Abstract
The increasing number of accidents is attributed to several factors, among which is the lack of concentration caused by fatigue. In This paper, we describe the approach developed to detect the driver’s drowsiness state from a video-based system to alert him and also reduce the number of accidents. Our approach uses a noninvasive method which excludes any human related elements. The latter calculates geometric descriptors. We analyze the signal extracted from the previous step by combining the two methods EMD (Empirical Mode Decomposition) and BP (Band Power). This analysis is confirmed by the SVM (Support Vector Machine) to classify the state of alertness of the driver.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Horng, W., Chen, C., Chang, Y., et al.: Software engineering – Driver fatigue detection based on eye tracking and dynamic template matching. In: IEEE International Conference on Networking, Sensing and Control. IEEE, New York (2004)
Sarbjit, S., Nikolaos, P.: Monitoring Driver Fatigue Using Facial Analysis Techniques. Intelligent Transportation Systems. ITS, Japan (1999)
Hiroshi, U., Masayuki, K.: Software engineering – Development of drowsiness detection system. Vehicle navigation and information systems conference. VNISC, Japan (1994)
Tnkehiro, I., Shinji, M., Kduo, K., Tomoaki, N., Shin, Y.: Driver Blink Measurement by the Motion Picture Processing and its Application to Drowsiness Detection. In: IEEE International Conference on Intelligent Transportation Systems. IEEE, Singapore (2002)
Masayuki, K., Hideo, O., Tsutomu, N.: Adaptability to ambient light changes for drowsy driving detection using image processing. UC Berkeley Transportation Library (1999)
Hongbiao, M., Zehong, Y., Yixu, S., Peifa, J.: A Fast Method for Monitoring Driver Fatigue Using Monocular Camera. In: Proceedings of the 11th Joint Conference on Information Sciences. JCIS, China (2008)
Yong, D., Peijun, M., Xiaohong, S., Yingjun, Z.: Driver Fatigue Detection based on Eye State Analysis. In: Proceedings of the 11th Joint Conference on Information Sciences. JCIS, China (2008)
Wenhui, D., Xiuojuan, W.: Driver Fatigue Detection Based On The Distance Of Eyelid. In: IEEE Workshop Vlsi Design and Video Tech. IEEE, China (2005)
Murray, J., Andrew, T., Robert, C.: A new method for monitoring the drowsiness of drivers. In: International Conference on Fatigue Management in Transportation Operations. CFMTO, USA (2005)
Takuhiro, O., Fumiya, N., Takashi, K.: Driver drowsiness detection focused on eyelid behavior. In: 34th Congress on Science and Technology of Thailand. CSTT, Thailand (2008)
Picot, A., Caplier, A., Charbonnier, S.: omparison between EOG and high frame rate camera for drowsiness detection. In: IEEE Workshop on Applications of Computer Vision. IEEE, USA (2009)
Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: Proc. of CVPR (2001)
Cauchie, J., Fiolet, V., Villers, D.: Optimization of an Hough transform algorithm for the search of a center. Pattern Recognition (2008)
Latif, M., Sanei, S., Chambers, J.: Localization of abnormal EEG sources incorporating constrained BSS. In: International Conference on Artificial Neural Networks (2005)
Larue, G.S., Andry, R., Anthony, P.: Driving performance impairments due to hypovigilance on monotonous roads. Accident Analysis and Prevention (2011)
Huang, N.E., Shen, Z., Long, S.R., Wu, M.L., Shih, H.H., Zheng, Q., Yen, N.C., Tung, C.C., Liu, H.H.: The empirical mode decomposition and Hilbert spectrum for nonlinear and non-stationary time series analysis. Procedures of Royal Society of London. London (1998)
Pfurtscheller, G., Neuper, C.: Motor imagery and direct brain-computer communication. Proceedings of the IEEE (2001)
Suykens, J.A.K., Van Gestel, T., De Brabanter, J., De Moor, B., Vandewalle, J.: Least Squares Support Vector Machines. World Scientific, Singapore (2002)
Boustane, T., Quellec, G., Chainais, P.: Implantation de la methode EMD en C avec interface Matlab. Project report ISIMA, France (2004)
Porwik, P., Lisowska, A.: The Haar Wavelet Transform in Digital Image Processing: Its Status and Achievements. Machine GRAPHICS and VISION. MGV, Poland (2004)
Kojima, N., Kozuka, K., Nakano, T., Yamamoto, S.: Detection of Consciousness Degradation and Concentration of a Driver for Friendly Information Service. In: Vehicle Electronics Conference Proceedings of the IEEE International. IEEE, Japan (2001)
Garcia, I., Bronte, S., Bergasa, L.M., Almazan, J., Yebes, J.: Vision-based drowsiness detector for real driving conditions. In: IEEE Intelligent Vehicles Symposium. IEEE, Spain (2012)
Devi, M.S., Choudhari, M.V., Bajaj, P.: Driver Drowsiness Detection Using Skin Color Algorithm and Circular Hough Transform. In: Fourth International Conference on Emerging Trends in Engineering and Technology. CETET, Mauritius (2011)
Akrout, B., Mahdi, W.: Drowsiness Detection Based on Video analysis Approach. In: The 8th International Conference on Computer Vision Theory and Applications. VISAPP, Bacelona, Spain (2013)
Akrout, B., Mahdi, W.: Vision based approach for driver drowsiness detection based on 3D head orientation. In: The 7th FTRA International Conference on Multimedia and Ubiquitous Engineering. MUE, Seoul, Korea (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
Akrout, B., Mahdi, W. (2013). A Blinking Measurement Method for Driver Drowsiness Detection. In: Burduk, R., Jackowski, K., Kurzynski, M., Wozniak, M., Zolnierek, A. (eds) Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013. Advances in Intelligent Systems and Computing, vol 226. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00969-8_64
Download citation
DOI: https://doi.org/10.1007/978-3-319-00969-8_64
Publisher Name: Springer, Heidelberg
Print ISBN: 978-3-319-00968-1
Online ISBN: 978-3-319-00969-8
eBook Packages: EngineeringEngineering (R0)