Abstract
Road accidents happen frequently, and the main cause for this is driver’s carelessness. This carelessness occurs due to driver inattention or driver drowsiness. Detection of this driver’s carelessness and alerting the driver at right time is the main concern so as to reduce traffic accidents. In this paper, a robust method is presented based on eyes state analysis in real time which works well for noisy images as well. The main aim is to detect drowsiness or distraction of driver while driving during day as well as at night and alert the driver by issuing a warning signal. Firstly, real-time video acquisition starts by initializing the camera. Then, the eye detection is done by using Viola–Jones algorithm. Lastly, iris detection is done by using circular Hough transform technique for checking the eyes state. The proposed method has shown an accuracy of 99% during daytime and an accuracy of 96% during nighttime and 91% accuracy for noisy frames.
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References
H. Kalbkhani, M. G. Shayesteh, and S. M. Mousavi, “Efficient Algorithms for Detection of Face, Eye and Eye State,” IET Computer Vision, vol. 7, no. 3, pp. 184–200, January 2013.
(2016, March) Centers for Disease Control and Prevention. [Online]. https://www.cdc.gov/motorvehiclesafety/distracted_driving/.
Jasni and A. S. BT, “Drowsiness Detection for Car Assisted Driver System Using Image Processing Analysis,” University Malaysia Pahang, Pekan, Project Report, 2010.
S. R and D. S. Dharan, “Driver’s Drowsiness Detection Using Circular Hough Transform and Iris Visibility Ratio Analysis,” International Journal of Engineering Research and Technology, vol. 3, no. 5, pp. 2183–2185, May 2014.
A. Girit, “Drowsy Driver Detection Using Image Processing,” Middle East Technical University, Turkish, Thesis Report, 2014.
J. Gill and Chisty, “A Brief Survey-Driver Drowsiness Detection System,” International Journal for Multi Disciplinary Engineering and Business Management, vol. 3, no. 2, pp. 92–97, April 2015.
H. Kaur, “Driver Drowsiness Detection System Using Image Processing,” International Journal on Advanced Computer Theory and Engineering, vol. 4, no. 5, pp. 35–40, 2015.
S. Batchu and S. P. Kumar, “Driver Drowsiness Detection to Reduce the Major Road Accidents in Automotive Vehicles,” International Research Journal of Engineering and Technology, vol. 2, no, 1, pp. 345–349, April 2015.
(2015, March) The Royal Society for the Prevention of Accidents. [Online]. http://www.rospa.com/road-safety/advice/drivers/distraction/fact-sheet/.
N. Alioua, A. Amine, M. Rziza, and D. Aboutajdine, “Eye State Analysis Using Iris Detection Based on Circular Hough Transform,” in International Conference on Multimedia Computing and Systems, Ouarzazate, 2011, pp. 1–5.
M. S. Devi, M. V. Choudhari, and D. P. Bajaj, “Driver Drowsiness Detection Using Skin Color Algorithm and Circular Hough Transform,” in Fourth International Conference on Emerging Trends in Engineering and Technology, Port Louis, 2011, pp. 129–134.
N. Cherabit, F. Z. Chelali, and A. Djeradi, “Circular Hough Transform for Iris Localization,” Science and Technology, vol. 2, no. 5, pp. 114–121, 2012.
S. Hichri, H. Nakkach, F. Benzarti, and H. Amiri, “Monitoring of Driver’s Drowsiness based on Eyes State Analysis,” in Third International Conference on Automation, Control, Engineering and Computer Science, Hammamet, 2016, pp. 779–783.
S. Darshana, D. Fernando, S. Jayawardena, S. Wickramanayake, and D. C. DeSilva, “Efficient PERCLOS and Gaze Measurement Methodologies to Estimate Driver Attention in Real Time,” in Fifth International Conference on Intelligent Systems, Modelling and Simulation, Langkawi, 2014, pp. 289–294.
G. J. AL-Anizy, M. J. Nordin, and M. M. Razooq, “Automatic Driver Drowsiness Detection Using Haar Algorithm and Support Vector Machine Techniques,” Asian Journal of Applied Sciences, vol. 8, no. 2, pp. 149–157, 2015.
A. Punitha and M. K. Geetha, “Driver Eye State Detection Using Minimum Intensity Projection– An Application to Driver Fatigue Alertness,” Indian Journal of Science and Technology, vol. 8, no. 17, pp. 1–9, August 2015.
W.-B. Horng and C.-Y. Chen, “A Real-Time Driver Fatigue Detection System Based on Eye Tracking and Dynamic Template Matching,” Tamkang Journal of Science and Engineering, vol. 11, no. 1, pp. 65–72, 2008.
S. H. Parmar, M. Jajal, and Y. P. Brijbhan, “Drowsy Driver Warning System Using Image Processing,” International Journal of Engineering Development and Research, vol. 1, no. 3, pp. 78–83, December 2014.
W. Han, Y. Yang, G.-B. Huang, O. Sourina, F. Klanner, and C. Denk, “Driver Drowsiness Detection Based on Novel Eye Openness Recognition Method and Unsupervised Feature Learning,” in IEEE International Conference on Systems, Man, Cybernetics, Hong Kong, 2015, pp. 1470–1475.
A. Soetedjo, “Eye Detection Based-on Color and Shape Features,” International Journal of Advanced Computer Science and Applications, vol. 3, no. 5, pp. 17–22, 2011.
M. S. Podder and M. S. Roy, “Driver’s Drowsiness Detection Using Eye Status to Improve the Road Safety,” International Journal of Innovative Research in Computer and Communication Engineering, vol. 1, no. 7, pp. 1490–1497, September 2013.
V. E. Dahiphale and S. R, “Real-Time Computer Vision System for Continuous Face Detection and Tracking,” International Journal of Computer Applications, vol. 122, no. 18, pp. 1–5, July 2015.
M. Chaudhari, S. Sondur, and G. Vanjare, “A Review on Face Detection and Study of Viola Jones Method,” International Journal of Computer Trends and Technology, vol. 25, no. 1, pp. 54–61, July 2015.
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Verma, S., Girdhar, A., Jha, R.R.K. (2018). Real-Time Eye Detection Method for Driver Assistance System. In: Perez, G., Tiwari, S., Trivedi, M., Mishra, K. (eds) Ambient Communications and Computer Systems. Advances in Intelligent Systems and Computing, vol 696. Springer, Singapore. https://doi.org/10.1007/978-981-10-7386-1_58
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DOI: https://doi.org/10.1007/978-981-10-7386-1_58
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