AUTOMATIC LICENSE PLATE RECOGNITION USING YOLOV4 AND TESSERACT OCR

Abstract

In modern times the quantity of on road vehicles is expanding very quickly. Most of the time, it is important to verify the identity of these vehicles for authorization of the transit regulation, overseeing parking garages. it is hard to check this colossal number of moving vehicles physically. Subsequently, building up a precise automatic license plate recognition model (ALPR) including character recognition is important to ease the issues mentioned above. We have developed a model based on multiple types of license plates from different countries. The dataset of images was trained using Yolov4 which uses CNN architectures. Character recognition was done using the Tesseract OCR after multiple image pre-processing techniques and morphological transformations. The proposed program has obtained an accuracy of 92% in license plate detection and 81% in character recognition.