Automatic License Plate Recognition using the Deep Learning Networks

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Motamed Sara; Askari Elham

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Journal Paper

Paper Information

Journal: International Journal of Information and Communication Technology Research Year:2025 | Volume:17 | Issue:1 Page(s): 21-26

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Title

Automatic License Plate Recognition using the Deep Learning Networks

Author(s)

Motamed Sara | Askari Elham | Issue Writer Certificate

Keywords

license plate detection

deep learning

Yolo algorithm

XGBoost

Encoder-decoder

Abstract

According to today's statistics, more than half a billion vehicles are moving in the world and inspection and monitoring is one of the basic needs of any traffic system. All cars have an identification number or the same license plate as their primary ID, which today is one of the most suitable vehicle authentication tools. In this paper, the high capacity of deep neural networks in learning license plate identifiers is used. The proposed model of this paper has two stages of highlighting the license plate and reading the ID. In this regard, for highlighting, the combination of YOLO and XGBoost network is used in encoder-coder network. The proposed model is evaluated on the FZU Cars dataset and based on the results of the experiments, the proposed model has a higher accuracy than the basic methods.

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