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Recognition of traffic lights in urban traffic scenes using color space model
Author(s): Xiaoyan Zhu; Chihang Zhao; Xingzhi Qi; Jie He
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Paper Abstract

In order to identify the status of traffic lights in urban traffic scenes effectively, a recognition method of traffic lights using HSV color space model is proposed in this paper. Firstly, the median filter and the light compensation algorithm are used to preprocess images of urban traffic scenes. Secondly, the template matching method of traffic lights and the Bhattacharyya coefficient are used to detection of the traffic lights area in images of traffic scenes. Finally, the status of traffic lights in urban traffic scenes are identified using HSV color space model. The experimental results show that the proposed recognition method of traffic lights using HSV color space model offers the best performance than RGB color space model and YCbCr color space model. The recognition accuracies of red, green and yellow traffic lights are 96.67%, 95.0% and 88.67%, respectively.

Paper Details

Date Published: 29 October 2018
PDF: 5 pages
Proc. SPIE 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence, 108360R (29 October 2018); doi: 10.1117/12.2514674
Show Author Affiliations
Xiaoyan Zhu, Southeast Univ. (China)
Chihang Zhao, Southeast Univ. (China)
Xingzhi Qi, Southeast Univ. (China)
Jie He, Southeast Univ. (China)


Published in SPIE Proceedings Vol. 10836:
2018 International Conference on Image and Video Processing, and Artificial Intelligence
Ruidan Su, Editor(s)

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