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System for Detecting Driver`s Drowsiness Robust Variations of External Illumination
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 Title & Authors
System for Detecting Driver`s Drowsiness Robust Variations of External Illumination
Choi, WonWoong; Pan, Sung Bum; Shin, Ju Hyun;
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 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;
 Language
Korean
 Cited by
1.
얼굴 특징점 기반의 졸음운전 감지 알고리즘,오미연;정유수;박길흠;

한국멀티미디어학회논문지, 2016. vol.19. 11, pp.1852-1861 crossref(new window)
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