The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2023.0140402
PDF

An Automatic Framework for Number Plate Detection using OCR and Deep Learning Approach

Author 1: Yash Shambharkar
Author 2: Shailaja Salagrama
Author 3: Kanhaiya Sharma
Author 4: Om Mishra
Author 5: Deepak Parashar

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 4, 2023.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: The use of automatic number plate detection devices in safety, commercial, and security has increased over the past few years. Number plate detection using computer vision is used to provide fast and accurate detection and recognition. Lately, many computerized approaches have been developed for the identification of vehicle registration details based on license plate numbers using either Deep Learning (DL) methodologies. In the proposed framework, we used Optical Character Recognition (OCR) and a deep learning-based new approach for automatic number plate detection and recognition. A deep learning approach trains the model to recognize the vehicle. The vehicle registration plate area is cropped adequately from the image, and a Convolution Neural Network (CNN) uses OCR to identify numbers and letters. The Jetson TX2 NVIDIA target served as the model's training data source, and its performance has been tested on a public dataset from Kaggle database. We obtained the highest accuracy of 96.23%. The proposed system could recognize vehicle license plate numbers on real-world images. The system can be implemented at security checkpoint entrances in highly restricted areas such as military areas or areas surrounding high-level government agencies.

Keywords: Number plat detection; recognition; deep learning; OCR; image classification

Yash Shambharkar, Shailaja Salagrama, Kanhaiya Sharma, Om Mishra and Deepak Parashar, “An Automatic Framework for Number Plate Detection using OCR and Deep Learning Approach” International Journal of Advanced Computer Science and Applications(IJACSA), 14(4), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140402

@article{Shambharkar2023,
title = {An Automatic Framework for Number Plate Detection using OCR and Deep Learning Approach},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140402},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140402},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {4},
author = {Yash Shambharkar and Shailaja Salagrama and Kanhaiya Sharma and Om Mishra and Deepak Parashar}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org