An Identification Framework to Determine Drowsy Drivers and Help in the Prevention of Road Accidents
Tanmay Jain1, Ayush Raina2, Sureshkumar N3
1Tanmay Jain, BTech Student, Computer Science and Engineering, Vellore Institute of Technology, Vellore, India.
2Ayush Raina, BTech Student, Computer Science and Engineering, Vellore Institute of Technology, Vellore, India.
3Dr. Sureshkumar N, Associate Professor, School of Computer Science and Engineering, Vellore Institute of Technology.
Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 2787-2791 | Volume-8 Issue-12, October 2019. | Retrieval Number: L25701081219/2019©BEIESP | DOI: 10.35940/ijitee.L2570.1081219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: There is less concentration to a possibly risky driving conduct – driving with fatigue. There has been a progression of innovation overtime to help drivers. In this paper, we propose a framework to check consciousness of a driver whether the person is an abled condition to drive. In this model, the individual’s face is recorded by a camera with face detection, and segmentation to segment eye and mouth features accurately. We utilize the discovery of face eyes and mouth and apply behavioral measures, for example, eye conclusion and yawning to recognize the tiredness of the driver. The spotlight set on planning a framework that will precisely screen the eye developments. This check can identify sufficiently early to evade road accidents.
Keywords: Drowsiness, Eye Blink, Fatigue Detection, Image Retrieval.
Scope of the Article: Patterns and Frameworks