ALPR System Using Sequence Modelling: A real time system for vehicle authentication

Automatic vehicle record-keeping systems have varied applications such as security for car parking facilities, tracking vehicle location and monitoring vehicular traffic. In this paper, we propose a system for vehicle authentication, book-keeping and tracking. The proposed system implements Automatic License Plate Recognition (ALPR) with Convolution Neural Network (CNN) followed by a Gated Recurrent Unit (GRU), which recognizes vehicles and automatically authenticates them with the records on a database to provide information about the vehicle. On the request of the vehicle owner, the system can send vehicle location data through SMS (Short Message Service) notification to the vehicle owner by using a GSM module. Tradition ALPR Systems employ Image Segmentation followed by individual character classification. In this work, we have used a sequence modeling technique that does not require image segmentation. It achieved a character recognition accuracy of 98% and a complete license plate character recognition accuracy of 88%, when trained on a modest data set consisting of 400 images of different fonts.