Enhancing driver safety : Real-time eye detection for drowsiness prevention driver assistance systems †
Drowsiness has become a significant contributing factor to traffic accidents in modern times, posing a major concern to society. Driver fatigue or sleepiness leads to decreased reaction time, diminished attention, and compromised decision-making abilities, thereby affecting the overall driving exper...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Multidisciplinary Digital Publishing Institute (MDPI)
2023
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/42810/1/Enhancing%20driver%20safety_Real-time%20eye%20detection%20for%20drowsiness%20prevention%20driver.pdf http://umpir.ump.edu.my/id/eprint/42810/ https://doi.org/10.3390/engproc2023046039 https://doi.org/10.3390/engproc2023046039 |
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| Summary: | Drowsiness has become a significant contributing factor to traffic accidents in modern times, posing a major concern to society. Driver fatigue or sleepiness leads to decreased reaction time, diminished attention, and compromised decision-making abilities, thereby affecting the overall driving experience. This paper addresses this issue by proposing a drowsiness detection system based on image processing, utilizing a cascade of classifiers built on Haar-like features. The system effectively detects the eyes, allowing for determination of eye closure or opening, which serves as an indicator of driver drowsiness. |
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