| 基于SVM的脱机手写汉字机器学习识别方法研究 |
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| 引用本文： | 王建平,陈军,徐晓冰,王熹徽.基于SVM的脱机手写汉字机器学习识别方法研究[J].微机发展,2006,16(10):104-107. |
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| 作者姓名： | 王建平 陈军 徐晓冰 王熹徽 |
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| 作者单位： | 合肥工业大学电气与自动化工程学院 安徽合肥230009 |
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| 摘 要： | 提出了一种模糊统计方法的脱机手写体汉字特征提取方法,结合小波网格方法和汉字笔画密度特征方法对汉字进行特征提取,并运用支持向量机方法,通过机器学习对脱机手写汉字识别。仿真实验表明,支持向量机方法在脱机手写汉字识别中有良好的识别性能及模糊统计方法是有效的。
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| 关 键 词： | 支持向量机 脱机手写汉字体汉字 模糊统计特征 汉字识别 |
| 文章编号： | 1673-629X(2006)10-0104-04 |
| 修稿时间： | 2006年1月15日 |
Research on Method of Off-Line Handwritten Chinese Characters Recognition Based on SVM |
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| WANG Jian-ping,CHEN Jun,XU Xiao-bing,WANG Xi-hui.Research on Method of Off-Line Handwritten Chinese Characters Recognition Based on SVM[J].Microcomputer Development,2006,16(10):104-107. |
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| Authors: | WANG Jian-ping CHEN Jun XU Xiao-bing WANG Xi-hui |
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| Abstract: | In this paper,a new feature extraction method based on fuzzy statistic feature was proposed.SVM,The theory of small-sample statistical learning proposed by Vapnik,was used for off-line handwritten Chinese characters recognition.The feature date was extracted by three methods they are the density of Chinese characters stokes,wavelet transform and elastic meshing,and fuzzy statistic feature.The result of recognition shows that the SVM method can be used practically in off-line handwritten Chinese characters recognition and the new feature extraction method is effective and scientific. |
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| Keywords: | SVM off-line handwritten Chinese characters fuzzy statistic feature Chinese characters recognition |
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