Efficient Drowsiness detection system for drivers using image processing techniques

Drowsiness detection system is considered as a safety system used to detect the drowsiness status of a person and generate output accordingly to make him/her alert. Generally, this type of system is being used in vehicle to check the drowsiness status of the drivers. It is commonly seen that driver feels drowsy during driving for a long time which may result in dangerous consequences. Drowsiness detection system helps to make the driver alert so that those unexpected consequences can be avoided. This system is getting more popularity and being implemented widely in vehicle for safety purpose. Different technologies make this system more efficient so that the performance is getting improved day by day. In this work, a drowsiness detection system has been thoroughly discussed which is designed for the safety purpose of the drivers and has been built with image processing techniques where image detection algorithm and classifier have been used to detect faces as well as generate the predicted outcome. There are good numbers of conventional systems which have been built for the same purposes but their flexibility, accuracy, robustness and overall performances are questionable. Following a thorough review of the literature and a comparison with the traditional suggested method, the best model was chosen, ensuring a high degree of output generation accuracy.