Studies Of Face Detection And Recognition For Driver Fatigue Monitor System

Driver's fatigue factors have been one of the most important causes of traffic accident. Because Safety Driving Assist technology has been the key technology, it has been paid more and more attention to. Driver fatigue monitor is a focus of it. Machine vision has better advantage than other methods on time, accuracy, and adaptability. It makes the scope of Driver fatigue monitor technology wider.The research content of this thesis embraces: the location and tracing of driver's face, the location of driver's lip and eye, the extracting character vector of driver's lip and eye, and the recognition of the driver' fatigue state.The skin color has the good assembling character in the color room. This thesis selects YC_bC_r color room as distributed and statistical mapping room, and builds a two-dimensional Gause distributed mathematical model through statistics and recognition. It adopts face detecting method based on similarity and the shape of face. Kalman filter is used to track Driver's face.Using the detecting border method and the searching red color element point method to cut and extract driver's lip. It can dislodge interference aroud the lip, and pick up the shape of lip completely. Then it uses the approaching method to locate every character point of the lip.In the research of the driver fatigue monitor system, this paper selects the right eye as the object. According to the arrangement of the part of face, it calculates the range of the right eye based on the place of mouth corner and the length of mouth. Because eyelid and eyebal are black, the thesis uses the project of black color element point to locate the domain of the right eye, and the approaching method to locate every character point of the right eye.This paper puts forward a neural network group method, and recognizes driver's fatigue states by BP neural network group. Experiment results show the BP neural network has fast and steady convergence, and its recognition is accurate and available.This thesis adopts VC++ 6.0 to develop the algorithm of the location and recognization of the driver's face in the driver fatigue monitor system, and makes the related test and computer simulation to show the correctness of this study.