Driver Drowsiness Detection System


Authors : Nikunj Mistry

Volume/Issue : Volume 5 - 2020, Issue 11 - November

Google Scholar : http://bitly.ws/9nMw

Scribd : https://bit.ly/378mc4K

A Driver Pattern Recognition System was developed, using concepts based on the concept of a nondisruptive machine. The machine uses a small monochrome safety camera that points directly to the driver's face and monitors the driver's eyes to detect fatigue. In such a case when fatigue is detected, the driver is alerted with a warning signal and if the driver is distracted he will also warn the driver to be careful. This report explains how the eyes can be found, and how to determine if the eyes are open or closed. The advanced algorithm differs from any currently published documents which is the main objective of the project. The device deals with finding facial edges using information obtained from the binary version of the image, which reduces the area where the eyes will be. When the surface area is defined, the eyes are obtained by measuring the horizontal area. Recalling the knowledge that the circuits of the eyes on the face bring about a great change in strength, The eyes are obtained by experiencing major changes in facial pressure. When the eyes are in a good position, measuring the distances between the size changes in the eye area determines whether the eyes are open or closed. The long distance is associated with blindfolds. If the eyes are found closed with five consecutive frames, the machine assumes the driver is asleep and sends an alarm. Also, the system can detect when the eyes are not available and operate under appropriate lighting conditions

Keywords : Binarisation, OpenCV, Detection Algorithm, Noise Removal.

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