Driver Drowsiness Detection Using Canny Edge Detection and Hough Transformation

Authors

  • Ankit Sureshbhai Jayswal U.V. Patel College of Engineering, Ganpat University, Mehsana.
  • Prof. Rachana V. Modi Assistant Professor Information Technology Department U.V. Patel College of Engineering Mehsana

DOI:

https://doi.org/10.37591/joosd.v4i3.1134

Abstract

Abstract

The aim of this study is to save many lives during road accidents because of driver’s drowsiness. A method for detecting sleepiness in drivers is developed by using a camera that points directly towards the driver’s face and captures the video. Once a video is captured, it detects a face and continues monitoring the face region and eyes in order to detect fatigue. Viola Jones algorithm is used to detect human face and eyes in this paper. The system is able to monitoring eyes and determines whether the eyes are open or closed. For that, here we have used the combination of two algorithms: Canny Edge Detection and Hough Transformation. Hough Transformation is used to detect iris from eye template. In such a case when drowsiness is detected, a warning alarm is issued to alert the driver. It can determine a time proportion of eye closure as the proportion of a time interval that the eye is in the closed position.

Keywords: Canny edge detection, Euclidean method, Hough round transform

Cite this Article

Jayswal Ankit S., Prof. Rachana V. Modi. Driver Drowsiness Detection Using Canny Edge Detection and Hough Transformation. Journal of Open Source Developments. 2017; 4(3):9–13p.


Author Biographies

  • Ankit Sureshbhai Jayswal, U.V. Patel College of Engineering, Ganpat University, Mehsana.
    Information Technology
  • Prof. Rachana V. Modi, Assistant Professor Information Technology Department U.V. Patel College of Engineering Mehsana
    Assistant ProfessorInformation Technology DepartmentU.V. Patel College of EngineeringMehsana

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Published

2017-11-29

Issue

Vol. 4 No. 3 (2017)

Section

Research Articles

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