| 一种多分类器集成的手写体汉字识别方法 |
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| 引用本文： | 朱敏觉,朱宁波,袁异.一种多分类器集成的手写体汉字识别方法[J].计算机工程与科学,2009,31(4). |
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| 作者姓名： | 朱敏觉 朱宁波 袁异 |
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| 作者单位： | 湖南大学计算机与通信学院,湖南,长沙,410082 |
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| 摘 要： | 多分类器集成是手写体汉字识别领域的新方向。本文提出的多分类器集成方法通过改进的欧氏距离分类器将待识别汉字分类到某个粗分结果集中,然后根据粗分结果集选择1-N(one-against-rest)的SVM分类器对待识别汉字进行细分,最后用贝叶斯集成两级分类器。实验对国标一级汉字中的1034个手写汉字进行识别,证明了方案的有效性。
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| 关 键 词： | 手写体汉字识别 欧氏距离 支持向量机 贝叶斯集成 弹性网格 方向特征提取 |
A Handwritten Chinese Character Recognition Method Based on Multi-Classifier Ensemble |
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| ZHU Min-jue,ZHU Ning-bo,YUAN Yi.A Handwritten Chinese Character Recognition Method Based on Multi-Classifier Ensemble[J].Computer Engineering & Science,2009,31(4). |
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| Authors: | ZHU Min-jue ZHU Ning-bo YUAN Yi |
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| Affiliation: | School of Computer and Communications;Hunan University;Changsha 410082;China |
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| Abstract: | Multi-classifier ensemble is a new research direction.A new method of multi-classifier ensemble is presented in this paper.The method uses two-level classifiers to ensemble.An improved Euclid distance classifier at the first level is used to make a rough set for the test samples,and then the one-against-rest SVM classifiers are applied to recognize the handwritten Chinese more exactly.Finally the two-level classifiers are ensembled by the Bayesian law.The experiment for the handwritten national standard Chi... |
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| Keywords: | handwritten Chinese recognition Euclid distance support vector machine Bayesian ensemble elastic mesh directional feature extraction |
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