Open Access
ARTICLE
Driver Fatigue Detection System Based on Colored and Infrared Eye Features Fusion
Yuyang Sun1, Peizhou Yan2, *, Zhengzheng Li2, Jiancheng Zou3, Don Hong4
1 School of Mathematical Sciences, Capital Normal University, Beijing, 100048, China.
2 School of Electrical and Control Engineering, North China University of Technology, Beijing, 100144, China.
3 School of Sciences, North China University of Technology, Beijing, 100144, China.
4 Department of Mathematical Sciences, Middle Tennessee State University, Murfreesboro, TN 37132, USA.
* Corresponding Author: Peizhou Yan. Email: .
Computers, Materials & Continua 2020, 63(3), 1563-1574. https://doi.org/10.32604/cmc.2020.09763
Received 17 January 2020; Accepted 04 April 2020; Issue published 30 April 2020
Abstract
Real-time detection of driver fatigue status is of great significance for road
traffic safety. In this paper, a proposed novel driver fatigue detection method is able to
detect the driver’s fatigue status around the clock. The driver’s face images were captured
by a camera with a colored lens and an infrared lens mounted above the dashboard. The
landmarks of the driver’s face were labeled and the eye-area wassegmented. By calculating
the aspect ratios of the eyes, the duration of eye closure, frequency of blinks and PERCLOS
of both colored and infrared, fatigue can be detected. Based on the change of light intensity
detected by a photosensitive device, the weight matrix of the colored features and the
infrared features was adjusted adaptively to reduce the impact of lighting on fatigue
detection. Video samples of the driver’s face were recorded in the test vehicle. After
training the classification model, the results showed that our method has high accuracy on
driver fatigue detection in both daytime and nighttime.
Keywords
Cite This Article
Y. Sun, P. Yan, Z. Li, J. Zou and D. Hong, "Driver fatigue detection system based on colored and infrared eye features fusion,"
Computers, Materials & Continua, vol. 63, no.3, pp. 1563–1574, 2020. https://doi.org/10.32604/cmc.2020.09763
Citations