Driver Drowsiness Detection Using Multi-feature Analysis

now a day’s Road accidents are common in developed as well as developing countries. These accidents happen due to different different reasons like sleeping disorders, working in night shift or more than eight hours as over time, side effects of medicine, alcohol, speeding, freakishness of teenager’s etc. One of the most important reasons is drowsiness. Drowsiness means sleepiness, which affects the performance of driving and leads to death of driver as well as passengers also. This is the reality because forty one percentage drivers have admitted that they fall asleep at some time and out of them twenty seven percentage drivers have admitted that sometimes they are really unable to open their eyes while driving. So, we are going to develop a system to detect the drowsiness on the basis of eye blinking to save the life of human being and also to decrease the rate of road-accidents all over the world because 2.5 percent fatal road accidents happen only due to drowsiness. The numbers of tools have been developed to detect drowsing drivers on the different – different features like drifting from lane, missing exit, hitting sign board or strip etc. We have developed a tool with the help of camera, HAAR features and blinking rate of eyes to increase the accuracy of detection of drowsiness of drivers at minimum cost to save the lives, which is very easy to implement in any type of light motor vehicle. Keywords— Drowsiness, HAAR, Eye Blinking, Face Detection, Eye Detection, Gray image, CREB, NREB etc.