Abstract: Traffic sign classification is the basic link of traffic sign recognition system, and traffic sign shape recognition is the core part of traffic sign classification. This paper studies traffic signs and analyzes them into three categories: ban signs, warning signs and instruction signs, respectively. A new algorithm is proposed, which uses the statistical feature of edge trend to reflect the feature of target shape. It is combined with BP neural network to identify the shape of traffic signs. Firstly, the color information is used to realize the segmentation of traffic signs. Secondly, the edge trend of traffic signs is recorded and the proportion is counted. Finally, BP neural network is used for classification to realize the identification of the shape of traffic signs. This method has good recognition effect and speed for traffic sign images with different tilt angles and shooting angles.

Key words: shape recognition, traffic sign classification, edge trend, directional feature statistics, BP neural network