Browse > Article
http://dx.doi.org/10.5302/J.ICROS.2016.15.0153

Development of a Drowsiness Detection System using Machine Vision  

Kang, Su Min (Department of Electronics Engineering, Dankook University)
Huh, Kyung Moo (Department of Electronics Engineering, Dankook University)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.22, no.4, 2016 , pp. 266-270 More about this Journal
Abstract
In this paper, we propose a technique of drowsiness detection using machine vision. The drowsiness of vehicle driver is often the primary cause of motor vehicle accidents. Therefore, the checking of eye images for detecting drowsiness status of driver is critical for preventing these accidents. In our suggested method, we analyze the changes of histogram and edge of eye region images which are acquired using CCD camera. We developed a drowsiness detection system using the histogram and edge change information. The experimental results show that our proposed method enhances the accuracy of detecting drowsiness nearly to 98%, and can be used for preventing vehicle accidents due to the drowsiness of drivers.
Keywords
drowsiness detection; histogram; edge detection; machine vision;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
연도 인용수 순위
1 M. Chau and M. Betke, "Real time eye tracking and blink detection with USB cameras," Boston University Computer Science Technical Report, no. 2005-12, May 2005.
2 N. Sharma and V. K. Banga, "Drowsiness warning system using artificial intelligence," World Academy of Science, Engineering and Technology, vol. 4, no. 7, pp. 1771-1773, 2010.
3 J.-I. Kim, H.-S. Ahn, G.-M. Jeong, and Chan-Woon, "Estimation of a Driver's physical condition using real-time vision system," The Journal of The Institute of Webcasting, Internet and Telecommunication, vol. 9, no. 5, pp. 213-224, Oct. 2009.
4 Y. H. Joo, J. K. Kim, and I. H. Ra, "Intelligent drowsiness drive worning system," Journal of Intelligence and information System, vol. 18, no. 2, pp. 223-229, Apr. 2008.
5 A. Malla, P. Davidson, P. Bones, R. Green, and R. Jones, "Automated video-based measurement of eye closure for detecting behavioral microsleep," 32nd Annual International Conference of the IEEE EMBS, pp. 6742-6744, Aug. 2010.
6 M. H. Yang, D. J. Kriegman, and N. Ahuja, "Detecting faces in images: A survey," IEEE PAMI, vol. 24, no. 1, pp. 34-58, Jan. 2002.   DOI
7 J.-M. Choi, H. Song, S. H. Park, and C.-D. Lee, "Implementation of driver fatigue monitoring system," The Journal of the Institute of Webcasting, Internet and Telecommunication, vol. 37, no. 8, pp. 711-720, Aug. 2012.
8 H.-S. Cha and S.-H. Hong, "Advanced retinex algorithm for image enhancement," Journal of Korea Multimedia Society, vol. 16, no. 1, pp. 29-41, Jan. 2013.   DOI
9 S.-M. Kang, K.-M. Huh, and Y.-B. Joo, "Development of a drowsiness detection system using a histogram for vehicle safety," Journal of Institute of Control, Robotics and Systems, vol. 21, no. 2, pp. 102-107, Feb. 2015.   DOI
10 S.-M. Kang, S.-H. Park, and K.-M. Huh, "An enhanced histogram matching method for automatic visual defect inspection robust to illumination and resolution," Journal of Institute of Control, Robotics and Systems, vol. 20, no. 10, pp. 1030-1035, Oct. 2014.   DOI