| 基于PCA和BP神经网络算法的车牌字符识别 |
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| 引用本文： | 闫雪梅,王晓华,夏兴高.基于PCA和BP神经网络算法的车牌字符识别[J].激光与红外,2007,37(5):481-484. |
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| 作者姓名： | 闫雪梅 王晓华 夏兴高 |
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| 作者单位： | 北京理工大学信息科学技术学院电子工程系,北京,100081 |
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| 摘 要： | 文章采用了双重PCA算法链接BP神经网络的方法对车牌字符进行识别.先由主成分分析法对原始样本数据进行分类,然后由BP神经网络法对拒识样本进行识别.研究结果表明,与传统的单一识别方法相比,提高了识别正确率,减少了训练时间.
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| 关 键 词： | 主成分分析(PCA) BP神经网络 字符识别 神经网络 网络算法 车牌字符 字符识别 BP Neural Network Based Character Recognition Plate 训练时间 识别正确率 识别方法 结果 研究 拒识样本 网络法 分类 样本数据 成分分析法 |
| 文章编号： | 1001-5078（2007）05-0481-04 |
| 修稿时间： | 2007-04-042007-04-09 |
License Plate Character Recognition Based on PCA and BP Neural Network |
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| YAN Xue-mei,Wang Xiao-hu,XIA Xing-gao.License Plate Character Recognition Based on PCA and BP Neural Network[J].Laser & Infrared,2007,37(5):481-484. |
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| Authors: | YAN Xue-mei Wang Xiao-hu XIA Xing-gao |
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| Affiliation: | Department of Electronic Engineering, School of Information Science and Technology,Beijing Institute of Technology, Beijing 100081,China |
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| Abstract: | In this paper, double PCA combined with BP neural network is used. Firstly the principal component analysis is used to classify the sample data and then the BP neural network is used to recognize the unrecognized samples. The study result indicates that the new method improves the precision of recognition and reduces the training time. |
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| Keywords: | principal component analysis (PCA) BP neural network character recognition |
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