Real Time Indian License Plate Detection using Deep Neural Networks and Optical Character Recognition using LSTM Tesseract

Abstract

Among the ranking of the largest road network in the world, India stood at third position. According to a survey held in 2016 the total number of vehicles in India were 260 million. Therefore, there is a necessity to develop Expert Automatic Number Plate Recognition (ANPR) systems in India because of the tremendous rise in the number of automobiles flying on the roads. It would help in proper tracking of the vehicles,expert traffic examining, tracing stolen vehicles, supervising parking toll and imposing strict actions against red light breaching. Implementing an ANPR expert system in real life seems to be a challenging task because of the variety of number plate (NP) formats,designs, shapes, color, scales, angles and non-uniform lightning situations during image accession. So, we implemented an ANPR system which acts more robustly in different challenging scenarios then the previous proposed ANPR systems.The goal of this paper,is to design a robust technique forLicense Plate Detection(LPD) in the images using deep neural networks, Pre-process the detected license platesand performLicense Plate Recognition (LPR) usingLSTMTesseract OCR Engine. According to our experimentalresults, we have successfully achieved robust results withLPD accuracy of 99% and LPR accuracy of 95%just like commercial ANPR systemsi.e., Open-ALPRand Plate Recognizer.