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Detection and classification of traffic lights for automated setup of road surveillance systems

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Abstract

Traffic light plays an important role in controlling the traffic flow to maintain order. The state of the traffic light is used in automatic detection of illegal motions against traffic rules. In this paper, a video based-method is proposed to tackle the problem of detection and classification of traffic lights in the scenes, thus providing an automated setup of road surveillance systems in intelligent transportation systems (ITS). Firstly, the proposed method localizes the regions of traffic lights by detecting the regularity in which the traffic light colors change, and then classify the traffic lights by an SVM classifier on their shape features. This method is insensitive to illumination changing and adaptable to various kinds of shape settings. Finally, the experimental results show that this method is efficient and effective in automatically recognizing traffic lights.

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Acknowledgements

This research is supported in part by the following funds: National Natural Science Foundation of China under grant number 61472113 and 61304188, and Zhejiang Provincial Natural Science Foundation of China under grant number LZ13F020004 and LR14F020003.

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Authors and Affiliations

  1. Hangzhou Normal University, Hangzhou, Zhejiang, People’s Republic of China

    Xingmin Shi & Na Zhao

  2. College of Computer Science, Zhejiang University, Hangzhou Normal University, Hangzhou, Zhejiang, People’s Republic of China

    Yingjie Xia

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  1. Xingmin Shi
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  2. Na Zhao
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Correspondence to Yingjie Xia.

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Shi, X., Zhao, N. & Xia, Y. Detection and classification of traffic lights for automated setup of road surveillance systems. Multimed Tools Appl 75, 12547–12562 (2016). https://doi.org/10.1007/s11042-014-2343-1

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  • DOI: https://doi.org/10.1007/s11042-014-2343-1

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