Abstract
Traffic signs recognition is an important component in driver assistance systems as it helps driving under safety regulations. The aim of this work is to propose a vision based traffic sign recognition. In the recognition process, we detect the potential traffic signs regions using monocular color based segmentation. Afterwards, we identify the traffic sign class using its HoG features and the SVM classifier. As shown experimentally, compared to leading methods from the literature under complex conditions, our method has a higher efficiency.
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Romdhane, N.B., Mliki, H., El Beji, R., Hammami, M. (2016). A Comparative Study of Vision-Based Traffic Signs Recognition Methods. In: Campilho, A., Karray, F. (eds) Image Analysis and Recognition. ICIAR 2016. Lecture Notes in Computer Science(), vol 9730. Springer, Cham. https://doi.org/10.1007/978-3-319-41501-7_39
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DOI: https://doi.org/10.1007/978-3-319-41501-7_39
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