Detection of a Drive Drowsiness Based on Eyes Closure and Yawning using Aspect Ratio

Abstract

Now a day’s people are very busy with their works so no one wants to waste their time while traveling by vehicles. But due to lack of sleepless night drivers some time they can sleep at driving itself. These leads to met the road accidents and to preventing these kind of accidents we implementing detecting drowsiness technology with machine learninglanguage. In this technology while driving we can detect driver face and finding land marks on face which means eye,nose and mouth. Later we can find aspect ratio of three landmarksand compare with specific threshold values if any landmarks of aspect ratio exceeded then it can generate drowsy alert on screen. Here for face detection we use HAAR Cascade algorithm and for finding landmarks it can use supporting cascade file which contains eyes, nose and mouth features.