Drowsy driver detection using Viola-Jones Algorithm / Wan Nurul Adlina Wan Sallehuddin ... [et al.]

• Main Authors: Wan Sallehuddin, Wan Nurul Adlina (Author), Mohamed Hatim, Shahirah (Author), Zulkifli, Zalikha (Author), Mohamad Ali, Razizul (Author)
• Format: Book
• Published: Universiti Teknologi MARA, Perak, 2021-11.
• Subjects: Article; PeerReviewed
• Online Access: Link Metadata
• Notes: https://ir.uitm.edu.my/id/eprint/61549/1/61549.pdf; Drowsy driver detection using Viola-Jones Algorithm / Wan Nurul Adlina Wan Sallehuddin ... [et al.]. (2021) Mathematical Sciences and Informatics Journal (MIJ) <https://ir.uitm.edu.my/view/publication/Mathematical_Sciences_and_Informatics_Journal_=28MIJ=29/>, 2 (2). pp. 51-56. ISSN 2735-0703
• Keywords: QA Mathematics; Analysis; Analytical methods used in the solution of physical problems

Drowsy driving is one of the factors that lead to road accidents which can cause dead. This is because driver does not able to give fully attention while driving. There are many factors that lead to driver drowsiness such as driving for a long time, do not have enough sleep and shift work. Thus, this research is proposed to develop a system to detect and alert drowsy driver by using Viola-Jones algorithm. Blinking rate is used as the indicator to determine either the driver is in drowsy or awake state. Viola-Jones algorithm is used to detect driver's face and eyes in real time. Haar cascade classifier for frontal face and glasses eyes are used to train the system to detect driver's face and eyes. In order to calculate eye blink, Eye Aspect Ratio (EAR) calculation is used to calculate and estimate of the eye-opening state in this system. The results of testing showed that the system with the Viola-Jones algorithm and Haar cascade classifier able to detect eyes blinking rate at the high accuracy percentages.