A Driver Nodding Detection and Prevention System To Avoid Accidents

Driving with drowsiness is one of the major cause or a reason behind the road and traffic accidents. Driver fatigue is a significant factor in a large number of vehicle accidents. So there is a need to develop such a techniques which helps to prevents the growth rate of such accidental things.for development of technologies for detecting or preventing drowsiness at the wheel is a major challenge in the field of accident avoidance systems.Drowsy driver detection system is one of the potential applications of intelligent vehicle systems.Due to the hazard that drowsiness presents on the road, methods need to be developed for counteracting its affects.This paper aims to describes a real-time non-intrusive method for detecting drowsiness of driver by using yawning measurement.Our proposed system involves several steps including the real time detection and tracking of driver’s face, detection and tracking of the mouth contour and the detection of yawning based on measuring both the rate and the amount of changes in the mouth contour area. It uses webcam to acquire video images of the driver. Visual features like mouth & eyes which are typically characterizing the drowsiness of the driver are extracted with the help of image processing techniques to detect drowsiness. Here we are applying the bluring algorithm on images ,those are capture from webcam to remove the noise. Then converting the RGB image to HSV image.Where HSV converts the RGB image into black and white image and the blob detection will detect the blob from the images. Final test results demonstrate that the proposed system can efficiently measure the aforementioned parameters and detect the yawning state as a sign of driver’s drowsiness.