Abstract: Driver drowsiness is a major cause of road accidents worldwide, leading to significant loss of lives and property. To address this critical issue, the development of an effective and reliable system for detecting driver drowsiness has become essential. This abstract presents the need for employing image processing techniques in detecting driver drowsiness, highlighting its potential to enhance road safety. The proposed solution leverages computer vision and image processing algorithms to analyze real-time images or video frames captured from a camera placed inside the vehicle. By monitoring the driver's facial features and eye movements, the system can accurately determine the level of drowsiness and issue appropriate warnings or alerts when necessary. In conclusion, employing image processing techniques for detecting driver drowsiness is a crucial step towards improving road safety. By leveraging computer vision and machine learning, this approach has the potential to save numerous lives, prevent accidents, and create a safer driving environment for everyone. Future research and development efforts should focus on refining and deploying such systems widely to enhance overall road safety.
Keywords: Image processing ,Driver drowsiness detection ,Fatigue detection ,Eye tracking ,Driver safety.
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DOI:
10.17148/IJARCCE.2023.125214
