Study And Implementation Of Driver Drowsiness Detection System Based On Face Recognition

Driver fatigue is one of the important causes of serious accidents. It results in a lot of people's deaths or injuries and directly or indirectly tremendous economic loss. In other words, safety Driving Assist technology has been arouse more and more attention. And it is very important for us to study the technique of fatigue detection to reduce the traffic accidents. Therefore, many countries make great efforts on how to detect drowsiness during driving.Based on the detection of driver's eye states, this paper tries to set up a driver drowsiness detection system that can issue prompt warnings when necessary. This paper mainly covers the following works:The mechanism, possible reasons of drive fatigue, and most people's fatigue expression are analyzed firstly. The arithmetic of driver's face detection and eye locating is studied and improved. The method of face detection, eye location, eye states recognition and some techniques of digital image treatment are studied. Based on the current algorithms, the algorithm adapted to the system is presented.The skin color has the good assembling character in the color room. This thesis selects YCbCr color room as distributed and statistical mapping room, and builds a two-dimensional Gause distributed mathematical model through statistics and recognition. This face detecting model based on similarity and the integral projection of face image. It can cover the other useless image It can accelerate the speed of the detection and make the face location more precision.A new method using the geometrical characteristics of human face and the center of gravity of image is presented for the eye location. The experiments have proved that it is a very effective method and it is also applicable for the eye-closed images.A method using the gray-level projection and Hough transform is presented for the eye states detection. The algorithm of face location, eye location and eye states recognition are integrated in order to determine drowsiness. Several pictures are treated in the simulation system.