Drowsy driver mobile application: Development of a novel scleral-area detection method. (1st October 2017)

• Record Type: Journal Article
• Authors: Mohammad, Faisal; Mahadas, Kausalendra; Hung, George K.
• Is Part Of: Computers in biology and medicine. Volume 89(2017)
• Page Start: 76
• Page End: 83
• Publication Date: 2017-10-01
• Subjects: Drowsy -- Fatigue -- Distraction -- Face/eye detection -- Scleral area -- OpenCV; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2017.07.027
• Languages: English
• ISSNs: 0010-4825

Abstract

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.