Research Of Driver Fatigue Alarm Algorithm Based On Visual Information

Driver's fatigue is one of the main causes of traffic accidents. In order to take the initiative to eliminate the factors that lead to traffic accidents and to minimize loss of life and economic, the most thorough way is to use pre-prevention and technical means to monitor and limit improper driving behavior such as the fatigue of driver.This paper describes the research background and the significance of driver fatigue detection. We also compare and analyze the development and research status of driver fatigue detection, A non-invasive approach for monitoring driver's state based on visual information is a better and relatively easy to implement choice. The eye state is the most direct and effective response to the physical characteristics between features used to monitor driver's state using visual methods. The works of face detection, eye detection, eye feature extraction and eye status judgement in this paper are as follows:We start from face detection based on AdaBoost,and added by optimize module to improve the detection rate. For getting standard face image, we use eye location to normalize face image. First,the paper analyzes the training and detection process deeply. As the false positive rate is so high after AdaBoost detection, a skin detection module based on the YCrCb color space is analyzed and added to improve the performance of the system. Then, a variable step size based on template matching eye location algorithm to determine the location of one eye, the algorithm could work on rotated images and get higher detection rate. What is more , it combined with the circle-feature method, can deal with moderate illumination and expression changes. Experiments on lots of Face images have shown that our algorithm is reliable and fast.