Design And Implementation Of Driver Fatigue Detection System Based On Multi-features

The increase in car brought great convenience to people’s travel, also broughtrevolutionary change to people’s life and work, however, road traffic injuries are a deadlydisaster. Driver fatigue as one of the main reasons for road traffic injuries, detection andprevention technology has not been a big breakthrough. Fatigue driving has become one ofthe most important threats to traffic safety.Departure from the computer image processing technology, combined withknowledge of computer applications, mathematics, computer vision, artificial intelligenceand other disciplines, this paper propose a driver fatigue detection model combined withmulti-features. Through quantitative calculation of fatigue get fatigue state. Meanwhile, inorder to better adapt to different individuals, this paper proposes a feedback model,allowing the system to establish a learning mechanism.According to the theoretical analysis of the model, which involves multiple featuresextracted were discussed in detail, including the location, zoning, and feature extraction.And a collection of video data validation, experimental results show that can extract thecorresponding features, indicating that the science and effectiveness of the detectionalgorithm. This paper presents the fatigue associated degree concept, fatigue quantitativecalculation method to integrate multiple features。The veto model reduce the falsedetection rate. From many different perspectives, so fatigue detection more comprehe nsiveand objective.Finally, the experimental data proved the mentioned driver fatigue detection modelbased on multi-features is scientific and effective. System has very high accuracy rate forfatigue detection, can play a role in early warning.