Driver Fatigue Recognition using Skin Color Modeling

Abstract

In Driver’s fatigue is a major safety concern in transportation system, because driver drowsiness and distraction have been casual factor for the large number of road accident. Fatigue reduces the driver’s perception level and decision making ability, which responsible for serious road accident. Around 22%-24% of car crash occurred by driver drowsiness. There is a way to reduce these accidents by monitoring drives fatigue and driving behaviors at the driving time by alerting the drivers, while the drivers are drowse. Face detection, eyes state measurement, lip detection, yawing detection, head tilting detection are the major visual facial symptoms for the driver fatigue detection. In this paper a modern assistive frame work has been introduced, which detected driver drowsiness based on visual features measurement. The goal of this paper has been monitored the driver driving behaviors, to detect the visual facial symptoms for safe driving in the road. Facial features symptoms have been monitored by two cameras. To detect driver distraction, the proposed algorithm has been experimented the facial fatigue expression, head tilting and lane departure. Experimental result of the proposed method has been compared with the existing methods. The experimental results show that, the proposed algorithm has good accuracy and reliable performance to reduce the road accident than the existing methods. The average accuracy of the proposed method is 92.44%.