| Issue |
E3S Web Conf.
Volume 229, 2021
The 3rd International Conference of Computer Science and Renewable Energies (ICCSRE’2020)
|
|
|---|---|---|
| Article Number | 01006 | |
| Number of page(s) | 10 | |
| DOI | https://doi.org/10.1051/e3sconf/202122901006 | |
| Published online | 25 January 2021 | |
Traffic Sign Detection for Intelligent Transportation Systems: A Survey
1
LabSIE, Department of Mathematics and Computer Science, multidisciplinary faculty, Ibn Zohr University, BP 638, 45000 Ouarzazate, Morocco.
2
LabSIV, Department of Computer Science, Faculty of Science, Ibn Zohr University, BP 8106, 80000 Agadir, Morocco.
Recently, intelligent transportation systems (ITS) attracts more and more attention for its wide applications. Traffic sign detection and recognition (TSDR) system is an essential task of ITS. It enhances the safety by informing the drivers about the current state of traffic signs and offering valuable information about precautions. This paper reviews the popular traffic sign detection methods (TSD) prevalent in recent literature. The methods are divided into color-based, shape-based, and machine learning based ones. Color space, segmentation method, features, and shape detection method are the terms considered in the review of the detection module. The paper presents a comparison between these methods. Furthermore, a list of publicly available data sets and a discussion on possible future works are provided.
Key words: Intelligent transportation systems / Traffic sign detection / Traffic sign recognition / survey.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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