Vehicle License Plate Recognition and Detection Using Neural Networks

Abstract

Vehicle License Plate Identification and Recognition (VLPIR) uses image processing and character recognition technology in order to identify the license plate number automatically. VLPIR system are used for the purpose of effective traffic control, security applications such as access control to restricted areas and tracking of car, tracing of stolen cars, identification of dangerous and reckless drivers on the road. The objective of this work is to develop an algorithm for Vehicle License Plate identification and Recognition (VLPIR) of Nigeria License Plates. Standard Nigeria plate numbers consists of different colors such as the background colour (white), background image (Nigerian Map in green colour) and the number colour (red or blue). The system are divided into three, vehicle license plate extraction, character segmentation and character recognition, since the rows that contain the number plates are expected to exhibit many sharp variations. Hence, edge detection technique is used to find the location of the plate, vertical and horizontal projection is exploited to perform the character segmentation to ease and improve recognition rate. Median filter is used to remove noise, enhancement of the image to increase readability of the plate number. Neural network is used to recognize the vehicle license plate character.