Detection and classification of speed limit traffic signs

This paper presents a novel traffic sign recognition system which can aid in the development of Intelligent Speed Adaptation. This system is based on extracting the speed limit sign from the traffic scene by Circular Hough Transform (CHT) with the aid of colour and non-colour information of the traffic sign. The digits of the speed limit sign are then extracted and classified using SVM classifier which is trained for this purpose. In general, the system detects the prohibitory traffic sign in the first place, specifies whether the detected sign is a speed limit sign, and then determines the allowed speed in case the detected sign is a speed limit sign. The SVM classifier was trained with 270 images which were collected in different light conditions. To check the robustness of this system, it was tested against 210 images which contain 213 speed limit traffic sign and 288 Non-Speed limit signs. It was found that the accuracy of recognition was 98% which indicates clearly the high robustness targeted by this system.

[1]  Antonio Fernández-Caballero,et al.  An optimization on pictogram identification for the road-sign recognition task using SVMs , 2010, Comput. Vis. Image Underst..

[2]  J. Torresen,et al.  Efficient recognition of speed limit signs , 2004, Proceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No.04TH8749).

[3]  Klaus Zimmermann,et al.  Towards reliable traffic sign recognition , 2009, 2009 IEEE Intelligent Vehicles Symposium.

[4]  Nasser Kehtarnavaz,et al.  A real-time histographic approach to road sign recognition , 1996, Proceeding of Southwest Symposium on Image Analysis and Interpretation.

[5]  M.A. Salichs,et al.  Neural traffic sign recognition for autonomous vehicles , 1994, Proceedings of IECON'94 - 20th Annual Conference of IEEE Industrial Electronics.

[6]  W. Cleveland,et al.  Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting , 1988 .

[7]  Yichang Tsai,et al.  Real-time Speed Limit Sign Recognition Based on Locally Adaptive Thresholding and Depth-First-Search , 2005 .

[8]  Weijie Liu,et al.  Detection and recognition of traffic signs in adverse conditions , 2009, 2009 IEEE Intelligent Vehicles Symposium.

[9]  Yoshiaki Shirai,et al.  An active vision system for real-time traffic sign recognition , 2000, ITSC2000. 2000 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.00TH8493).

[10]  Bruce A. Draper,et al.  Color recognition in outdoor images , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[11]  Sei-Wang Chen,et al.  A road sign recognition system based on dynamic visual model , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[12]  Giovanni Pilato,et al.  Road signs recognition using a dynamic pixel aggregation technique in the HSV color space , 2001, Proceedings 11th International Conference on Image Analysis and Processing.

[13]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[14]  Mark Dougherty,et al.  Road and traffic sign detection and recognition , 2005 .

[15]  Sei-Wang Chen,et al.  Road-sign detection and tracking , 2003, IEEE Trans. Veh. Technol..