Abstract

Alertness of the driver is very important to reduce accidents that occur. Sometimes due to long journey, the drivers often get tired and suffer from the problems of sleepiness. So it is important to alert the driver when they are drowsy. In this work, a technique has been developed to monitor the drivers during their whole journey, which is done on the basis of detecting their eyes or body posture. Several methods have been already designed for the detection of drowsiness of the driver. The algorithm is designed using MATLAB. This method includes a sensor or camera which will capture the image and the captured images are continuously monitored and send to the buzzer. The default template has already designed and fed as a reference source, so that the captured image can be easily matched with the reference image.p>

Keywords
Indian Sign Language, DWT, Computer Vision, HMMs, Gesture Recognition
How to Cite this Article?
Thakur, A., and Rathore, S. S. (2016). Mouth And Eye Detection Based Drowsy Driver Warning System Using Viola Jones Algorithm. i-manager’s Journal on Pattern Recognition, 3(3), 7-12.
References
[1]. M. Rizon and T. Kawaguchi, (2003). “Automatic Eye Detection using Intensity and Edge Information”. Proceedings IEEE TENCON, Kuala Lumpur, Vol.2, pp.415- 420.
[2]. Arun, S., Kenneth S., and Murugappan, M. (2012). “Detecting Driver Drowsiness based on Sensors: A Review”. Sensors, Vol.21, No.12, pp.16937-16953.
[3]. Shabnam Abtahi, Shervin Shirmohammadi, Behnoosh Hariri, Daniel Laroche, and Luc Martel, (2013). “A yawning measurement method using embedded smart cameras”. Instrumentation and Measurement Technology Conference (I2MTC) 2013 IEEE International, Minneapolis, MN, pp.1605-1608.
[4]. M.J. Flores, M. Anningll, and A. Escalera, (2009). “Real-Time Warning System for Driver Drowsiness Detection using Visual Information”. J. Intell. Robot System, Vol.59, No.2 , pp.103 -125.
[5]. Viola, and Jones, (2001). “Robust Real-time Object Detection”. IJCV, Vol.57, No.2, pp.137-154.
[6]. C. Zhang, X. Lin, R. Lu, P.H. Ho, and X. Shen, (2008). “An efficient message authentication scheme for vehicular communications”. IEEE Trans. Veh. TechnoI., Vol.57, No.6, pp.3357-3368.
[7]. Charles, C., Simon, G., & Michael, G., (2009). “Predicting Driver Drowsiness using Vehicle Measures: Recent Insights and Future Challenges”. Journal of Safety Research, Vol.40, No.2, pp.239-45.
[8]. G. Hosseini, and H. Hossein-Zadeh, A. (2006). “Display driver drowsiness warning system”. International Conference of the Road and Traffic Accidents, Tehran University.
[9]. L. M. Bergasa, and J. Nuevo, (2006). “Real-Time system for monitoring driver vigilance”. IEEE Transactions on Intelligent Transportation Systems, Vol.7, No.1, pp.63- 77.
[10]. P. Gejgus, and M. Sparka, (2003). “Face Tracking in Color Video Sequences”. SCCG’03 Proceedings of the 19 Spring Conference on Computer Graphics, Budmerice, Slovakia, pp.245-249.
[11]. R G Gonzales, and RE. Woods, (2002). Digital Image Processing, Second Edition. Prentice Hall.
[12]. Das, D., Shiyu, Z., & Lee, J. (2012). “Differentiating Alcohol-Induced Driving Behavior using Steering Wheel Signals”. Intelligent Transportation Systems, IEEE Transactions on, Vol.13, No.3, pp.1355-1368.
[13]. Hamzah S. AlZu'bi, Waleed Al-Nuaimy, and Nayel S. Al-Zubi, (2013). “EEG-based Driver Fatigue Detection”. IEEE Sixth International Conference on Developments in eSystems-Engineering (DeSE), pp.111-114.
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