Extracting Road Signs using the Color Information

Authors: Wen-Yen Wu, Tsung-Cheng Hsieh, Ching-Sung Lai

Abstract:

In this paper, we propose a method to extract the road signs. Firstly, the grabbed image is converted into the HSV color space to detect the road signs. Secondly, the morphological operations are used to reduce noise. Finally, extract the road sign using the geometric property. The feature extraction of road sign is done by using the color information. The proposed method has been tested for the real situations. From the experimental results, it is seen that the proposed method can extract the road sign features effectively.

Keywords: Color information, image processing, road sign.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1329262

References:

[1] M. Benallal and J. Meunier, J. "Real-time color segmentation of road signs," in Proceedings of the 2003 Electrical and Computer Engineering Conference, vol.3, Canada, 2003, pp.1823-1826.
[2] W. G. Shadeed, D. I. Abu-Al-Nadi, and M. J. Mismar, "Road traffic sign detection in color images," in Proceedings of the 2003 10th IEEE International Conference on Electronics, Circuits and Systems, vol.2, Sharjah, UAE, 2003, pp.890-893.
[3] S. Vitabile, G. Pollaccia, G. Pilato, and F. Sorbello, "Road signs recognition using a dynamic pixel aggregation technique in the HSV color space," in Proceedings of the 11th International Conference on Image Analysis and Processing, Palermo, Italy, 2002, pp.572-577.
[4] A. D. L. Escalera, J. M. Armingol, and M. Mata, "Traffic sign recognition and analysis for intelligent vehicles," Image and Vision Computing, vol. 21, no. 3, pp. 247-258, 2002.
[5] C. L. Huang and S. H. Hsu, "Road sign interpretation using matching pursuit method," in Proceedings of the 15th International Conference on Pattern Recognition, vol.1, Barcelona, Spain, 2000, pp.329-333.
[6] C. Y. Fang, C. S. Fuh, and S. W. Chen, "Detection and tracking of road signs," Pattern Recognition and Image Analysis, vol. 11, no. 2, pp. 304-308, 2001.
[7] Y. B. Lauziere, D. Gingras, and F. P. Ferrie, "A model-based road sign identification system," in Proceedings of the 2001 IEEE Computer Society Conference, vol.1, Hawaii, USA, 2001, pp.1163-1170.
[8] H. Ohara, I. Nishikawa, S. Miki, and N. Yabuki, "Detection and recognition of road signs using simple layered neural networks," in Proceedings of the 9th International Conference on Neural Information Processing, vol.2, Singapore, 2002, pp.626-630.
[9] P. Paclík, J. Novovičová, P. Pudil, and P. Somol, "Road sign classification using Laplace kernel classifier," Pattern Recognition Letters, vol. 13-14, no 21, pp. 1165-1173, 2000.
[10] G. Piccioli, E. D. Michel, P. Parodi, and M. Campani, "Robust method for road sign detection and recognition," Image and Vision Computing, vol. 14, no. 3, pp. 119-129, 1996.
[11] Y. C. Hu, R. S. Chen, G. H. Tzeng, "Finding fuzzy classification rules using data mining techniques," Pattern Recognition Letters, Vol. 24, pp. 509-519, 2003.
[12] D. A. Keima, C. Pansea, M. Sipsa, S. C. North, "Pixel based visual data mining of geo-spatial data," Computers & Graphics, Vol. 28, pp. 327-344, 2004.
[13] B. Shneiderman, "The eyes have it: a task by data type taxonomy for information visualizations," in Proceedings of the IEEE Visual Languages, pp. 336-43, 1996.