Speed Limit Sign Detection Based on Gaussian Color Model and Template Matching

Traffic sign detection and recognition play crucial roles on the Intelligent Transportation System(ITS). Firstly, in YCbCr color space, color segmentation of the traffic scene images using Gaussian color model is calculated Cand traffic sign regions are obtained. Secondly, the morphology processing is utilized on the segmented image to extract the candidate traffic signs with a rectangle region in the original image to be selected according as its shape property. Finally, template matching is applied for speed signs classification. The performance of the proposed method is evaluated on Norwegian speed limit signs in natural environment. Experiment results show that this algorithm can effectively improve the traffic sign detection efficiency, which is used in traffic signs recognition and tracking of intelligent vehicles.