Traffic sign detection and recognition has been the active research topic due to its potential applications in intelligent transportation. However, detection and recognition of traffic panels containing much information, still remains to be a challenging problem. This paper proposes a method to detect and recognize traffic panels from street-level images in the urban scenes and to analyze the information on them. The traffic panels are detected based on histogram of oriented gradient and linear support vector machines. The text strings and symbols on traffic panels are segmented using connected component analysis method. Finally, the symbols on traffic panels are recognized by means of a model named bag of spatial visual words. Experimental results on images from Baidu Panorama Map prove the effectiveness of the proposed method.
展开▼
