Affiliations 

  • 1 Centre for Integrated Systems Engineering and Advanced Technologies, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia. safat.wali@siswa.ukm.edu.my
  • 2 Institute of Power Engineering, Universiti Tenaga Nasional, Kajang 43000, Malaysia. aaamajid2@gmail.com
  • 3 Institute of Power Engineering, Universiti Tenaga Nasional, Kajang 43000, Malaysia. hannan@uniten.edu.my
  • 4 Centre for Integrated Systems Engineering and Advanced Technologies, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia. draini@ukm.edu.my
  • 5 Centre for Integrated Systems Engineering and Advanced Technologies, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia. salinasamad@ukm.edu.my
  • 6 Institute of Power Engineering, Universiti Tenaga Nasional, Kajang 43000, Malaysia. pinjern@uniten.edu.my
  • 7 Institute of Power Engineering, Universiti Tenaga Nasional, Kajang 43000, Malaysia. muhamadm@uniten.edu.my
Sensors (Basel), 2019 May 06;19(9).
PMID: 31064098 DOI: 10.3390/s19092093

Abstract

The automatic traffic sign detection and recognition (TSDR) system is very important research in the development of advanced driver assistance systems (ADAS). Investigations on vision-based TSDR have received substantial interest in the research community, which is mainly motivated by three factors, which are detection, tracking and classification. During the last decade, a substantial number of techniques have been reported for TSDR. This paper provides a comprehensive survey on traffic sign detection, tracking and classification. The details of algorithms, methods and their specifications on detection, tracking and classification are investigated and summarized in the tables along with the corresponding key references. A comparative study on each section has been provided to evaluate the TSDR data, performance metrics and their availability. Current issues and challenges of the existing technologies are illustrated with brief suggestions and a discussion on the progress of driver assistance system research in the future. This review will hopefully lead to increasing efforts towards the development of future vision-based TSDR system.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.