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     Research Journal of Applied Sciences, Engineering and Technology


Efficient Drowsiness Detection by Facial Features Monitoring

Mohd Shamian Bin Zainal, Ijaz Khan and Hadi Abdullah
Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Malaysia
Research Journal of Applied Sciences, Engineering and Technology  2014  11:2376-2380
http://dx.doi.org/10.19026/rjaset.7.539  |  © The Author(s) 2014
Received: August 15, 2013  |  Accepted: August 27, 2013  |  Published: March 20, 2014

Abstract

With increase in technology fatigue detection systems with more accuracy are overcoming their previous versions. The main focus of these systems is on robustness, accuracy and cost. Based on these factors this study presents a driver fatigue detection system design. This design uses facial features (eyes and mouth) to determine driver’s vigilance. A hybrid of two commonly known techniques Viola Jones and skin color detection is used as detection technique. Lastly some experimental results are given showing the accuracy and robustness of the proposed system.

Keywords:

Eyes state detection, fatigue monitoring, mouth detection, pixel color detection, threshold, viola Jones, yawning detection,


References

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Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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