| 基于改进支持向量机的车牌识别 |
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| 引用本文： | 赵明敏,田丽. 基于改进支持向量机的车牌识别[J]. 陕西理工学院学报(自然科学版), 2014, 0(4): 27-31 |
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| 作者姓名： | 赵明敏 田丽 |
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| 作者单位： | 安徽工程大学电气工程学院,安徽芜湖241000 |
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| 基金项目： | 基金项目：国家中小企业创新基金资助项目（11C26213402044）;安徽省教育厅自然科学基金资助项目（KJ20128027） |
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| 摘 要： | 针对目前市场上使用的监控设备在雾霾天气下辨识精度和速度不足等问题,采用小波低频融合原理对采集到的图像预处理,并基于改进支持向量机算法对预处理后的车牌图像提取特征值。实验结果表明,改进后的车牌识别方法与传统方法相比,提高了辨别速度,减小了误识率,为雾天视频监控系统的研发提供了新的思路。
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| 关 键 词： | 车牌识别 低频融合 支持向量机 |
License plate recognition using improved support vector machine |
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| ZHAO Ming-min,TIAN Li. License plate recognition using improved support vector machine[J]. Journal of Shananxi University of Technology(Natural Science Edition), 2014, 0(4): 27-31 |
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| Authors: | ZHAO Ming-min TIAN Li |
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| Affiliation: | ( School of Electric Engineering, Anhui Polytechnic University, Wuhu 241000, China) |
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| Abstract: | In view of inaccruacy and inadequacy in speed of recoginition of the current monitoring equipment in smoggy weather,the study uses low-frequency wavelet fusion theory to pretreat the collected. Then,post-treatment is administered to extract distinguished features of the license plate based on improved support vector machines. The experimental results show that：compared with the traditional methods for vehicle license plate recognition,the proposed method improves the speed discrimination,reduces the misrecognition and provides a new way for video monitor system developers in the haze weather. |
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| Keywords: | license plate recognition low frequency fusion support vector machines |
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