Application of new technology in building human comforts and automation is growing fast, particularly in automobile industry. Automatic detection and recognition of traffic signs for assisting driver to ensure a safe travel have been givenpractical importance for intelligent traffic system. The proposed method detects the location of the traffic sign in thecaptured image, based on its geometrical characteristics and using color information. Such signs are then recognized using a pattern matching with the normalized cross correlation method and tracked through a sequence of images. The algorithm is tested using image set of different traffic signs and non traffic signs taken under various adverse conditions such as, various backgrounds, lighting conditions, orientation and distances. Experimental result shows the better performance in the detection and recognition of road signs with recognition rate of 90%. Computational time is also quite low which makes it applicable for the real time system.

1. Hossain, S. M. , Hasan, M. M. , Ali A. M. , Kabir, H. Md. and Ali, A. B. M. 2010. Automatic detection and recognition of traffic signs. In IEEE Conference on Robotics, Automation and Mechatronics. pp. 286-291.
2. HasanFleyeh(1)(2) and Taha Khan. 2010. Pattern Matching Approach Towards Real-time Traffic Sign Recognition. In multimedia computing and information technology (MCIT) 2010. IEEE. pp 57- 60.
3. Fatmehsan, Y. R. , Ghahari, A. , Zoroofi, R. A. 2010 Gabor wavelet for road sign detection and recognition using a hybrid classifier. In multimedia computing and information technology (MCIT). IEEE. pp. 25 - 28
4. Hemadri, V. B. and Kulkarni, U. P. 2011. Detection and Recognition of Mandatory and Cautionary Road Signals Using Unique Identifiable features. In Proceedings of the International Conference & Workshop on Emerging Trends in Technology (ICWET). pp. 1376-1377.
5. Qingsong, X. , Juan,S. and Tiantian, L. 2010. A Detection and Recognition Method for Prohibition Traffic Signs. In Image Analysis and Signal Processing (IASP), 2010 International Conference on. IEEE. pp. 583 - 586.
6. Fleyeh, H. and Davami E. 2011. Eigen-based traffic sign recognition. IET Intell. Transp. Syst. 5 190–196.
7. Huang, Y. S. , Fu, M. Y. and Ma, H. B. 2010. A Combined Method for Traffic Sign Detection and Classification. In Pattern Recognition (CCPR), Chinese Conference on. IEEE 2010. pp 1-5.
8. Chen. L. Li, Q. , Li. M. and Mao. Q. 2011. Traffic sign detection and recognition for intelligent vehicle. In Intelligent Vehicles Symposium (IV), IEEE. pp 908-913.
9. Ruta,A. , Li,Y. and Liu, X. 2010 Real-time traffic sign recognition from video by class-specific discriminative features. Pattern Recognition 43, 416—430
10. Zaklouta, F. and Stanciulescu, 2012. B. Real-time traffic sign recognition in three stages. Robotics and Autonomous Systems. 2012, In press.
11. Kiran, C. G. , Prabhu, L. V. , Abdu, R. V. and Rajeev, K. 2009. Traffic sign detection and pattern recognition using support vector machine. In Advances in Pattern Recognition,. ICAPR '09. Seventh International Conference IEEE. pp. 87 – 90.

Color segmentation Shape analysis Road sign detection