View Article |
Traffic sign detection and recognition: review and analysis
Nursabillilah Mohd Ali1, Mohd Safirin Karis2, Amar Faiz Zainal Abidin3, Bahzifadhli Bakri4, Ezreen Farina Shair5, Nur Rafiqah Abdul Razif6.
Over the years, traffic sign detection and recognition systems gives extra value to driver assistance when driving, leading to more user-friendly driving experience and much improved safety for passengers. As part of Advanced Driving Systems (ADAS) one can be benefitted by using this system especially with driving incapacities by alerting and aid them about the existence of traffic signs to minimized unwanted circumstances during driving such as fatigue, poor sight and adverse weather conditions. Though a various number of traffic sign detection systems have been revised in literature; the need of design with a robust algorithm still remains open for further research. This paper purposes to design a system capable of performing traffic sign detection while considering variations of challenges such as color illumination, computational difficulty and functional constraints existed. Traffic sign detection is divided into three main parts namely; Pre-processing, Color segmentation and Thresholding. The color segmentation method is vital as it presents a detailed investigation of vision based color spaces in this case RGB, HSV and CMYK considering varying illumination conditions under different environments. This paper further highlights possible improvements to the proposed approaches for traffic sign detection.
Affiliation:
- Universiti Teknikal Malaysia Melaka, Malaysia
- Universiti Teknikal Malaysia Melaka, Malaysia
- Universiti Teknikal Malaysia Melaka, Malaysia
- Universiti Teknikal Malaysia Melaka, Malaysia
- Universiti Teknikal Malaysia Melaka, Malaysia
- Universiti Teknikal Malaysia Melaka, Malaysia
Download this article (This article has been downloaded 120 time(s))
|
|
Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
|
6 |
Immediacy Index
|
0.000 |
Rank |
0 |
Indexed by |
Scopus 2020 |
Impact Factor
|
CiteScore (1.4) |
Rank |
Q3 (Engineering (all)) |
Additional Information |
SJR (0.191) |
|
|
|