小波 分形 |
| 文章编号： | 1000-7024(2005)05-1217-03 |
Feature extraction with wavelet and fractal for handwritten Chinese character recognition |
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| YUAN Ning,LUAN Hong,PAN Yu-qi,SHI Bing,QIU Kai-yi. Feature extraction with wavelet and fractal for handwritten Chinese character recognition[J]. Computer Engineering and Design, 2005, 26(5): 1217-1219 |
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| Authors: | YUAN Ning LUAN Hong PAN Yu-qi SHI Bing QIU Kai-yi |
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| Affiliation: | YUAN Ning 1,LUAN Hong 1,PAN Yu-qi 1,SHI Bing 2,QIU Kai-yi 3 |
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| Abstract: | A new feature extraction approach for computer recognition of handwritten Chinese character is studied. In this method, wavelet and fractal are used to pick up the structure feature and statistical feature, and these features are combined and used for recognizer as input data. The experiment shows satisfied result. Identify rate can reach 98.71% for training stylebook and 91.37% for testing sty- lebook. |
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| Keywords: | Chinese characters recognized feature extraction wavelet fractal |
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