Driver Fatigue Detection System Based on DM3730

Driver fatigue is a popular problem which has attracted people’s views. Many research departments are researching driver fatigue detection in order to improve the traffic safety. This paper presented a driver fatigue detection system based on DM3730. The system calculated the inter-image difference between frames captured by near-infrared light irradiation, which included identification of the eyes by Otsu adaptive threshold segmentation method and prediction the orientation of the eye in nearby images by Kalman filter. Then the system determined the state of fatigue by improved PERCLOS (Percentage of Eyelid Closure over the Pupil)method. Experimental results show that the system has the advantages of small size and low power consumption. Meanwhile it meets the requirements of all-weather, real-time monitoring. The system can be extended to automobile and other production processes which the fatigue monitoring is required.