Research On The Fatigue Driving Detection Technology Based On Eye-state Recognition

With the improvement of people’s living standard and the speeding up of people’s life rhythm, traffic accidents due to fatigue driving also increased year by year. When driver is in the state of fatigue, his control ability to the operation of the vehicle and the perceptual ability on the surrounding environment will fall. So it’s very easy to cause traffic accidents. Fatigue driving has become one of the most important hidden troubles of the traffic safety today. Therefore developing a set of practical, high detection accuracy of fatigue driving warning system has important practical significance.In this paper, we designed a set of improved solution of the fatigue driving testing system according to the technical feature and the application requirements of the fatigue driving early-warning system. The design mainly includes the following process: Step one, get video images of the upper part of driver’s body using cameras. Step two, do the initial image processing for the detection images, including illumination compensation, background subtraction, and so on. Then locate the driver’ eyes accurately using the Adaboost algorithm. Step three, track eye picture and predict the location of it using Mean Shift algorithm combined with Kalman filter. Step four, Extract the human eye contour using ellipse fitting method and locate the eye iris using Hough transformation, and use the detection result to judge the state of the driver’s eyes and it’s gazing direction. Step five, Identify the fatigue state using the PERCLOS and the gazing direction.Based on the algorithm process above, we have designed a set of early warning simulation system for fatigue driving based on PC environment. According to the experimental results, this fatigue driving warning simulation system can detect the eyes’ closing condition and gazing distribution, it can judge if the driver is in the state of fatigue driving or not accurately.