Citation

Lim K, Hong Y, Choi Y, Byun H. PLoS One 2017; 12(3): e0173317.

Affiliation

Department of Computer Science, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul, Republic of Korea.

Copyright

(Copyright © 2017, Public Library of Science)

DOI

10.1371/journal.pone.0173317

PMID

28264011

Abstract

We present a General Purpose Graphics Processing Unit (GPGPU) based real-time traffic sign detection and recognition method that is robust against illumination changes. There have been many approaches to traffic sign recognition in various research fields; however, previous approaches faced several limitations when under low illumination or wide variance of light conditions. To overcome these drawbacks and improve processing speeds, we propose a method that 1) is robust against illumination changes, 2) uses GPGPU-based real-time traffic sign detection, and 3) performs region detecting and recognition using a hierarchical model. This method produces stable results in low illumination environments. Both detection and hierarchical recognition are performed in real-time, and the proposed method achieves 0.97 F1-score on our collective dataset, which uses the Vienna convention traffic rules (Germany and South Korea).

Language: en