Traffic Sign Detection and Recognition for Driving Assistance System


  • Chin-Chen Chang Department of Computer Science and Information Engineering, National United University, Miaoli 360, Taiwan
  • Huei-Yung Lina Department of Electrical Engineering and Advanced Institute of Manufacturing with High-tech Innovations, National Chung Cheng University, Chiayi 621, Taiwan
  • Shu-Chun Huang Department of Electrical Engineering and Advanced Institute of Manufacturing with High-tech Innovations, National Chung Cheng University, Chiayi 621, Taiwan



In this paper, we present a traffic sign detection and recognition for a driving assistance system. The proposed approach consists of two subsystems for detection and recognition. First, the road sign detection subsystem adopts the color information to filter out most of irrelevant image regions. Image segmentation and hierarchical grouping are then used to select candidate regions of road signs. For the road sign recognition subsystem, a convolutional neural network (CNN) is adopted to classify traffic signs for candidate regions. Experimental results show that our approach can obtain the desired results effectively.


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How to Cite

Chang, C.-C., Lina, H.-Y., & Huang, S.-C. (2018). Traffic Sign Detection and Recognition for Driving Assistance System. European Journal of Applied Sciences, 6(3), 17.