| 粗糙集神经网络系统在车牌字符识别中的研究 |
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| 引用本文： | 孙虹. 粗糙集神经网络系统在车牌字符识别中的研究[J]. 安徽建筑工业学院学报, 2007, 15(4): 95-98. DOI: 10.3969/j.issn.1006-4540.2007.04.026 |
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| 作者姓名： | 孙虹 |
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| 作者单位： | 安徽建筑工业学院机械与电气工程系,合肥,230601 |
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| 基金项目： | 安徽省教育厅自然科学项目（20006KJ013C）; 安徽建筑工业学院2006年硕博科研启动项目（20060701-16） |
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| 摘 要： | 以简化信息处理的复杂性并提高信息处理精度为目标,提出了基于粗糙集神经网络系统的车牌字符识别方法.提取训练样本的特征向量建立决策表,基于粗糙集理论对决策表属性进行约简,由约简后的属性构造神经网络识别器.车牌字符识别试验结果验证了系统的有效性.
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| 关 键 词： | 粗糙集 神经网络 字符识别 |
| 文章编号： | 1006-4540（2007）04-095-04 |
| 修稿时间： | 2007-08-02 |
The Car''''s Plate Characters Recognition Based on Rough Set Network System |
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| SUN Hong. The Car''''s Plate Characters Recognition Based on Rough Set Network System[J]. Journal of Anhui Institute of Architecture(Natural Science), 2007, 15(4): 95-98. DOI: 10.3969/j.issn.1006-4540.2007.04.026 |
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| Authors: | SUN Hong |
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| Affiliation: | SUN Hong (Department of Mechanical and Electrical engineering,Anhui Institute of Architecture ＆ Industry Hefei 230601,China) |
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| Abstract: | A method based on the combination of rough set and neural network was presented for the car's plate character recognition.Combining these two theories not only simplifies the complexity of information processing but also improves the precision of information processing.The features of the training samples were extracted to build up the decision table;the rough set theory was applied to reduce the decision table.Finally,the reduced decision attributes were used to construct neural network recognizing machine.The experiment results of the car's plate character recognition show that the algorithms are practical and effective. |
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| Keywords: | Rough Set Neural Network Characters Recognition |
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