Drowsy Driver Detection using MSER Feature Detection and Binarization on MATLAB


Asma Jamesh
Biomedical Engineering Sri Ramakrishna Engineering College, Coimbatore


Every year, 1.5 lakh people die in road mishaps in India. Among these accidents, 40% are due to ‘Drowsy or Sleep Driving’. According to several statistics, almost all commercial private drivers tend to drive continuously for 10 hours a day. Nearly all road accidents caused due to lack of sleep and drowsiness are highly hazardous and fatal. Drowsy Driver Detection Algorithm acquires real-time video and captures snapshots using an external Webcam. Using the Viola-Jones Algorithm, the face and the eyes of the driver are detected. The original RGB eye image is converted to a Gray image and then into a Binary image. Two techniques, Maximally Stable Extremal Regions Feature Detection and Binarization are deployed to determine the status of the driver. This research paper focuses on the development of a MATLAB algorithm to alert the driver or the co-passenger on-time by plotting the MSER Features and thresholding the acquired real-time images.

September 22, 2021
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