Detection and classification of eye state in ir camera for driver drowsiness identification

ICSIPA09 - 2009 IEEE International Conference on Signal and Image Processing Applications, Conference Proceedings

Volumn , Issue , 2009, Pages 340-345

  Bhowmick, Brojeshwar ^a   Kumar, K S Chidanand ^a  

^a TATA CONSULTANCY SERVICES   (India)

Author keywords

Bottom hat transformation; Driver drowsiness; Gray level co occurence ma trix(GLCM); Infra Red(IR); K means; Otsu Thresholding; Support vector machine(SVM)

Indexed keywords

CO-OCCURENCE; DRIVER DROWSINESS; GRAY LEVELS; INFRA RED; K-MEANS; THRESHOLDING;

CAMERAS; EYE PROTECTION; FACE RECOGNITION; IMAGING SYSTEMS; MATHEMATICAL MORPHOLOGY; SUPPORT VECTOR MACHINES;

SIGNAL DETECTION;

EID: 77954519883     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICSIPA.2009.5478674     Document Type: Conference Paper

References (15)

1. NHTSA: Drowsy driver detection and warning system for commercial vehicle drivers " Field proportional test design, analysis and progress". National Highway Traffic SafetyAdministration, Washington, DC.
2. Weirwille., WW Overview of Research on Driver Drowsiness Definition and Driver Drowsiness Detection. 14th International Technical Conference on Enhanced Safety of Vehicles, pp 23-26(1994).
3. Infrared Eye Detection,http://www.cse.unr.edu/CRCD/SummerOl/Scottf/ approaches.html
4. Shuyan Zhao.,Grigat R.R.:Robust Eye Detection under Active Infrared Illumination: 18th IEEE International conference on Pattern Recognition,pp.481- 484IEEE press,(2006).
5. Guang-yuan Zhang.,Bo Cheng., Rui-jia Feng., Jia-wen li.:Real-time driver eye detection method using support vector machine with hu invariant moments. International Conference on Machine Learning and Cybernetics,pp.2999-3004IEEE press,(2008).
6. Ling Gan.,Bing Cui.,Weixing Wang.:Driver Fatigue Detection Based on Eye Tracking. The sixth world congress on Intelligent Control and Automation,pp.5341-5344WCICA press,Dalian(2006)
7. Zutao Zhang.Jia-shu Zhang.:Driver Fatigue Detection Based Intelligent Vehicle Control. 18th International Conference on Pattern Recognition.pp. 1262- 1265.ICPR press, (2006).
8. Zhiwei Zhu., Qiang Ji.: Robust Real-Time Eye Detection and Tracking under Variable Lighting Conditions and Various Face Orientations. J.Computer Vision and Image Understanding. 98 124-154 (2005).
9. Vision and Image sciences laboratory. http://visl.technion.ac.il/ projects/2005w26/
10. Otsu N.:A Threshold Selection Method from Gray-Level Histograms.In: IEEE Transactions on Systems,Man and Cybernatics,pp.62-66IEEE press, (1979).
11. Yong Du., Peijun Ma., Xiaohong Su., Yingjun Zhang. "Driver Fatigue Detection based on Eye State Analysis", JCIS-2008 Proceedings, December 2008
12. M. Eriksson., N.R Papanikotopoulos. "Eye-tracking for detection of driver fatigue," in Proc .Int. Conf. Intelligent Transportation Systems, Boston, pp. 314 319, 1997.
13. D.F. Dinges, R. Grace. " PERCLOS: A valid psychophysiological measure of alertness as assessed by psychomotor vigilance" US Department of Transportation, Federal highway Administration. Publication Number FHV\A-MCRT-98-1006
14. Qiang Ji., Zhiwei Zhu., Peilin Lan. "Real Time Non-intrusive Monitoring and Prediction of Driver Fatigue", IEEE transctions on Vehicular Technology, vol 53pp 1052-10682004
15. Haralick, R.M., K. Shanmugan.Dinstein.I, "Textural Features for Image Classification", IEEE Transactions on Systems, Man, and Cybernetics, Vol.SMC-3pp. 610-621,1973