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http://dx.doi.org/10.9717/kmms.2016.19.6.1024

System for Detecting Driver's Drowsiness Robust Variations of External Illumination  

Choi, WonWoong (Dept. of Software Convergence Engineering, Chosun University)
Pan, Sung Bum (Dept. of Electronics Engineering, Chosun University)
Shin, Ju Hyun (Dept. of Control and Instrumentation Robot Engineering, Chosun University)
Publication Information
Journal of Korea Multimedia Society / v.19, no.6, 2016 , pp. 1024-1033 More about this Journal
Abstract
In this study, a system is proposed for analyzing whether driver's eyes are open or closed on the basis of images to determine driver's drowsiness. The proposed system converts eye areas detected by a camera to a color space area to effectively detect eyes in a dark situation, for example, tunnels, and a bright situation due to a backlight. In addition, the system used a thickness distribution of a detected eye area as a feature value to analyze whether eyes are open or closed through the Support Vector Machine(SVM), representing 90.09% of accuracy. In the experiment for the images of driver wearing glasses, 83.83% of accuracy was obtained. In addition, in a comparative experiment with the existing PCA method by using Eigen-eye and Pupil Measuring System the detection rate is shown improved. After the experiment, driver's drowsiness was identified accurately by using the method of summing up the state of driver's eyes open and closes over time and the method of detecting driver's eyes that continue to be closed to examine drowsy driving.
Keywords
Safe Driving System; Driver's Drowsiness; External Illumination; State of Driver's Eyes Open and Close; SVM; Drowsiness Decision;
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Times Cited By KSCI : 3  (Citation Analysis)
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