Railway sign detection and classification

This paper illustrates an application of computer vision at Italian railway signalling. From video frames captured on a driving train, each image is processed for robust object detection based on HSI color model, threshold analysis. Next, a classification algorithm based on shape feature and template matching is performed to detect the relevant railway signs and to discard objects of railway infrastructure. Our algorithm works with minimal computation and simple image processing techniques. Our approach can detect sign candidates in presence of complex background. Experimental results show relevant percentage of accuracy on a standard PC

[1]  Dariu Gavrila,et al.  Traffic Sign Recognition Revisited , 1999, DAGM-Symposium.

[2]  Lucas Paletta,et al.  Information Selection and Probabilistic 2D - 3D Integration in Mobile Mapping , 2003, ICVS.

[3]  Lucas Paletta.  Detection of traffic signs using posterior classifier combination , 2002, Object recognition supported by user interaction for service robots.

[4]  Y. Zhu,et al.  An integrated framework of vision-based vehicle detection with knowledge fusion , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[5]  Luis Moreno,et al.  Road traffic sign detection and classification , 1997, IEEE Trans. Ind. Electron..

[6]  G. Paar,et al.  Mobile detection of traffic infrastructure , 2001, ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585).

[7]  Jean Ponce,et al.  Computer Vision: A Modern Approach , 2002 .

[8]  Pavel Pudil,et al.  Road sign classification using Laplace kernel classifier , 2000, Pattern Recognit. Lett..

[9]  Sei-Wang Chen,et al.  An automatic road sign recognition system based on a computational model of human recognition processing , 2004, Comput. Vis. Image Underst..

[10]  Rafael C. González,et al.  Digital image processing using MATLAB , 2006 .

[11]  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).

[12]  A. Zelinsky,et al.  Real-time radial symmetry for speed sign detection , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[13]  H. Fleyeh,et al.  Color detection and segmentation for road and traffic signs , 2004, IEEE Conference on Cybernetics and Intelligent Systems, 2004..

[14]  Visvanathan Ramesh,et al.  A system for traffic sign detection, tracking, and recognition using color, shape, and motion information , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

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

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