Driver Drowsiness Detection System using Raspberry Pi

Abstract: This paper presents a real-time driver drowsiness detection system for driving safety. Supported computer vision techniques, the driver’s face is found from color video captured in an exceedingly car. Then, face detection is used to locate the regions of the driver’s eyes, which are used because the templates for eye tracking in subsequently frames. Finally, the tracked eye’s images are used for drowsiness detection so as to come up with waring alarms. The proposed approach hasthree phases: Face, Eye detection and drowsiness detection The role of image processing is to acknowledge the face of the driving force then extracts the image of the eyes of the driving force for detection of drowsiness. The HAAR face detection algorithm takes captured frames of image as input and so the detected face as output. Next, CHT is employed to tracking eyes from the detected face. If the eyes are closed for a predefined period of your time the eyes of the motive force are considered closed and hence an alarm are beginning to alert the driving force.