Real-time Detection Algorithm Based On The Ocular Characteristics Of Fatigue Driving

Today, the car in the world has become one of the most common means of transport. According to a German automotive market researching institution predicted that Global vehicles (including personal cars and commercial vehicles) holdings in 2010 will surpass 1 billion. This situation has brought great pressures and challenges to the world's traffic safety directly. Fatigue driving has become one of the main incentives of the world's traffic accidents.In the current driver fatigue detection field, as technology advances, computer vision, image processing and pattern recognition technology has been further developed and improved. The research based on driver facial features, non-contact fatigue detection algorithm and development of fatigue warning systems have become one of the mainstream.In view of this background, this paper developed a detection algorithm based on driver's face and eye state, with the video image processing technology in natural light. Referring to PERCLOS criteria of fatigue testing, it developed a accurate fatigue detection method, and achieved the driver fatigue detection and early warning.This paper included the following contents:(1)For the driver's face detection, it developed a driver's face detection and localization algorithm which has good robustness and fast calculation. The algorithm syncretized the skin color information based on YCbCr & HSV color space and Adaboost classifier.(2)In the basis of human face detection and location, it achieved pupil of human eyes orientation and the state of eyes identified, using the area of human eye template matching algorithm and the Hough transform circle detection algorithm. The method based on the from coarse to fine multi-level filtering idea. It had laid a theoretical basis for follow-up to determine the fatigue.(3)In the determination of the conditions of the state of the human eyes, through careful analysis of fatigue on driving, referring to PERCLOS criteria it designed a fatigue detection method based on the idea of threshold-segmentation.(4)It implemented the entire algorithm with C language source code. Using OpenCV development platform, it completed the effect of the whole detection algorithm validation.Through laboratory simulations, it showed that based on feature of the eyes driving fatigue real-time detection algorithm has better accuracy and robustness. It laid the foundation for more in-depth researching of algorithm and hardware implementation.