| 基于SVM和小波边缘检测的车型图像识别 |
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| 引用本文： | 邹国平,虞安军,黄铮.基于SVM和小波边缘检测的车型图像识别[J].交通标准化,2007(11):117-120. |
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| 作者姓名： | 邹国平 虞安军 黄铮 |
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| 作者单位： | 江西赣粤高速公路股份有限公司,江西,南昌,330025 |
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| 摘 要： | 在基于小波边缘检测和SMO算法的基础上进行车型图像识别,首先将待识别目标进行二维小波分解,获取不同尺度下的小波系数,然后对其进行主元分析,得到的主元作为支持向量机的特征量输入.实验结果表明,该方法具有良好的分类性能.
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| 关 键 词： | 车型识别 支持向量机 序贯最小优化 小波变换 主元分析 小波边缘检测 图像识别 Wavelets Edge Detection Support Vector Machine Based Image Recognition 分类性能 方法 结果 实验 输入 特征量 支持向量机 主元分析 小波系数 尺度 二维小波分解 识别目标 行车 |
| 文章编号： | 1002-4786（2007）11-0117-03 |
| 收稿时间： | 2007-04-28 |
| 修稿时间： | 2007年4月28日 |
Vehicle Image Recognition Based on Support Vector Machine and Edge Detection by Wavelets |
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| ZOU Guo-ping,YU An-jun,Huang Zheng.Vehicle Image Recognition Based on Support Vector Machine and Edge Detection by Wavelets[J].Communications Standardization,2007(11):117-120. |
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| Authors: | ZOU Guo-ping YU An-jun Huang Zheng |
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| Institution: | Jiangxi Ganyue Expressway Co., Ltd., Nanchang 330025, China |
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| Abstract: | Vehicle image recognition is conducted based on edge detection by wavelets and SMO algorithm. First 2-D wavelet is used to decompose the image and get the wavelet coefficients, then calculate principal components which will be the inputs of SVM. Experiment results indicate that this method has good classification performance. |
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| Keywords: | vehicle recognition support vector machines sequential minimal optimization wavelet transform principal components analysis |
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