Heavy Eyed Driver Detection System
A. Sharmila Agnal1, M. Balaji2, D. Adinarayana Reddy3, P. Vikas4

1A. Sharmila Agnal*, Department of Computer Science and Engineering SRM Institute of Science and Technology, Chennai, Tamil Nadu, India.
2M. Balaji, Department of Computer Science and Engineering SRM Institute of Science and Technology, Chennai, Tamil Nadu, India.
3D. Adinarayana Reddy, Department of Computer Science and Engineering SRM Institute of Science and Technology, Chennai, Tamil Nadu, India
4P. Vikas, Department of Computer Science and Engineering SRM Institute of Science and Technology, Chennai, Tamil Nadu, India

Manuscript received on October 15, 2019. | Revised Manuscript received on 23 October, 2019. | Manuscript published on November 10, 2019. | PP: 666-669 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4548119119/2019©BEIESP | DOI: 10.35940/ijitee.A4548.119119
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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: Driver fatigue is a great element in a massive variety of car accidents. Drowsy driver warning gadgets can form the foundation of the machine to maybe minimize the accidents associated with drowsiness. This paper uses a web cam for picture capturing. A web camera is connected to PC, and images are received and processed with the aid of mat lab using image processing. By setting the camera interior the car, we can monitor the face of the driver and look for the eye actions that say whether the driver is in a situation to drive. If the gadget detects that the driver is drowsy, a warning alert is issued. If eyes are detected as shut for too lengthy a beep sound is produced and as a result alerting the driver.
Keywords: Drowsiness, Eye Detection, SVM(Support Vector Machine), Classification
Scope of the Article: Classification