Abstract
The drowsiness detection system is a non-evasive system which uses vision-based concepts. In this work, we present a method based on image processing technique for detecting driver drowsiness by considering eye blink rate and pressure sensor value from hand gloves. We applied the Haar Cascade Classifier and Viola–Jones algorithm to detect face and eyes. A camera is focused on the face of the subject from an adequate distance. The system first detects the driver’s face. Then it confirms the region of interest: eye. It then starts counting the blinking of the eye and hand grip pressure from the gloves. If the blinking rate is higher than the normal rate for a given period of time and the hand pressure value is lower than the threshold, the system confirms that the driver’s condition is drowsy. It then gives a warning signal to the driver. If the system cannot measure any blink for a fixed period of time and hand pressure value is extremely lower than the threshold, the proposed system confirms that the driver is sleepy. It then either slows down to the point of stopping the vehicle or gives a strong alarm to wake up the driver. Experimental evaluation is done with 5 mock-drivers of different age groups in a total of more than 4 h of recording time. Result shows that the system is performing as expected to detect driver drowsiness. Eye blinking rate together with hand grip pressure gives a better performing system making it an excellent candidate for future exploration in the field of automotive.
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Acknowledgements
Authors would like to thank the Department of Computer Science & Engineering of both Chittagong University of Engineering & Technology and Daffodil International University for their continuous support throughout the research. Bangladesh Auto Industries Ltd. provided all the test subjects (getting voluntary consents) for experimentation. The authors are grateful to them.
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Ashfakur Rahman Arju, M., Khan, N.H., Hoque, K.E., Jisan, A.R., Tareque, S.M., Hasan, M.Z. (2020). A Framework for Detecting Driver Drowsiness Based on Eye Blinking Rate and Hand Gripping Pressure. In: Uddin, M., Bansal, J. (eds) Proceedings of International Joint Conference on Computational Intelligence. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-13-7564-4_26
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