ARTIFICIAL VISION SYSTEM FOR AUTOMATIC NUMBER PLATE IDENTIFICATION (International Journal of Engineering and Computer Science, 2017)
During the recent years, Intelligent Transportation Systems (ITS) are having a wide impact in people’s life as their scope is to improve transportation safety and mobility and to enhance productivity through the use of advanced technologies.  License Plate Recognition (LPR) is an integral part of ITS. The popularity of License Plate Recognition System is mainly because of its Successful applications in Traffic congestion and monitoring, Revenue control related to road usage, Campus security Systems, Access Control Systems, etcIn this paper, a algorithm for vehicle license plate identification is proposed, on the basis of a image segmentation technique and connected component analysis in conjunction with character recognition Neural Network. The algorithm was tested gray level vehicle images of different backgrounds .The camera focused in the plate, while the angle of view and the distance from the vehicle varied according to the experimental setup. In the first  image enhancement is performed. Then it  is used for edge detection. After edge detection series  detect the license plate number. Character segmentation is done using line scanning technique.  In addition to the algorithms based on gray-level image processing, color information of license plates also plays an important role in license plates localization, where the unique color or color combination between the license plates and vehicle bodies are considered as the key feature to locate the license plates. The mechanism is able to deal with difficulties raised from illumination variance, noise distortion ,and complex and dirty backgrounds. Numerous captured images including various types of vehicles with different lighting and noise effects have been handled. A study of the different parameters of the training and recognition phases showed that the proposed system reaches promising results in most cases and can achieve high success rates location has been confirmed by the experiments.