A robust traffic sign recognition system

Becer, Hüseyin Caner
The traffic sign detection and recognition system is an essential part of the driver warning and assistance systems. In this thesis, traffic sign recognition system is studied. We considered circular, triangular and square Turkish traffic signs. For detection stage, we have two different approaches. In first approach, we assume that the detected signs are available. In the second approach, the region of interest of the traffic sign image is given. Traffic sign is extracted from ROI by using a detection algorithm. In recognition stage, the ring-partitioned method is implemented. In this method, the traffic sign is divided into rings and the normalized fuzzy histogram is used as an image descriptor. The histograms of these rings are compared with the reference histograms. Ring-partitions provide robustness to rotation because the rotation does not change the histogram of the ring. This is very critical for circle signs because rotation is hard to detect in circle signs. To overcome illumination problem, specified gray scale image is used. To apply this method to triangle and square signs, the circumscribed circle of these shapes is extracted. Ring partitioned method is tested for the case where the detected signs are available and the region of interests of the traffic sign is given. The data sets contain about 500 static and video captured images and the images in the data set are taken in daytime.
Citation Formats
H. C. Becer, “A robust traffic sign recognition system,” M.S. - Master of Science, Middle East Technical University, 2011.