DRIVER DROWSINESS DETECTION SYSTEM USING DEEP LEARNING

DRIVER DROWSINESS DETECTION SYSTEM USING DEEP LEARNING

1BALAKRISHNAN K, 2KARTHIKEYAN N, 3HARIHARAN B, 4NISHADEVI K
1Student, Department of Artificial Intelligence, Bannari Amman Institute of Technology. Sathayamangalam . 2Student, Department of Artificial Intelligence, Bannari Amman Institute of Technology. Sathayamangalam . 3Student, Department of Artificial Inteligence. Bannari Amman Institute of Technology. Sathayamangalam . 4Assistant professor, Department of Artificial Inteligence. Bannari Amman Institute of Technology. Sathayamangalam .

Abstract—Drowsy Driver Detection System has been developed using a non-intrusive machine vision based concepts. The system uses a small monochrome security camera that points directly towards the driver’s face and monitors the driver’s eyes in order to detect fatigue. In such a case when fatigue is detected, a warning signal is issued to alert the driver. This report describes how to find the eyes, and also how to determine if the eyes are open or closed. The algorithm developed is unique to any currently published papers, which was a primary objective of the project.. Taking into account the knowledge that eye regions in the face present great intensity changes, the eyes are located by finding the significant intensity changes in the face. Once the eyes are located, measuring the distances between the intensity changes in the eye area determine whether the eyes are open or closed. A large distance corresponds to eye closure. If the eyes are found closed for 5 consecutive frames, the system draws the conclusion that the driver is falling asleep and issues a warning signal. The system is also able to detect when the eyes cannot be found, and works under reasonable lighting conditions.

Index Terms—Face Detection, Eye Detection, Image Processing