基于HOG特征和SVM的交通图像车辆标志识别

D. F. Llorca, R. Arroyo, M. Sotelo
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引用次数: 123

摘要

提出了一种基于梯度直方图(HOG)和支持向量机(SVM)的汽车标志识别方法。该系统专门设计用于处理交通摄像头提供的低分辨率标识图像。采用滑动窗口技术结合多数投票方案来估计汽车制造商。该方法在一组3579张车辆图像上进行了评估,这些图像由27个不同的汽车制造商的两台不同的交通摄像机拍摄。结果表明,该系统的总体识别率为92.59%,可用于实际应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vehicle logo recognition in traffic images using HOG features and SVM
In this paper a new vehicle logo recognition approach is presented using Histograms of Oriented Gradients (HOG) and Support Vector Machines (SVM). The system is specifically devised to work with images supplied by traffic cameras where the logos appear with low resolution. A sliding-window technique combined with a majority voting scheme are used to provide the estimated car manufacturer. The proposed approach is assessed on a set of 3.579 vehicle images, captured by two different traffic cameras that belong to 27 distinctive vehicle manufacturers. The reported results show an overall recognition rate of 92.59%, which supports the use of the system for real applications.
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