Fatigue Detection System By Using Image Processing

In recent times, road accidents have become a major concern for road safety, significantly contributing to an insecure environment. Proper precautions while driving are essential to prevent accidents. Many accidents occur due to the negligence and inattention of drivers. One of the key factors in such accidents is driver fatigue, which, if detected in time, could potentially save many lives. This research aims to design a system that can identify driver fatigue using image processing techniques. A face localization algorithm is proposed for detecting the face, and an eye localization algorithm is used to identify the eyes in the captured image. The system uses a fatigue detection algorithm based on the PERCLOS (Percentage of Eye Closure) method, which measures the likelihood of eyelid closure over the pupil and reflects slow eyelid movements, indicating drowsiness. The main approaches for detecting fatigue in drivers rely on monitoring physiological signals, vehicle status, and facial expressions. These methods primarily use image processing technologies to extract fatigue-related data from drivers, helping to predict potential risks associated with drowsy driving