Automated Vehicle Number Plate Recognition System

ABSTRACT

Automatic number plate recognition (ANPR) is an image processing technology which uses number (license) plate to identify the vehicle. The increasing rate of broad day robbery and stealing of vehicles in our present day is alarming and challenging since apprehending and retrieving of stolen vehicles have been very difficult and tasking. It therefore become necessary to device possible means to identify vehicles for easy tracking and recovery. This project therefore is a design and implementation of an efficient automatic authorized vehicle identification system by using the vehicle number plate. The design employed Digital Image Processing (DIP) technique and Optical Character Recognition (OCR) on images to read and identify vehicle registration plates. The system is implemented using python programming language and written using Pycharm which is one of the python IDE, and its performance is tested on real image. The developed system first detects the vehicle and then captures the vehicle image, afterwards the vehicle number plate region is extracted using the image segmentation technique while Optical Character Recognition technique is used for the character recognition. The resulting data is then used to compare with the records on the law enforcement database so as to come up with the specific information like vehicle owner, place of registration, address as well as other vital information. The result shows that the developed system successfully detects and recognizes the vehicle number plate on real images. It is therefore recommended that the government should embrace electronic way of detecting and recognizing plate numbers which will help in eradicating or reducing the incident of robbery and other criminal cases.