Real-Time Automatic License Plate Detection Using YOLO for Intelligent Transportation Systems

DOI

10.2991/978-94-6463-738-0_82How to use a DOI?

Keywords

Automatic License Plate Detection; YOLO Object Detection; Image Recognition

Abstract

Automatic License Plate Detection (ALPD) plays a crucial role in intelligent transportation systems, law enforcement, and security applications. This paper presents an efficient ALPD methodology utilizing the YOLO (You Only Look Once) deep learning model for real-time and high-accuracy detection of license plates. The methodology begins with data collection and preprocessing, where diverse vehicle images are gathered and enhanced for optimal recognition. YOLO is employed to detect license plates with high speed and precision, significantly outperforming traditional contour-based approaches. Post-processing techniques, including grayscale conversion, noise reduction, and image cropping, refine the detected plates before character segmentation is applied. Optical Character Recognition (OCR) using Long Short-Term Memory (LSTM) networks is then utilized to accurately extract alphanumeric characters from the segmented plates. To improve reliability, Non-Maximum Suppression (NMS) is implemented to eliminate redundant detections, ensuring the selection of the most precise bounding boxes. The suggested approach is appropriate for real-time applications as it strikes a compromise between accuracy and computational efficiency such as traffic monitoring, automated toll collection, and smart surveillance. Experimental results demonstrate that the YOLO-based approach provides superior performance in terms of processing speed and detecting accuracy, highlighting its potential for large-scale deployment in intelligent transportation systems.

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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TY  - CONF
AU  - Apurv Verma
AU  - Raj Rajbhar
AU  - Ravi Sahu
AU  - Rupal Sahu
PY  - 2025
DA  - 2025/06/22
TI  - Real-Time Automatic License Plate Detection Using YOLO for Intelligent Transportation Systems
BT  - Proceedings of the International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025)
PB  - Atlantis Press
SP  - 1069
EP  - 1078
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-738-0_82
DO  - 10.2991/978-94-6463-738-0_82
ID  - Verma2025
ER  -