Detecting Multiple Indian Licence plates from Real  time Videos using YOLOv4 and CNN

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Abhishek Wakchaure; Dr. Rajashree Shettar

Detecting Multiple Indian Licence plates from Real time Videos using YOLOv4 and CNN

Authors: Abhishek Wakchaure, Dr. Rajashree Shettar

Unique Paper ID: 152251
Volume: 8
Issue: 2
PageNo: 688-694

Keywords: Automatic Licence Plate Recognition complex environments Real time Optical Character Recognition YOLOv4 CNN UFPR-ALPR.

Abstract:
An Automatic Licence Plate Recognition (ALPR) system is able to read the characters on the number plate without human interference. It has been an area of continuous research due to a variety of practical applications but they are still dependent on many constraints. Indian licence plates are even tougher because of the density of cars on the roads. In this paper, we present a deep learning based approach which treats ALPR as two separate problems, an object detection using YOLO v4 and a character recognition problem using a Convolutional Neural Network model (CNN). The YOLO v4 model is custom trained to detect multiple licence plates in complex environments in real time and the CNN model is fine tuned so it is robust enough to recognize characters even in improper lighting conditions or low clarity. The approach yielded impressive results on two separate datasets, an UFPR-ALPR dataset which contains 150 videos and 4500 frames and an Indian Licence plate dataset with 640 images with different colour and lighting conditions.

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Cite This Article

ISSN: 2349-6002
Volume: 8
Issue: 2
PageNo: 688-694

Detecting Multiple Indian Licence plates from Real time Videos using YOLOv4 and CNN

Available:https://ijirt.org/article?manuscript=152251

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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