24 Int. J. Vehicle Safety, Vol. 10, No. 1, 2018 Copyright © 2018 Inderscience Enterprises Ltd. Robust real-time driver drowsiness detection based on image processing and feature extraction methods Maryam Keyvanara*, Nasrin Salehi and Amirhassan Monadjemi Department of Artificial Intelligence, Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran Email: maryam.k1ara@gmail.com Email: saalehi.n69@gmail.com Email: monadjemi@eng.ui.ac.ir *Corresponding author Abstract: Recently, the human lifestyle has strongly been affected by the novel technological equipment. The applications of Artificial Intelligence are widely being utilised to improve the performance and quality of the modern life. One of the important applications of these techniques is to seek to improve public safety, including the safety of driving. The statistics indicate that the mortality of car accidents yearly constitutes a significant proportion of the overall deaths. A number of strategies have been studied to materialise driver drowsiness detection systems. One of the best strategies relies on image processing and computer vision methods. In this paper, a novel real-time method for driver drowsiness detection is presented. This method uses Haar wavelet-based features for face detection. The eye state determination has been performed using PCA feature extraction along with an SVM classifier. The proposed method has been implemented and tested on a real-time ARM based embedded system, with a camera installed in front of the driver. Results show that the presented intelligent system has a high detection accuracy, compared to the methods presented thus far, on the standard datasets such as BioID and RS-DMV. Keywords: driver drowsiness detection; Haar cascade classifier; SVM; face and eye detection; real-time tracking; PCA. Reference to this paper should be made as follows: Keyvanara, M., Salehi, N. and Monadjemi, A. (2018) ‘Robust real-time driver drowsiness detection based on image processing and feature extraction methods’, Int. J. Vehicle Safety, Vol. 10, No. 1, pp.24–39. 1 Introduction In the recent years, special attention has been paid to vehicle safety and many kinds of research have been conducted on it. Accidents caused by drowsy drivers and sleepy driving are one of the most popular reasons for driving incidents. Intelligent systems and driver monitoring are two main factors that are considered highly in safe driving. These