Real-Time Vehicle Driver Drowsiness Prediction Using Image Processing

8 Mar
Posted on Author Neha Rai

Real-Time Vehicle Driver Drowsiness Prediction Using Image Processing

Authors -Dr.R.Sathya, Harini M, Megavathi S, Vishalini V

Abstract- – Drowsiness while driving is a significant cause of road accidents, leading to fatal consequences. This paper presents a real-time driver drowsiness detection system utilizing image processing and an improved Eye Aspect Ratio (I-EAR) technique. The system employs Haar cascade classifiers for facial and eye region detection, followed by an I-EAR calculation to determine the driver’s drowsiness state. If prolonged eye closure is detected, an alert is triggered to warn the driver. The proposed method enhances road safety by providing an efficient and non-intrusive way to monitor driver alertness. Experimental results validate the system’s effectiveness under different lighting conditions and facial variations. The paper also discusses the integration of the system into real-world applications and its adaptability to different driving environments.

DOI: /10.61463/ijset.vol.10.issue2.215