@article{ref1,
title="Drowsy driver mobile application: development of a novel scleral-area detection method",
journal="Computers in biology and medicine",
year="2017",
author="Mohammad, Faisal and Mahadas, Kausalendra and Hung, George K.",
volume="89",
number="",
pages="76-83",
abstract="A reliable and practical app for mobile devices was developed to detect driver drowsiness. It consisted of two main components: a Haar cascade classifier, provided by a computer vision framework called OpenCV, for face/eye detection; and a dedicated JAVA software code for image processing that was applied over a masked region circumscribing the eye. A binary threshold was performed over the masked region to provide a quantitative measure of the number of white pixels in the sclera, which represented the state of eye opening. A continuously low white-pixel count would indicate drowsiness, thereby triggering an alarm to alert the driver. This system was successfully implemented on: (1) a static face image, (2) two subjects under laboratory conditions, and (3) a subject in a vehicle environment.<br><br>Copyright © 2017 Elsevier Ltd. All rights reserved.<p /> <p>Language: en</p>",
language="en",
issn="0010-4825",
doi="10.1016/j.compbiomed.2017.07.027",
url="http://dx.doi.org/10.1016/j.compbiomed.2017.07.027"
}