Automatic license plate recognition using improved deep learning

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Motamed Sara

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Journal Paper

Paper Information

Journal: محاسبات نرم Year:2023 | Volume:12 | Issue:1 Page(s): 41-48

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Information Journal Paper

Title

Automatic license plate recognition using improved deep learning

Author(s)

Motamed Sara | Issue Writer Certificate

Keywords

License plate recognition

Deep learning

Neural Networks

Generative Adversarial Network

Encoding-decoding structure

Abstract

According to today's statistics, more than half a billion vehicles move around the world, making inspection and monitoring one of the basic needs of any traffic control system. All vehicles have an identification number exhibited as the license plate, their primary ID, a vital element. Deep learning methods are adopted to detect vehicle license plates. This proposed method consists of two steps: highlighting the license plate and reading the ID stages. In this context, the combination of deep Neural Networks (DNN) and the competitive Generative Adversarial Network (GAN) is applied in the encoding-coder network/structure for this highlighting. The proposed models are assessed based on the FZU Cars and Stanford Cars datasets, to which the results of this study are compared and discussed. The findings here indicate that the accuracy of this proposed model is almost 98%, subject to the two datasets.

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