Table of Contents
International Journal of Vehicular Technology
Volume 2014, Article ID 678786, 7 pages
Research Article

Driver’s Fatigue Detection Based on Yawning Extraction

1LRIT Associated Unit to CNRST (URAC 29), Faculty of Sciences, University of Mohammed V-Agdal, 4 Avenue Ibn Battouta, B.P. 1014, Rabat, Morocco
2LGS, ENSA, Ibn Tofail University, B.P 241, Kenitra, Morocco

Received 25 May 2014; Revised 20 July 2014; Accepted 20 July 2014; Published 6 August 2014

Academic Editor: Aboelmagd Noureldin

Copyright © 2014 Nawal Alioua et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The increasing number of traffic accidents is principally caused by fatigue. In fact, the fatigue presents a real danger on road since it reduces driver capacity to react and analyze information. In this paper we propose an efficient and nonintrusive system for monitoring driver fatigue using yawning extraction. The proposed scheme uses face extraction based support vector machine (SVM) and a new approach for mouth detection, based on circular Hough transform (CHT), applied on mouth extracted regions. Our system does not require any training data at any step or special cameras. Some experimental results showing system performance are reported. These experiments are applied over real video sequences acquired by low cost web camera and recorded in various lighting conditions.