Real-Time Speed Limit Sign Detection and Recognition from Image Sequences

Traffic sign, especially speed limit sign recognition is important in a driver assistance system. In this paper, a robust approach for real-time detection and recognition of speed limit sign is presented. It consists of two major steps: sign detection and sign recognition. In detection stage, Fast Radial Symmetry Transform is utilized to detect possible sign locations. Then the new method proposed, that is named “Largest Containing Circle” is used to segment characters region. In recognition stage, one fuzzy template matching method is applied to coarse recognize the sign number character, Furthermore, we conduct a similar character recognizer based on the local feature vector for fine recognition of the character. Experimental results in different conditions, including sunny, cloudy, foggy and rainy weather demonstrates that most speed limit signs can be correctly detected and recognized with a high accuracy and the average processing time is 15ms per frame on a standard PC.