A Robust License Plate Detection and Character Recognition Algorithm Based on a Combined Feature Extraction Model and BPNN
The rapid development of the license plate recognition technology has made great progress for its widespread uses in intelligent transportation system (ITS). This paper has proposed a novel license plate detection and character recognition algorithm based on a combined feature extraction model and B...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2018/6737314 |
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| _version_ | 1832564066573352960 |
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| author | Fei Xie Ming Zhang Jing Zhao Jiquan Yang Yijian Liu Xinyue Yuan |
| author_facet | Fei Xie Ming Zhang Jing Zhao Jiquan Yang Yijian Liu Xinyue Yuan |
| author_sort | Fei Xie |
| collection | DOAJ |
| description | The rapid development of the license plate recognition technology has made great progress for its widespread uses in intelligent transportation system (ITS). This paper has proposed a novel license plate detection and character recognition algorithm based on a combined feature extraction model and BPNN (Backpropagation Neural Network) which is adaptable in weak illumination and complicated backgrounds. Firstly, a preprocessing is first used to strengthen the contrast ratio of original car image. Secondly, the candidate regions of license plate are checked to verify the true plate, and the license plate image is located accurately by the integral projection method. Finally, a new feature extraction model is designed using three sets of features combination, training the feature vectors through BPNN to complete accurate recognition of the license plate characters. The experimental results with different license plate demonstrate effectiveness and efficiency of the proposed algorithm under various complex backgrounds. Compared with three traditional methods, the recognition accuracy of proposed algorithm has increased to 97.7% and the consuming time has decreased to 46.1ms. |
| format | Article |
| id | doaj-art-91a0c776f7624ccea0aa5a5ef482d5e8 |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-91a0c776f7624ccea0aa5a5ef482d5e82025-02-03T01:11:49ZengWileyJournal of Advanced Transportation0197-67292042-31952018-01-01201810.1155/2018/67373146737314A Robust License Plate Detection and Character Recognition Algorithm Based on a Combined Feature Extraction Model and BPNNFei Xie0Ming Zhang1Jing Zhao2Jiquan Yang3Yijian Liu4Xinyue Yuan5School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210042, ChinaDepartment of Electronic Engineering, City University of Hong Kong, Hong KongJiangsu Key Laboratory of 3D Printing Equipment and Manufacturing, Nanjing 210042, ChinaSchool of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210042, ChinaSchool of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210042, ChinaSchool of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210042, ChinaThe rapid development of the license plate recognition technology has made great progress for its widespread uses in intelligent transportation system (ITS). This paper has proposed a novel license plate detection and character recognition algorithm based on a combined feature extraction model and BPNN (Backpropagation Neural Network) which is adaptable in weak illumination and complicated backgrounds. Firstly, a preprocessing is first used to strengthen the contrast ratio of original car image. Secondly, the candidate regions of license plate are checked to verify the true plate, and the license plate image is located accurately by the integral projection method. Finally, a new feature extraction model is designed using three sets of features combination, training the feature vectors through BPNN to complete accurate recognition of the license plate characters. The experimental results with different license plate demonstrate effectiveness and efficiency of the proposed algorithm under various complex backgrounds. Compared with three traditional methods, the recognition accuracy of proposed algorithm has increased to 97.7% and the consuming time has decreased to 46.1ms.http://dx.doi.org/10.1155/2018/6737314 |
| spellingShingle | Fei Xie Ming Zhang Jing Zhao Jiquan Yang Yijian Liu Xinyue Yuan A Robust License Plate Detection and Character Recognition Algorithm Based on a Combined Feature Extraction Model and BPNN Journal of Advanced Transportation |
| title | A Robust License Plate Detection and Character Recognition Algorithm Based on a Combined Feature Extraction Model and BPNN |
| title_full | A Robust License Plate Detection and Character Recognition Algorithm Based on a Combined Feature Extraction Model and BPNN |
| title_fullStr | A Robust License Plate Detection and Character Recognition Algorithm Based on a Combined Feature Extraction Model and BPNN |
| title_full_unstemmed | A Robust License Plate Detection and Character Recognition Algorithm Based on a Combined Feature Extraction Model and BPNN |
| title_short | A Robust License Plate Detection and Character Recognition Algorithm Based on a Combined Feature Extraction Model and BPNN |
| title_sort | robust license plate detection and character recognition algorithm based on a combined feature extraction model and bpnn |
| url | http://dx.doi.org/10.1155/2018/6737314 |
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