Open AccessA Small Traffic Sign Detection Algorithm Based on Modified SSD
Author(s) -
Hongxin Shan,
Zihao Wang
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/646/1/012006
Subject(s) - computer science , robustness (evolution) , benchmark (surveying) , traffic sign , sign (mathematics) , algorithm , artificial intelligence , real time computing , data mining , mathematics , mathematical analysis , biochemistry , chemistry , geodesy , gene , geography
Traffic sign detection is an important part of many systems such as autonomous driving, driver safety and assistance. In this paper, the detection capability of SSD for small targets is analyzed and improved based on ssd_300 model. CSUST Chinese Traffic Sign Detection Benchmark (CCTSDB) dataset is used to train the model for Chinese road traffic conditions. The improved model was compared with ssd_300 model. The experimental results show that the mAP of the improved model on the test dataset achieves 0.85, which is 0.13 higher than ssd_300, and the algorithm can reach real-time detection. The improved model can effectively detect three categories of Chinese traffic signs and has strong robustness against various disturbances.