The accidents due to driver fatigue has increased the ratio of accidents year by year. Since the advent of technology, it
becomes important to develop a driver drowsiness detection system to alert the drivers irrespective of given condition. This
detection begins by exploring various physiological features of the drivers such as yawning behaviors. These noticeable features
are obtained from the frames that are captured by the camera. We label the frames as automatic datasets and then look for
major signs in detection such as frequent yawning patterns, frequent eye blinks etc. We measure the datasets against the
threshold; if the measured value surpasses the optimum value then driver is alerted via an alarm. This system provides a good
accuracy ratio over most of the detections.
