Proceedings of the International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025)

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Moving Vehicle Registration Plate Detection

Authors
Poonam Gupta1, *, Sanjeev Mishra2, Raghav Parate3, Adwait Bhakre4
1Assistant Professor, Department of Computer & Engineering, SSIPMT College, Raipur, India
2B. Tech. Student, Department of Computer Science & Engineering, SSIPMT College, Raipur, India
3B. Tech. Student, Department of Computer Science & Engineering, SSIPMT College, Raipur, India
4B. Tech. Student, Department of Computer Science & Engineering, SSIPMT College, Raipur, India
*Corresponding author. Email: poonam.gupta@ssipmt.com
Corresponding Author
Poonam Gupta
Available Online 22 June 2025.
DOI
10.2991/978-94-6463-738-0_79How to use a DOI?
Keywords
License Plate Recognition (LPR); Real-time Object Detection; Convolutional Neural Networks (CNNs); Optical Character Recognition (OCR); Video Frame Processing; Traffic Management Systems; Intelligent Transportation Systems (ITS); Motion Blur Compensation
Abstract

The detection of vehicle registration plates is a critical component in applications such as traffic monitoring, law enforcement, and automated toll collection systems. This project focuses on the development of a robust and efficient system for detecting and extracting vehicle registration plates from moving vehicles in real-time. The proposed system utilizes image processing techniques and machine learning algorithms to identify and localize license plates from video frames or images captured by cameras. Key steps in the process include image acquisition, preprocessing to handle varying lighting and motion conditions, edge detection, and region selection to isolate the plate. Optical Character Recognition (OCR) is employed to extract alphanumeric information from the detected plate for further processing. The system is designed to handle challenges such as motion blur, different plate sizes, angles, and environmental conditions. The project aims to achieve high accuracy and processing speed to facilitate seamless integration into real-world applications, ensuring scalability and reliability.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025)
Series
Advances in Intelligent Systems Research
Publication Date
22 June 2025
ISBN
978-94-6463-738-0
ISSN
1951-6851
DOI
10.2991/978-94-6463-738-0_79How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Poonam Gupta
AU  - Sanjeev Mishra
AU  - Raghav Parate
AU  - Adwait Bhakre
PY  - 2025
DA  - 2025/06/22
TI  - Moving Vehicle Registration Plate Detection
BT  - Proceedings of the International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025)
PB  - Atlantis Press
SP  - 1023
EP  - 1043
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-738-0_79
DO  - 10.2991/978-94-6463-738-0_79
ID  - Gupta2025
ER  -