Drowsiness Detection using Image Processing

Palak Agarwal; Naveen Pal; Ayushi Rohela; Ashish Yadav

Abstract

These days, an ever increasing number of callings require long haul focus. Drivers must watch out for the street, so they can respond to unexpected occasions right away. Driver exhaustion regularly turns into an immediate reason for some auto collisions. In this way, there is a need to build up the frameworks that will identify and tell a driver of her/him awful psychophysical condition, which could altogether lessen the quantity of exhaustion related auto collisions. In any case, the advancement of such frameworks experiences numerous challenges identified with quick and appropriate acknowledgment of a driver's weakness side effects. One of the technical possibilities to implement driver drowsiness detection systems is to custom the vision-based method. This article presents the currently used driver drowsiness detection systems. Here we are detecting the driver drowsiness by estimating vision system of him.

Keywords

Image Processing, Machine Learning, Drowsiness Detection

Reference

[1] Miaou, “Study of Vehicle Scrap page Rates,” Oak Ridge National Laboratory, Oak Ridge, TN,, S.P.,April 2012.

[2] Wreggit, S. S., Kim, C. L., and Wierwille, W. W., Fourth Semi-Annual Research Report”, Research on VehicleBased Driver Status Performance Monitoring”, Blacksburg, VA: Virginia Polytechnic Institute and State University, ISE Department, January 2013.

[3] Bill Fleming, “New Automotive Electronics Technologies”, International Conference on Pattern Recognition, pp. 484- 488,December 2012.

[4] Ann Williamson and Tim Chamberlain,“Review of on-road driver fatigue monitoring devices”, NSW Injury Risk Management Research Centre, University of New South Wales, , July 2013.

[5] E. Rogado, J.L. García, R. Barea, L.M. Bergasa, Member IEEE and E. López, February, 2013, “Driver Fatigue Detection System”, Proceedings of the IEEE International Conference on Robotics and Biometics, Bangkok, Thailand.

[6] Boon-Giin Lee and Wan-Young Chung, Member IEEE, “Driver Alertness Monitoring Using Fusion of Facial Features and Bio-Signals”, IEEE Sensors Journal, VOL. 12, NO. 7, July 2012.

[7] H. Singh, J. S. Bhatia, and J. Kaur, “Eye tracking based driver fatigue monitoring and warning system”, in Proc. IEEE IICPE, New Delhi, India, Jan. 2014.

Cites this article as

[Palak Agarwal , Naveen Pal , Ayushi Rohela , Ashish Yadav (2018), Drowsiness Detection using Image Processing, International Journal of Innovative Research in Engineering & Management (IJIREM), Vol-5, Issue-6, Page No-238-239], (ISSN 2347 - 5552). www.ijirem.org