Advancements in globalization have significantly seen a rise road travel. This has also led to increased car accidents and fatalities, which become global cause of concern. Driver's behavior, including drowsiness, contributes many the deaths. The main objective this study is develop system diminish mishaps caused by driver's drowsiness. Recently deep convolutional neural networks been used mult...

Nowadays, the use of public transportation is reducing and people prefer to private transport because its low cost, comfortable ride, personal preferences. However, causes numerous real-world road accidents due conditions drivers’ state such as drowsiness, stress, tiredness, age during driving. In cases, driver fatigue detection mandatory avoid ensure a journey. To date, several complex systems...

Advanced Driver Assistance Systems are used to increase the security of vehicles. Computer Vision is one of the main technologies used for this aim. Lane marks recognition, pedestrian detection, driver drowsiness or road sign detection and recognition are examples of these systems. The last one is the goal of this paper. A system that can detect and recognize road signs based on color and shape...

this paper presents an automatic drowsy driver monitoring and accident prevention system that is based on monitoring the changes in the eye blink duration. Our proposed method detects the drowsiness in eyes using the proposed mean sift algorithm. Our new method detects eye blinks via a standard webcam in real-time YUY2_640x480 resolution. Experimental results in the eyeblink database showed tha...