License Plate reader with PUC Details using Image Processing and Deep Learning

Abstract

As each vehicle is uniquely acknowledged by its license plate, the Transport System places a high priority on finding and recognizing of license plates. The news is constantly reporting on accidents and missing cars. Authorities must acknowledge all of these unlawful acts. As a result, research into the identification and recognition of vehicle number plates is ongoing. However, identifying a vehicle’s number plate has always been difficult for a number of reasons, such as brightness changes, shadows cast by moving vehicles, erratic license plate character types, different plate styles, and color effects caused by the surroundings. In this system, Number plate of vehicle is detected from a live video or an image. There is image preprocessing and segmentation done on the live video or number plate image. Deep learning model methods are used, the characters from it are separated and then each character gets recognized. This helps to collect the vehicle overall project then the capabilities of different techniques into one integrated automatic system are summarized. This kind of systems can be implemented on the roadside and makes a real time comparison between passing car and list of stolen cars. This detected license plate number could also be used in car parking systems. PUC which stands for Pollution Under Control, where emission levels of vehicles and the regular renovation of the PUC certificate is done or not is verified and the details are shown. This will help in keeping an overall check on vehicles and the task which most of the places do manually to check the PUC certificate for checking status, can be verified quickly and the fine can be implemented as per so.