A Real-Time Intelligent Alarm System on Driver Fatique Based on Video Sequence

Abstract

The proposed work deals with development of an automatic system for drowsy driver detection using machine vision system. The system uses a small monochrome security camera that points directly toward the driver’s face and focuses the driver’s eyes. The video samples of drivers in drowsy and non-drowsy condition are obtained and stored in database. The video samples are converted to frames. Each frame is converted to binary images to track edges of eyes. An algorithm is developed to locate the eyes and its closure. After extracting the face area, the eyes are located by computing the average of pixels in horizontal area. Taking into account the knowledge that eye regions in the face present great intensity changes and the eyes are located by finding the significant intensity changes in the face. Once the eyes are located, measuring the distances between the intensity changes in the eye area determined whether the eyes are open or closed. The variation in intensity is plotted. Based on the distance between two valleys of the plot eyes, closure is detected. Once the closure is detected, fatigue is reported through a warning signal to the driver to it. The algorithm developed is unique to any currently published papers, which was a primary objective of our work. The performance of the work is reported for drowsy and non-drowsy driver’s samples in different environment.