Road Sign Analysis Using Multisensory Data

This paper deals with the problem of estimating the following road sign parameters: height, dimensions, visibility distance and partial occlusions. This work belongs to a framework whose main applications involve road sign maintenance, driver assistance, and inventory systems. From this paper we suggest a multisensory system composed from two cameras, a GPS receiver, and a distance measurement device, all of them installed in a car. The process consists of several steps which include road sign detection, recognition and tracking , and road signs parameters estimation. From some trigonometric properties, and a camera model, the information provided by the tracking subsystem and the distance measurement sensors, we estimate the road signs parameters. Results show that the described calculation methodology offers a correct estimation for all types of traffic signs.

[1]  S. Lafuente-Arroyo,et al.  Road Sign Tracking with a Predictive Filter Solution , 2006, IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics.

[2]  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.

[3]  Francisco López-Ferreras,et al.  Road-Sign Detection and Recognition Based on Support Vector Machines , 2007, IEEE Transactions on Intelligent Transportation Systems.

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

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

[6]  José Manuel Pastor,et al.  Visual sign information extraction and identification by deformable models for intelligent vehicles , 2004, IEEE Transactions on Intelligent Transportation Systems.

[7]  F. J. Acevedo-Rodríguez,et al.  TRAFFIC SIGN CLASSIFICATION INVARIANT TO ROTATIONS USING SUPPORT VECTOR MACHINES , 2007 .