Number Plate Recognition System Using Convolutional Neural Network

Every Country is facing a problem of vehicle owner and traffic control management. It is a big challenge to identify those persons who violates the traffic rules and drive vehicles fastly. It is not possible for traffic person to control such vehicles movement to identify the vehicle number due to vehicles are moving at a speed. To identify such vehicles which are not having the latest number plates and owner may be punished with some penalty. A policy which has been launched by the traffic control department all the vehicles must be equipped by the number plates associated with the chips. So that there is a need to develop a monitoring system which recognizes a number plates of the vehicles automatically. It is the best possible solution for such number plates identification. Lots of systems available for number plate recognition. Such available systems follow various methodology but still it is complex task due to parameters such as high speed, nonuniformity of the number plate, language and different lighting conditions can affect a recognition system. Majority of the systems suffers such limitations. In this paper we have discussed various approaches of the number plate system image size, success rate, and processing time as measure. We have suggested the future scope and extension of this research of the number plate system also.