Abstract
Eye state tracking for driving is the key problem in fatigue detection, and it has been proved to be effective and popular method in fatigue driving. In this paper, we present a new algorithm framework for fatigue driving. We first recognize human eyes with AdaBoost algorithm, then an improved Otsu algorithm is modified to automatically adapt to varied environments. Furthermore, we propose an effective algorithm based on dynamic sliding window in order to compute proper threshold between open and close eye window. Finally, we estimate the different level of fatigue driving with improved percentage of eyelid closure time (PERCLOS) algorithm. Human eye images are captured with camera in real time, and our method is simulated on personal computer. The comparative experiments demonstrate that the proposed algorithm framework can effectively discriminate the level of fatigue state in driving.
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
References
Fan X, Sun Y, Yin B, Guo X (2010) Gabor based dynamic representation for human fatigue monitoring in facial image sequences. Pattern Recogn Lett 31:234–243
Thibos LN (1989) Image processing by the human eye. In: Advances in intelligent robotics systems conference, pp 1148–1153
Viola P, Jones M (2004) Robust real-time face detection. Int J Comput Vision 57:137–154
Xiong C, Xie M, Wang L (2012) Driver fatigue detection based on AdaBoost. In: Jin D, Jin S (eds) Advances in intelligent and soft computing, vol 159. Springer, Berlin, pp 13–17
Jin Y, Su G, Wei L (2008) Implementation of face detecting algorithm of AdaBoost based on DSP. Comput Eng Design 14:32–35
Zhang J, Wang D (2010) Building multi-view real-time video face detection system based on Adaboost algorithm. Comput Eng Design 18:36–40
Ostu N (1979) A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern 9(l):62–66
Lin T, Chen S (2008) Study on the method for driver’s eyes fatigue state detection based on haar-like feature. School of Electronic & Engineering, South China University of Technology, vol 25. doi: 10.3969/j.issn.1002-0268.2008.07.025
Al-Kubati AAM, Saif JAM, Taher MAA (2012) Evaluation of canny and otsu image segmentation. In: International conference on emerging trends in computer and electronics engineering (ICETCEE’2012), pp 24–25
Cleveland D (1999) Unobtrusive eyelid closure and visual point of regard measurement system. In: Proceedings of the ocular measures of driver alertness technical conference, Herndon, Virginia, USA
Dinges DF, Mallis MM, Maislin G, Powell JW (1998) Final report: evaluation of techniques for ocular measurement as an index of fatigue and as the basis for alertness management. National Highway Traffic Safety Administration. Report No DOT HS 808 762
Rimini-Doering M, Altmueller T, Ladstaetter U, Rossmeier M (2005) Effects of lane departure warning on drowsy drivers’ performance and state in a simulator. In: Proceedings of the third international driving symposium on human factors in driver assessment, training, and vehicle design, pp 88–95
Kurylyak Y, Lamonaca F, Mirabelli G (2012) Detection of the eye blinks for human’s fatigue monitoring. In: IEEE international symposium on medical measurements and applications proceedings (MeMeA), pp 1–4
Radlak K, Smolka B (2012) A novel approach to the eye movement analysis using a high speed camera. In: 2nd international conference on advances in computational tools for engineering applications (ACTEA), pp 145–150
Yuan W, Yuan Y (2010) Algorithm research of the eye open degree detection base on PERCLOS. Comput Eng Design 25:21–25
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chen, D., Wang, Z., Zhuo, Q., Wu, F. (2014). A New Algorithm for Fatigue Detection in Driving. In: Wen, Z., Li, T. (eds) Foundations of Intelligent Systems. Advances in Intelligent Systems and Computing, vol 277. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54924-3_98
Download citation
DOI: https://doi.org/10.1007/978-3-642-54924-3_98
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-54923-6
Online ISBN: 978-3-642-54924-3
eBook Packages: EngineeringEngineering (R0)