Digital Image Processing

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Drowsy Driver Alert System Using Image Processing


Affiliations
1 Bannari Amman Institute of Technology, Sathyamangalam, TN, India
2 Bannari Amman Institute of Technology, Sathyamangalam, TN, India
     

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A non-intrusive machine vision based concept is adopted in the development of Drowsy Driver Alert System. The system uses a small monochrome security camera that points directly towards the driver's face and monitors the driver's eyes in order to detect fatigue. The aim of this work is to develop a prototype drowsiness detection system. This paper describes about how to monitor the eye and detect for the eye closure. The system deals with information obtained for the binary version of the image to find the edges of the face, which narrows the area of where the eyes may exist. By considering the fact that the eye regions in the face reflect greater intensity changes than other parts, the eyes are located by finding the significant intensity changes in the face. The intensity changes in the eyes area determine whether eyes are open or closed. If the eyes are found closed for five consecutive frames, the driver is falling asleep and issues a warning signal.

Keywords

Drowsiness Detection, Feature Extraction, Frame, Image Segmentation, Non-Invasive System.
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  • Road safety information, rospa, -“driver fatigue and road accidents”, www.rospa.com, 2011.

  • RuianLiu,et.al, "Design of face detection and tracking system," Image and Signal Processing (CISP),2010 3rd International Congress on ,vol.4, no., 16-18 Oct. 2010, pp.1840-1844.

  • P.C. Philipp, E. Udo and U. Peter,“Experimental evaluation of eye-blink parameters as a drowsiness measure” European Journal of App lied Physiology, Volume 89, Issue 3 -4, 2003,319-325.

  • P. Ilkwo n, A. Jung-Ho and B. Hyeran,"Efficient Measurement of Eye Blinking underVarious Illumination Conditions for Drowsiness Detectio n Systems." Pattern Recognition, I CPR 2006.

  • Xianghua Fan, et.al, "The system of face detection based on OpenCV," Control and Decision Conference (CCDC), 2012 24thChinese, 23-25 May 2012, pp.648-651.

  • Goel, P, et.al. “Hybrid Approach of Haar Cascade Classifiers and Geometrical Properties of Facial Features Applied to Illumination Invariant Gender Classification System” Computing Sciences (ICCS), 2012 International Conference on, 14-15 Sept. 2012, pp.132- 136.

  • Parris, J., et.al, “Face and eye detection on hard datasets,” Biometrics (IJCB), 2011 International Joint Conference on, 11-13 Oct. 2011, pp.1-10.

  • Y. Dong, Z. Hu, K. Uchimura, and N. Murayama, “Driver inattention monitoring system for intelligent vehicles: A review,” IEEE Trans. Transp. Syst., vol. 12, no. 2, 2011, pp. 596–614.

  • R. N. Khushaba, S. Kodagoda, S. Lal, and G. Dissanayake, “Driver drowsiness classification using fuzzy wavelet-packet-based featureextraction algorithm,” IEEE Trans. Biomed. Eng., vol. 58, no. 1, pp. 121– 131, Jan. 2011.

  • S. Vitabile, A. De Paola, F. Sorbello, J Ambient Intell Human Comput, “A real- time non-intrusive FPGA-based Drowsiness system” Springer, University of Palermo, Italy 2011, pp.251-262.

  • Ralph Oyini Mbouna, Seong G.Kong, SeniorMember, IEEE, Visual Analysis of Eye State and Head Pose for Driver Alertness Monitoring, (IEEE), vol.14 ,2013,pp.1462-1469

  • Raoul Lopes , D.J Sanghvi, Aditya Shah,“Drowsiness Detection based on Eye Movement, Yawn Detection and Head Rotation”, Vol.2, No.6,2012.

  • Anirbandasgupta,anjithgeorge, “A Vision Based System For Monitoring The Loss Of Attention in Automotive Drivers”,(IEEE Transaction),vol.14,no.4 2013.

  • Shabnam Abtahi, Behnoosh, “Driver Drowsiness Monitoring Based on Yawning Detection”, Distributed Collaborative Virtual Environment Research Laboratory,University of Ottawa,Canada

  • Swati P. Kale, Deepak Dandekar, “Face Tracker for Head Position Detection”, National Conference on Innovative Paradigms in Engineering & Technology NCIPET, 2012

  • R. I. Hammoud, G. Witt, R. Dufour, A. Wilhelm, and T. Newman, “On driver eye closure recognition for commercial vehicles,” SAE Int. J. Com- mercial Veh., vol. 1, no. 1, pp. 454–463, Apr. 2009.


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  • Drowsy Driver Alert System Using Image Processing

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Authors

K. P. Sampoornam
Bannari Amman Institute of Technology, Sathyamangalam, TN, India
N. Saranya
Bannari Amman Institute of Technology, Sathyamangalam, TN, India

Abstract


A non-intrusive machine vision based concept is adopted in the development of Drowsy Driver Alert System. The system uses a small monochrome security camera that points directly towards the driver's face and monitors the driver's eyes in order to detect fatigue. The aim of this work is to develop a prototype drowsiness detection system. This paper describes about how to monitor the eye and detect for the eye closure. The system deals with information obtained for the binary version of the image to find the edges of the face, which narrows the area of where the eyes may exist. By considering the fact that the eye regions in the face reflect greater intensity changes than other parts, the eyes are located by finding the significant intensity changes in the face. The intensity changes in the eyes area determine whether eyes are open or closed. If the eyes are found closed for five consecutive frames, the driver is falling asleep and issues a warning signal.

Keywords


Drowsiness Detection, Feature Extraction, Frame, Image Segmentation, Non-Invasive System.

References