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Using Haar classifiers to detect driver fatigue and provide alerts

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Abstract

Drowsiness is a transition state between being awake and asleep and can have serious consequences when occurring in tasks that require sustained attention such as driving. During the state of drowsiness, reaction time is slower, vigilance is reduced, and information processing is less efficient, which may cause accidents. The proposed Driver Fatigue Detection System (called FDS) aims to monitor the alertness of drivers to prevent them from falling asleep at the wheel. The system monitors the driver’s face using Haar feature classifiers with an increased training set to detect changes in the face of the driver quickly. A correlation matching algorithm is used to accurately provide the target’s position and track the target’s eyes according to the intensity, shape, and size of the pupils. FDS uses an IR illuminator to produce the desired bright pupil effect when the driver is wearing sunglasses. The resulting system operates in real-time, and is more accurate and less intrusive to the driver than other systems currently available.

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Acknowledgment

This work was funded by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah, under grant No. (611-008-D1433). The authors, therefore, acknowledge with thanks DSR technical and financial support.

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Authors and Affiliations

  1. Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, B.P. 42808, 21551, Girl Section, Jeddah, Saudi Arabia

    Lamiaa Fattouh Ibrahim, Maysoon Abulkhair, Manal AL-Garni, Ameerah AL-Mutiry, Fadiah AL-Gamdi & Roa’a Kalenen

  2. Department of Computer Science and Information, Institute of Statistical Studies and Research, Cairo University, Cairo, Egypt

    Lamiaa Fattouh Ibrahim

  3. Deanship of E-learning and Distance Education, Umm AL-Qura University, Mecca, Saudi Arabia

    Amal D. AlShomrani

Authors
  1. Lamiaa Fattouh Ibrahim
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  2. Maysoon Abulkhair
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  3. Amal D. AlShomrani
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  4. Manal AL-Garni
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  5. Ameerah AL-Mutiry
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  6. Fadiah AL-Gamdi
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  7. Roa’a Kalenen
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Correspondence to Lamiaa Fattouh Ibrahim.

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Ibrahim, L.F., Abulkhair, M., AlShomrani, A.D. et al. Using Haar classifiers to detect driver fatigue and provide alerts. Multimed Tools Appl 71, 1857–1877 (2014). https://doi.org/10.1007/s11042-012-1308-5

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  • DOI: https://doi.org/10.1007/s11042-012-1308-5

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