Improving the performance of traffic sign detection using blob tracking

We propose a new approach for tracking circular traffic signs from image sequences to improve the performance of traffic sign detection, by reducing search region and suppressing misdetection caused by temporal occlusion or poor quality of image. Our proposed tracking, called two-layered blobs tracking, does not require an accurate model of the fixed object-moving camera system, which is essential in the Kalman-Filter tracking. The experimental results show that the proposed approach could track the circular traffic signs from a moving camera effectively, without any restrictions on speed and movement of the vehicle, and camera installation, thus it is easy to be implemented in real situation.

[1]  Koichi Yamada,et al.  Traffic Sign Classification Using Ring Partitioned Method , 2005, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

[2]  Sergio A. Velastin,et al.  People tracking in surveillance applications , 2006, Image Vis. Comput..

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

[4]  Koichi Yamada,et al.  An Efficient Algorithm for Traffic Sign Detection , 2006, Journal of Advanced Computational Intelligence and Intelligent Informatics.

[5]  T. Asakura,et al.  A study on traffic sign recognition in scene image using genetic algorithms and neural networks , 1996, Proceedings of the 1996 IEEE IECON. 22nd International Conference on Industrial Electronics, Control, and Instrumentation.

[6]  Alexandre R. J. François.  Real-Time Multi-Resolution Blob Tracking , 2004 .

[7]  Marco Campani,et al.  Robust method for road sign detection and recognition , 1996, Image Vis. Comput..

[8]  Arturo de la Escalera,et al.  Traffic sign recognition and analysis for intelligent vehicles , 2003, Image Vis. Comput..