AN INTEGRATED APPROACH FOR DRIVER’S DROWSINESS DETECTION

Abstract

Abstract— Driver's ability to control the vehicles is reduced when they are sleepy or exhausted. The main reason of the rising number of traffic fatalities and accidents is falling asleep while driving. Driving in drowsy state is therefore considered to be the most active field of research. A ninety grated strategy that depends on the EAR and MAR calculations as well as the eye and mouth closure status (PERCLOS) is proposed in this paper. This aids in determining whether the mouth is open or closed, or when driver is yawning. Using this approach, a camera is installed on the dashboard of the car to continuously take video of the face of the driver. After that, these video frame shares analyzed to see if the driver appears sleepy or not. Real-time testing was conducted for the proposed system.