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Research Article
License Plate Detection Based on Open CV
S. Ramya1
Hemasree M2
Moonisha M3
Krithika S4
1Assistant Professor, Department of Information Technology, Er. Perumal Manimekalai College of Engineering, Hosur, Tamilnadu, India. 234 Department of Information Technology, Er. Perumal Manimekalai College of Engineering, Hosur, Tamilnadu, India.
Published Online: May-August 2024
Pages: 136-139
Cite this article
↗ https://www.doi.org/10.59256/indjcst.202403020
References
1. C. Gou, K. Wang, Y. Yao, Z. Li, "Vehicle license plate recognition based on extremal regions and restricted Boltzmann machines", IEEE
Trans. Intell. Transp. Syst., vol. 17, no. 4, pp. 1096-1107, Apr. 2016.
2. S. G. Kim, H. G. Jeon, H. I. Koo, "Deep-learning-based license plate detection method using vehicle region extraction", Electron. Lett., vol.
53, no. 15, pp. 1034- 1036, 2017.
3. Y. Yuan, W. Zou, Y. Zhao, X. Wang, X. Hu, N. Komodakis, "A robust and efficient approach to license plate detection", IEEE Trans. Image
Process., vol. 26, no. 3, pp. 1102-1114, Mar. 2017.
4. İ.Türkyılmaz, K. Kaçan, "License plate recognition system using artificial neural networks", ETRI J., vol. 39, no. 2, pp. 163-172, 2017.
5. J. Xing, J. Li, Z. Xie et al., "Research and implementation of an improved radon transform for license plate recognition", IEEE Int. Conf. on
Intelligent Human Machine Systems and Cybernetics,pp. 45-48, 2016.
6. S. Ren, K. He, R. Girshick et al., "Faster R-CNN: towards real-time object detection with region proposal networks", Int. Conf. on Neural
Information Processing Systems, pp. 91-99, 2015.
7. J. Redmon, A. Farhadi, "YOLO9000: better faster stronger", IEEE Conf. Computer Vision and Pattern Recognition, pp. 6517-6525, 2017.
Trans. Intell. Transp. Syst., vol. 17, no. 4, pp. 1096-1107, Apr. 2016.
2. S. G. Kim, H. G. Jeon, H. I. Koo, "Deep-learning-based license plate detection method using vehicle region extraction", Electron. Lett., vol.
53, no. 15, pp. 1034- 1036, 2017.
3. Y. Yuan, W. Zou, Y. Zhao, X. Wang, X. Hu, N. Komodakis, "A robust and efficient approach to license plate detection", IEEE Trans. Image
Process., vol. 26, no. 3, pp. 1102-1114, Mar. 2017.
4. İ.Türkyılmaz, K. Kaçan, "License plate recognition system using artificial neural networks", ETRI J., vol. 39, no. 2, pp. 163-172, 2017.
5. J. Xing, J. Li, Z. Xie et al., "Research and implementation of an improved radon transform for license plate recognition", IEEE Int. Conf. on
Intelligent Human Machine Systems and Cybernetics,pp. 45-48, 2016.
6. S. Ren, K. He, R. Girshick et al., "Faster R-CNN: towards real-time object detection with region proposal networks", Int. Conf. on Neural
Information Processing Systems, pp. 91-99, 2015.
7. J. Redmon, A. Farhadi, "YOLO9000: better faster stronger", IEEE Conf. Computer Vision and Pattern Recognition, pp. 6517-6525, 2017.
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