Multi-Feature Fusion Based Circular Traffic Sign Detection
ZHANG Jing, HE Ming-Yi, DAI Yu-Chao, QU Xiao-Gang
Shaanxi Key Laboratory of Information Acquisition and Processing, School of Electronics and Information, Northwestern Polytechnical University, Xian 710129
Abstract Based on color and shape features of circular traffic sign, a multi-feature fusion based circular traffic sign detection algorithm is proposed. Firstly, color segmentation and achromatic decomposition are used to extract area containing circular traffic signs, and thus most of the background area is eliminated. Then, edge detection is applied, and the output edges are stored by chain code. Features, including length of contour, circularity and aspect ratio, are used to further eliminate background area. Finally, according to the shape feature of circular traffic sign, nonlinear least squares method is employed to detect the exact traffic signs. Effectiveness of the proposed algorithm is demonstrated preliminarily on real images captured under various weather and illumination conditions.
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2011, Vol. 24 
