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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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2021/8592216 |
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| _version_ | 1832566594013757440 |
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| 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 |
| collection | DOAJ |
| 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 |
| id | doaj-art-0f3951c0184e49cb98e75542dfa7343d |
| institution | Kabale University |
| issn | 2090-0155 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-0f3951c0184e49cb98e75542dfa7343d2025-02-03T01:03:41ZengWileyJournal of Electrical and Computer Engineering2090-01552021-01-01202110.1155/2021/8592216Research and Implementation of Fast-LPRNet Algorithm for License Plate RecognitionZhichao Wang0Yu Jiang1Jiaxin Liu2Siyu Gong3Jian Yao4Feng Jiang5School of Computer and Information EngineeringSchool of Computer and Information EngineeringSchool of Computer and Information EngineeringSchool of Computer and Information EngineeringSchool of Computer and Information EngineeringSchool of Computer and Information EngineeringThe 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.http://dx.doi.org/10.1155/2021/8592216 |
| spellingShingle | Zhichao Wang Yu Jiang Jiaxin Liu Siyu Gong Jian Yao Feng Jiang Research and Implementation of Fast-LPRNet Algorithm for License Plate Recognition Journal of Electrical and Computer Engineering |
| title | 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_short | Research and Implementation of Fast-LPRNet Algorithm for License Plate Recognition |
| title_sort | research and implementation of fast lprnet algorithm for license plate recognition |
| url | http://dx.doi.org/10.1155/2021/8592216 |
| work_keys_str_mv | AT zhichaowang researchandimplementationoffastlprnetalgorithmforlicenseplaterecognition AT yujiang researchandimplementationoffastlprnetalgorithmforlicenseplaterecognition AT jiaxinliu researchandimplementationoffastlprnetalgorithmforlicenseplaterecognition AT siyugong researchandimplementationoffastlprnetalgorithmforlicenseplaterecognition AT jianyao researchandimplementationoffastlprnetalgorithmforlicenseplaterecognition AT fengjiang researchandimplementationoffastlprnetalgorithmforlicenseplaterecognition |