Fatigue Detection System using Image Processing on Video Sequences

Abstract

In general, around 20 % of the road accidents are caused due to driver fatigue. A very effective and an intelligent system built into vehicles can minimize the accident death toll caused due to driver fatigue. In this paper, a fatigue detection system, based on image processing in a Real-Time environment, is introduced. The system is used in a running environment of a vehicle, wherein the driver in the vehicle onset is alerted of his drowsiness, thus reducing the rate of accidents. In this model, a camera is fitted in the car, which captures a real time video sequence at 15 fps. The face and the facial features are then detected. The parameters involve the eye state detection and yawning detection along with head rolls. This system is implemented in at morning day light and night time. This system gives high accuracy rate and low error detection with a quick processing of input data. Along with these features it is also cost efficient and easily implementable and installable in every type of vehicle, thus minimizing the number of accidents caused by driver's fatigue to a great extent.

Blinking Eyes Detection to Monitor Drowsy Drivers Due to Fatigue Using MATLAB Cascade Object Detector

“…Drowsy situations can trigger danger especially when performing tasks that require constant concentration, such as driving a vehicle over long distances. Consequences of being in a fatigue state while driving and experiencing a drowsy state, it is feared may result in accidents (Khan & Panchal, 2015). Therefore, a method to help detect drowsiness while driving is needed to prevent accidents.…”