基于pca和小波分类器的静态道路图像车辆检测

ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585) Pub Date : 2001-08-25 DOI:10.1109/ITSC.2001.948752

Junwen Wu, Xuegong Zhang, Jie Zhou

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引用次数: 41

摘要

从静态道路图像中检测车辆是一项困难的任务，因为运动信息不再可用。本文提出了一种基于主成分分析(PCA)技术的模式分类器算法。特征提取阶段采用小波变换。在真实道路图像上的实验表明了该算法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Vehicle detection in static road images with PCA-and-Wavelet-Based classifier

Detecting vehicles from static road images is a difficult task since motion information is no longer usable. This paper presents an algorithm for this task with a pattern classifier built on the principal component analysis or PCA technique. Wavelet transform is adopted in feature extraction phase. Experiments on real road images show the effectiveness of this algorithm.

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来源期刊

ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585)

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