Abstract: In this paper, a development of Nigeria Vehicle License Plate Recognition (NVLPR) system using artificial neural network is done. Vehicle License Plate Recognition (VLPR) is a special form of optical character recognition (OCR) which enables computer systems to read automatically the registration number of vehicles from digital pictures for the purpose of traffic control, security, access control to restricted areas, tracking of cars, tracing of stolen cars, identification of dangerous and reckless drivers on the road. This system is divided into three major parts: vehicle license plate detection, vehicle license plate character segmentation and License Plate character recognition. In vehicle license plate detection there are many challenges such as, complex plate background, illumination in consistencies, vehicle motion, distance changes for which edge detection analysis was explored. In this work, 200 vehicle license plates were captured, some with clear characters, others with blur and dirty stains. The character feature extraction and plate recognition accuracies were determined. Results showed that plates without blur and stain were most accurately extracted and recognized while satisfactory results were also obtained for the others.
Keywords: Software, License plate detection and recognition, Optical Character Recognition (OCR), Nigerian vehicle license plate, artificial neural network.