文章基本信息

标题：Traffic Sign Recognition Using Scale Invariant Feature Transform and Svm
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作者：Xiaoguang Hu ; Xinyan Zhu ; Deren Li 等
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2010
卷号：XXXVIII Part 4
出版社：Copernicus Publications
摘要：TSR (Traffic sign recognition) has been studied for realizing drivers assisting system and automated navigation and is an importantstudied field in ITS (Intelligent traffic system). In this paper, a recognition method of traffic signs separated from real image wasstudied. Images were divided into several categories according to the actual weather, distance and angle of view etc. SIFT was firstlyused to detect keypoints and describe them because the SIFT(Scale Invariant Feature Transform) features were invariant to imagescale and rotation and were robust to changes in the viewpoint and illumination. And then the Bag-of-words method was applied torecognition. Finally, the SVM(Support vector machine) approach was used in classification. As shown by the experiment results, theproposed method is effective.
关键词：Traffic sign recognition; SIFT; SVM; Bag-of-words