Research advanced in deep learning-based licence plate recognition and localization

Jingrui Li

doi:10.54254/2755-2721/20/20231065

Research Article

Open access

Published on 23 October 2023

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Li,J. (2023). Research advanced in deep learning-based licence plate recognition and localization. Applied and Computational Engineering,20,26-32.

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Research advanced in deep learning-based licence plate recognition and localization

Jingrui Li *^,1,

¹ Dalian Neusoft University of Information

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/20/20231065

Abstract

The purpose of licence plate recognition is to analyze pictures or videos of moving vehicles to read the plate and identify the vehicle's owner. Traffic data management and smart transportation systems rely heavily on licence plate reading technology. Initial picture capture, image preprocessing, licence plate analysis, character segmentation, and recognition are the building blocks of licence plate recognition. The present analysis centres on the examination of the above key steps. In this paper, we introduce the latest research progress in the implementation of licence plate recognition utilizing deep learning techniques, including the classic framework of licence plate location and character recognition, representative methods, and their advantages and disadvantages. We also perform a quantitative comparison of existing representative methods. Finally, we summarize the challenges in the research domain of licence plate recognition and discuss the future development direction from the aspects of neural network interpretability, more general small sample learning methods, and incremental learning.

Keywords

license plate recognition, image recognition, deep learning

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Cite this article

Li,J. (2023). Research advanced in deep learning-based licence plate recognition and localization. Applied and Computational Engineering,20,26-32.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 5th International Conference on Computing and Data Science

Conference website: https://2023.confcds.org/

ISBN：978-1-83558-031-8(Print) / 978-1-83558-032-5(Online)

Conference date: 14 July 2023

Editor：Roman Bauer, Marwan Omar, Alan Wang

Series: Applied and Computational Engineering

Volume number: Vol.20

ISSN：2755-2721(Print) / 2755-273X(Online)

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