Research and Implementation of Fast-LPRNet Algorithm for License Plate Recognition

The license plate recognition is an important part of the intelligent traffic management system, and the application of deep learning to the license plate recognition system can effectively improve the speed and accuracy of recognition. Aiming at the problems of traditional license plate recognition...

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Autores principales:	Zhichao Wang, Yu Jiang, Jiaxin Liu, Siyu Gong, Jian Yao, Feng Jiang
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Computer engineering. Computer hardware TK7885-7895
Acceso en línea:	https://doaj.org/article/0f3951c0184e49cb98e75542dfa7343d
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spelling	oai:doaj.org-article:0f3951c0184e49cb98e75542dfa7343d2021-11-29T00:56:44ZResearch and Implementation of Fast-LPRNet Algorithm for License Plate Recognition2090-015510.1155/2021/8592216https://doaj.org/article/0f3951c0184e49cb98e75542dfa7343d2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/8592216https://doaj.org/toc/2090-0155The license plate recognition is an important part of the intelligent traffic management system, and the application of deep learning to the license plate recognition system can effectively improve the speed and accuracy of recognition. Aiming at the problems of traditional license plate recognition algorithms such as the low accuracy, slow speed, and the recognition rate being easily affected by the environment, a Convolutional Neural Network- (CNN-) based license plate recognition algorithm-Fast-LPRNet is proposed. This algorithm uses the nonsegment recognition method, removes the fully connected layer, and reduces the number of parameters. The algorithm—which has strong generalization ability, scalability, and robustness—performs license plate recognition on the FPGA hardware. Increaseing the depth of network on the basis of the Fast-LPRNet structure, the dataset of Chinese City Parking Dataset (CCPD) can be recognized with an accuracy beyond 90%. The experimental results show that the license plate recognition algorithm has high recognition accuracy, strong generalization ability, and good robustness.Zhichao WangYu JiangJiaxin LiuSiyu GongJian YaoFeng JiangHindawi LimitedarticleComputer engineering. Computer hardwareTK7885-7895ENJournal of Electrical and Computer Engineering, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer engineering. Computer hardware TK7885-7895
spellingShingle	Computer engineering. Computer hardware TK7885-7895 Zhichao Wang Yu Jiang Jiaxin Liu Siyu Gong Jian Yao Feng Jiang Research and Implementation of Fast-LPRNet Algorithm for License Plate Recognition
description	The license plate recognition is an important part of the intelligent traffic management system, and the application of deep learning to the license plate recognition system can effectively improve the speed and accuracy of recognition. Aiming at the problems of traditional license plate recognition algorithms such as the low accuracy, slow speed, and the recognition rate being easily affected by the environment, a Convolutional Neural Network- (CNN-) based license plate recognition algorithm-Fast-LPRNet is proposed. This algorithm uses the nonsegment recognition method, removes the fully connected layer, and reduces the number of parameters. The algorithm—which has strong generalization ability, scalability, and robustness—performs license plate recognition on the FPGA hardware. Increaseing the depth of network on the basis of the Fast-LPRNet structure, the dataset of Chinese City Parking Dataset (CCPD) can be recognized with an accuracy beyond 90%. The experimental results show that the license plate recognition algorithm has high recognition accuracy, strong generalization ability, and good robustness.
format	article
author	Zhichao Wang Yu Jiang Jiaxin Liu Siyu Gong Jian Yao Feng Jiang
author_facet	Zhichao Wang Yu Jiang Jiaxin Liu Siyu Gong Jian Yao Feng Jiang
author_sort	Zhichao Wang
title	Research and Implementation of Fast-LPRNet Algorithm for License Plate Recognition
title_short	Research and Implementation of Fast-LPRNet Algorithm for License Plate Recognition
title_full	Research and Implementation of Fast-LPRNet Algorithm for License Plate Recognition
title_fullStr	Research and Implementation of Fast-LPRNet Algorithm for License Plate Recognition
title_full_unstemmed	Research and Implementation of Fast-LPRNet Algorithm for License Plate Recognition
title_sort	research and implementation of fast-lprnet algorithm for license plate recognition
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/0f3951c0184e49cb98e75542dfa7343d
work_keys_str_mv	AT zhichaowang researchandimplementationoffastlprnetalgorithmforlicenseplaterecognition AT yujiang researchandimplementationoffastlprnetalgorithmforlicenseplaterecognition AT jiaxinliu researchandimplementationoffastlprnetalgorithmforlicenseplaterecognition AT siyugong researchandimplementationoffastlprnetalgorithmforlicenseplaterecognition AT jianyao researchandimplementationoffastlprnetalgorithmforlicenseplaterecognition AT fengjiang researchandimplementationoffastlprnetalgorithmforlicenseplaterecognition
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Research and Implementation of Fast-LPRNet Algorithm for License Plate Recognition

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