Efficient Traffic Sign Detection Based on High Dynamic Range Preprocessing Module

Authors

  • Dr. Mohammed El Amine Moumene

Keywords:

Intelligent Transportation Systems, Traffic Sign Recognition, High Dynamic Range Imaging, Artificial Neural Network

Abstract

Traffic sign recognition systems are primordial for intelligent vehicles. Various vision based detection systems have been proposed to detect road panels, but few of them tackle adverse conditions of acquisition such as bad weather or high dynamic range scenes. In this paper, we introduce efficient traffic sign detection when facing difficult illumination conditions. First, a high dynamic range preprocessing module based on Neural Network exposure fusion is used. After that,  shape or color based detection phase is performed to detect regions of interest. Evaluation and comparisons using some relevant works showed that the added preprocessing module enhances the detection rate facing adverse illumination conditions.

References

Sheikh, M. A. A., Kole, A., & Maity, T. (2016, October). Traffic sign detection and classification using colour feature and neural network. In 2016 International Conference on Intelligent Control Power and Instrumentation (ICICPI) (pp. 307-311). IEEE.

Gómez-Moreno, H., Maldonado-Bascón, S., Gil-Jiménez, P., & Lafuente-Arroyo, S. (2010). Goal evaluation of segmentation algorithms for traffic sign recognition. IEEE Transactions on Intelligent Transportation Systems, 11(4), 917-930.

Yang, Y., Luo, H., Xu, H., & Wu, F. (2015). Towards real-time traffic sign detection and classification. IEEE Transactions on Intelligent transportation systems, 17(7), 2022-2031.

Garcia-Garrido, M. A., Sotelo, M. A., & Martin-Gorostiza, E. (2006, September). Fast traffic sign detection and recognition under changing lighting conditions. In 2006 IEEE Intelligent Transportation Systems Conference (pp. 811-816). IEEE.

Akinlar, C., & Topal, C. (2012). A real-time circle detector with a false detection control. IEEE International Con-ference on Acoustics, Speech and Signal Processing. Kyoto, 1309-1312.

Berkaya, S. K., Gunduz, H., Ozsen, O., Akinlar, C., & Gunal, S. (2016). On circular traffic sign detection and recognition. Expert Systems with Applications, 48, 67-75.

Moumene, M. E. A., & Benkedadra, M. (2021). Enhanced Road Lane Detection Facing Sun Glare. Journal of Mobile Multimedia, 773-788.

Mertens, T., Kautz, J., & Van Reeth, F. (2007, October). Exposure fusion. In 15th Pacific Conference on Computer Graphics and Applications (PG'07) (pp. 382-390). IEEE.

Moumene, M. E. A., & Benkedadra, M. (2021). Enhanced Road Lane Detection Facing Sun Glare. Journal of Mobile Multimedia, 773-788.

Downloads

Published

2021-09-20

How to Cite

El Amine Moumene, M. . (2021). Efficient Traffic Sign Detection Based on High Dynamic Range Preprocessing Module. WAS Science Nature (WASSN) ISSN: 2766-7715, 4(1). Retrieved from http://worldascience.com/journals/index.php/wassn/article/view/31

Issue

Section

Computer Science & Mathematics