疲劳驾驶预警系统对保障驾驶员的安全驾驶具有十分重要的作用。以驾驶员人眼图像信息处理为基础，建立了离散单位时间内非正常状态时间所占百分比疲劳判断模型，实现了对驾驶员疲劳状态的监控与预警。通过近红外光源对人眼主动照明，采用互补金属氧化物半导体摄像头实现对人眼图像信息的采集，基于Adaboost 算法实现人眼准确定位，利用Harris 强角点检测人眼中心区域，得到眼睛的视线状态信息，根据疲劳判断模型，设计可调的预警阈值，实现驾驶员疲劳状态的分级预警。实验结果表明：在一定条件下，系统判断响应时间为1.5 s，虚警率为4%，具有抗干扰性强和实时性好等特点。

The fatigue warning system is very important to guarantee driver′s safe driving. The discrete fatigue estimate model of percentage of eyelid closure over the pupil time bases on image process of eyes is established, and the driver fatigue status monitoring and warning are realized. Eye images acquisition is realized by complementary metal-oxide-semiconductor camera with near-infrared lamps shine. Adaboost algorithm is applied to locate the eyes, and Harris corner detection is used to obtain the information about sight of eyes. Grade warning level is designed by the adjustable warning threshold based on the fatigue estimate model. The experimental results show that the system can provide under 1.5 s reaction time, 4% false alarm rate, and possess good real-time and anti-jamming characteristic under certain conditions.