Development of Low-Cost Real-Time Driver Drowsiness Detection System using Eye Centre Tracking and Dynamic Thresholding

📅 2026-09-12
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🤖 AI Summary
为减少因驾驶员疲劳引起的交通事故,开发了一种基于眼中心跟踪和动态阈值处理的低成本实时驾驶员困倦检测系统。
📝 Abstract
One in every five vehicle accidents on the road today is caused simply due to driver fatigue. Fatigue or otherwise drowsiness, significantly reduces the concentration and vigilance of the driver thereby increasing the risk of inherent human error leading to injuries and fatalities. Hence, our primary motive being - to reduce road accidents using a non-intrusive image processing based alert system. In this regard, we have built a system that detects driver drowsiness by real time tracking and monitoring the pattern of the driver's eyes. The stand alone system consists of 3 interconnected components - a processor, a camera and an alarm. After initial facial detection, the eyes are located, extracted and continuously monitored to check whether they are open or closed on the basis of a pixel-by-pixel method. When the eyes are seen to be closed for a certain amount of time, drowsiness is said to be detected and an alarm is issued accordingly to alert the driver and hence, prevent a casualty.
Problem

Research questions and friction points this paper is trying to address.

driver drowsiness
road accidents
fatigue
Innovation

Methods, ideas, or system contributions that make the work stand out.

real-time tracking
eye centre tracking
dynamic thresholding
pixel-by-pixel method
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Fuzail Khan
Department of Electronics and Communication Engineering, National Institute of Technology Karnataka, Surathkal, India - 575025
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Sandeep Sharma
Department of Electronics and Communication Engineering, National Institute of Technology Karnataka, Surathkal, India - 575025
M
M. R. Arulalan
Department of Electronics and Communication Engineering, National Institute of Technology Karnataka, Surathkal, India - 575025