@inproceedings{976c19257f9d4359ad31ddcdd94cb5ee,
title = "Evolutionary QR-based Traffic sign recognition system for next-generation intelligent vehicles",
abstract = "This paper introduces a dramatically novel traffic signs recognition (TSR) system that can perform traffic sign detection and tracking simultaneously. The proposed approach utilizes intensity images and the depth images, in parallel, to robustly detect and track traffic signs in real-time. Additionally, we suggest to supplement the ordinary traffic signs with the corresponding quick-response (QR) code plates that inherent the many advantages of the QR-codes, introducing the concept of QR-TSR systems.",
keywords = "Depth data, Extended detection, Intellignet vehicles, Kinect, Maximally stable extremal regions, QR-Codes",
author = "Ehab Salahat and Hani Saleh and Andrzej Sluzek and Mahmoud Al-Qutayri and Baker Mohammad and Mohammad Ismail",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 82nd IEEE Vehicular Technology Conference, VTC Fall 2015 ; Conference date: 06-09-2015 Through 09-09-2015",
year = "2016",
month = jan,
day = "25",
doi = "10.1109/VTCFall.2015.7390939",
language = "British English",
series = "2015 IEEE 82nd Vehicular Technology Conference, VTC Fall 2015 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2015 IEEE 82nd Vehicular Technology Conference, VTC Fall 2015 - Proceedings",
address = "United States",
}