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Vol. 34, No. 8(3), S&M3042

Notice of retraction
Vol. 32, No. 8(2), S&M2292

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Sensors and Materials
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Sensors and Materials, Volume 35, Number 6(3) (2023)
Copyright(C) MYU K.K.
pp. 2129-2137
S&M3311 Research Paper of Special Issue
https://doi.org/10.18494/SAM4328
Published: June 30, 2023

License Plate Recognition System for Taiwanese Vehicles Using Cascade of YOLOv Detectors [PDF]

Chun-Cheng Lin, Mao-Huan Hsu, and Cheng-Yu Yeh

(Received January 12, 2023; Accepted May 31, 2023)

Keywords: license plate recognition (LPR), You Only Look Once (YOLO), object detection, deep learning

In this paper, we present a study of the license plate recognition (LPR) system for Taiwanese vehicles using a cascade of You Only Look Once version 4 (YOLOv4) detectors. The LPR system is composed of a vehicle detection model, a license plate (LP) detection model, an LP corner prediction model, and an LPR model. Herein, the pretrained YOLOv4 model was directly applied to vehicle detection. The YOLOv4 framework was adopted in the LP detection and LP recognition models, performing transfer learning on each model. Furthermore, to enhance the accuracy of the LPR system, an LP corner prediction model was developed in this study to predict the four corner positions of an LP to perform a perspective transformation on the plate for alignment purposes. The experimental results show that our LPR system achieves an accuracy of 98.88% when tested on 2049 images of the application-oriented LP dataset, outperforming most LPR systems reported in the literature.

Corresponding author: Cheng-Yu Yeh


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This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article
Chun-Cheng Lin, Mao-Huan Hsu, and Cheng-Yu Yeh , License Plate Recognition System for Taiwanese Vehicles Using Cascade of YOLOv Detectors, Sens. Mater., Vol. 35, No. 6, 2023, p. 2129-2137.



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