A Study of Fatigue Driving Detection System Based on AdaBoost Algorithm

In this paper, a fatigue driving detection system is designed. Firstly, the real-time collected facial images of vehicle drivers are pre-processed, and the AdaBoost algorithm classifier is used to locate the faces and eyes. Then the edge detection and contour extraction are performed on the obtained eye images to get the degree of eye opening and closing. Next, the proportion of the eye-closing time to the total observation time is calculated in combination with the perclos fatigue driving standard to determine whether fatigue is achieved. When fatigue is achieved, the system will give an early warning to wake up the driver who is sleepy. The simulation results show that this method has strong real-time performance, high detection accuracy and strong practicability.