Fatigue Detection Based On Eye State Judgement

The increase of car number has facilitated people’s daily life and work. The number of accidents caused by vehicle every year is very high. It has caused enormous losses for the country and endless sadness for many families. After research, it is found that a mass of accidents were caused by fatigue driving, which has become a hidden danger for traffic safety. So, fatigue driving detection is a hot topics in traffic safety field.This paper centres on eye state research. Detection is performed to find out the eye is whether open or closed, and the face is whether detected or not. According to detection result, we can estimate if the driver were fatigued. Finally, the detection function is transplanted to embedded system, which can be fixed on the car to detect fatigue driving. The algorithm is transformed to practical equipment.First, this paper introduces the theoretical basis and training process of Haar cascade classifier. Then, eye detection is performed in the face area detected by face classifier. After testing many eye detection algorithms, we select the LBP algorithm, which is good at eye location and eye state judgement. Using the LBP matrix of sample image to detect eye position, then, judging eye state according to detection result. The fast detection speed is fit for running in embedded system. After getting eye states, estimating the fatigue state according to the duration of some kind of eye state. If the detection result proves that the driver is tired, detection system will give an alarm. Experimental result shows that this algorithm is good at distinguishing frontal fatigue state, and adapt to illumination intensity changing. After testing in the condition with different illumination intensity, the average recognition rate of this algorithm exceed90percent. When the algorithm is transplanted to the embedded system with low running speed, the fastest average running speed is20frame every second. It can meet the basic needs of real-time detection. Because of these advantages, this detecction method has an extensive application prospect.