• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

A Method of License Plate Location and Character Recognition based on CNN

Vol. 14, No. 8, August 31, 2020
10.3837/tiis.2020.08.019, Download Paper (Free):

Abstract

At the present time, the economy continues to flourish, and private cars have become the means of choice for most people. Therefore, the license plate recognition technology has become an indispensable part of intelligent transportation, with research and application value. In recent years,the convolution neural network for image classification is an application of deep learning on image processing. This paper proposes a strategy to improve the YOLO model by studying the deep learning convolutional neural network (CNN) and related target detection methods, and combines the OpenCV and TensorFlow frameworks to achieve efficient recognition of license plate characters. The experimental results show that target detection method based on YOLO is beneficial to shorten the training process and achieve a good level of accuracy.


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Cite this article

[IEEE Style]
W. Fang, W. Yi, L. Pang, S. Hou, "A Method of License Plate Location and Character Recognition based on CNN," KSII Transactions on Internet and Information Systems, vol. 14, no. 8, pp. 3488-3500, 2020. DOI: 10.3837/tiis.2020.08.019.

[ACM Style]
Wei Fang, Weinan Yi, Lin Pang, and Shuonan Hou. 2020. A Method of License Plate Location and Character Recognition based on CNN. KSII Transactions on Internet and Information Systems, 14, 8, (2020), 3488-3500. DOI: 10.3837/tiis.2020.08.019.

[BibTeX Style]
@article{tiis:23769, title="A Method of License Plate Location and Character Recognition based on CNN", author="Wei Fang and Weinan Yi and Lin Pang and Shuonan Hou and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2020.08.019}, volume={14}, number={8}, year="2020", month={August}, pages={3488-3500}}