| 基于组合特征的车牌字符识别 |
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| 引用本文： | 路小波,凌小静,刘斌.基于组合特征的车牌字符识别[J].仪器仪表学报,2006,27(7):698-701. |
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| 作者姓名： | 路小波 凌小静 刘斌 |
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| 作者单位： | 东南大学教育部智能运输系统工程研究中心,南京,210096 |
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| 基金项目： | 高校科技创新工程项目;江苏省自然科学基金 |
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| 摘 要： | 提出了基于Zernike矩和小波变换特征相结合的车牌字符识别方法。利用Zernike矩描述字符全局特征，小波变换系数描述字符细节特征，采用神经网络进行车牌字符分类。测试结果表明，这种组合了两种特征优点的方法实用有效，识别效果优于两种特征独立使用的情况。
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| 关 键 词： | 车牌字符识别 Zernike矩 小波变换 特征提取 |
| 修稿时间： | 2005年2月1日 |
License plate character recognition based on the combined features |
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| Lu Xiaobo,Ling Xiaojing,Liu Bin.License plate character recognition based on the combined features[J].Chinese Journal of Scientific Instrument,2006,27(7):698-701. |
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| Authors: | Lu Xiaobo Ling Xiaojing Liu Bin |
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| Abstract: | This paper presents a method of license plate character recognition based on the combination of Zernike moment and wavelet transformation features.The Zernike moment is used to describe the global feature of the characters,and the wavelet transform coefficient for the detailed feature of the characters.A neural network is used to classify the license plate characters. Experimental results show the presented method achieves better recognition accuracy than using two features separately. |
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| Keywords: | license plate character recognition Zernike moment wavelet transform feature extraction |
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