Robust chinese traffic sign detection and recognition with deep convolutional neural network

Abstract

Detection and recognition of traffic sign, including various road signs and text, play an important role in autonomous driving, mapping/navigation and traffic safety. In this paper, we proposed a traffic sign detection and recognition system by applying deep convolutional neural network (CNN), which demonstrates high performance with regard to detection rate and recognition accuracy. Compared with other published methods which are usually limited to a predefined set of traffic signs, our proposed system is more comprehensive as our target includes traffic signs, digits, English letters and Chinese characters. The system is based on a multi-task CNN trained to acquire effective features for the localization and classification of different traffic signs and texts. In addition to the public benchmarking datasets, the proposed approach has also been successfully evaluated on a field-captured Chinese traffic sign dataset, with performance confirming its robustness and suitability to real-world applications.