Traffic Sign Recognition

Traffic sign recognition is a difficult task if aim is at detecting and recognizing signs in images captured from unfavorable environments. Co mplex background, weather, shadow, and other lighting-related problems may make it difficult to detect and recognize signs in the rural as well as the urban areas. Two major problems exist in the whole detection process. Road signs are frequently occluded partially by other vehicles. Many objects are present in traffic scenes which make the sign detection hard (pedestrians, other vehicles, buildings and billboards may confuse the detection system by patterns similar to that of road signs). Color informat ion fro m traffic scene images is affected by varying illu mination caused by weather conditions, time (day night) and shadowing (buildings)

[1]  Chao-Lin Liu,et al.  Traffic Sign Recognition in Disturbing Environments , 2003, ISMIS.

[2]  G.K. Siogkas,et al.  Detection, Tracking and Classification of Road Signs in Adverse Conditions , 2006, MELECON 2006 - 2006 IEEE Mediterranean Electrotechnical Conference.

[3]  Wen-Jia Kuo,et al.  Two-Stage Road Sign Detection and Recognition , 2007, 2007 IEEE International Conference on Multimedia and Expo.

[4]  Boguslaw Cyganek,et al.  Road Signs Recognition by the Scale-Space Template Matching in the Log-Polar Domain , 2007, IbPRIA.

[5]  C. Nunn,et al.  A novel region of interest selection approach for traffic sign recognition based on 3D modelling , 2008, 2008 IEEE Intelligent Vehicles Symposium.

[6]  Francisco López-Ferreras,et al.  Traffic sign shape classification and localization based on the normalized FFT of the signature of blobs and 2D homographies , 2008, Signal Processing.

[7]  Paulo Lobato Correia,et al.  Traffic Sign Recognition Based on Pictogram Contours , 2008, 2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services.

[8]  Luke Fletcher,et al.  Real-Time Speed Sign Detection Using the Radial Symmetry Detector , 2008, IEEE Transactions on Intelligent Transportation Systems.

[9]  Hilario Gómez Moreno,et al.  Traffic sign shape classification and localization based on the normalized FFT of the signature of blobs and 2D homographies , 2008 .

[10]  S. Lafuente-Arroyo,et al.  Traffic sign recognition system for inventory purposes , 2008, 2008 IEEE Intelligent Vehicles Symposium.

[11]  Wolfgang Rosenstiel,et al.  Design of an automotive traffic sign recognition system targeting a multi-core SoC implementation , 2010, 2010 Design, Automation & Test in Europe Conference & Exhibition (DATE 2010).

[12]  Saturnino Maldonado-Bascón,et al.  Goal Evaluation of Segmentation Algorithms for Traffic Sign Recognition , 2010, IEEE Transactions on Intelligent Transportation Systems.