Traffic sign detection using surround suppression of texture edges and cascade detector
Lei Cai, Chunyu Zhang, Bin Li, Chongbo Zhong, Qi Wang · 2010
This paper proposes a real-time traffic sign detection system. In order to extract accurately the shape feature of the traffic sign, reduce the computational load and further improve the traffic sign detection rate, a novel approach based on surround suppression of texture edges and cascade detector is presented. The principle of surround suppression mainly adds a computational step to the canny edge detector. This operator responds strongly to isolated lines and edges, region boundaries, and object contours. To discriminate a set of traffic signs from the background, a boosted cascade detector is used. In this boosted cascade detector, the adaboost algorithm is applied to select a small number of critical visual features and yield extremely efficient classifiers. Experiments show that our method is efficient to detect traffic signs and can be used in real-time traffic sign detection system.