Open Access
| Issue |
E3S Web Conf.
Volume 664, 2025
4th International Seminar of Science and Applied Technology: “Green Technology and AI-Driven Innovations in Sustainability Development and Environmental Conservation” (ISSAT 2025)
|
|
|---|---|---|
| Article Number | 01012 | |
| Number of page(s) | 9 | |
| Section | Artificial Intelligence and Human-Computer Interaction | |
| DOI | https://doi.org/10.1051/e3sconf/202566401012 | |
| Published online | 20 November 2025 | |
- S. Du, M. Ibrahim, M. Shehata, W. Badawy, Automatic license plate recognition (ALPR): A state-of-the-art review. IEEE Trans. Circuits Syst. Video Technol. 23, 311–325 (2013). https://doi.org/10.1109/TCSVT.2012.2203741 [CrossRef] [Google Scholar]
- R.A. Tavares, Comparison of image preprocessing techniques for vehicle license plate recognition using OCR: performance and accuracy evaluation. arXiv preprint (2024). http://arxiv.org/abs/2410.13622 [Google Scholar]
- S. Bora, Optimizing OCR performance for programming videos: The role of large language models and image super-resolution. MDPI Mathematics 12, 1036 (2025). https://www.mdpi.com/2227-7390/12/7/1036 [Google Scholar]
- H. Zhou, X. Liu, L. Zhang, Super-resolution with OCR optimization. MDPI Mathematics 12, 1036 (2021). https://www.mdpi.com/2227-7390/12/7/1036 [Google Scholar]
- S. Li, AI and machine learning in OCR systems. SpringerLink (2023). https://link.springer.com/article/10.1007/978-3-031-54744-1_17 [Google Scholar]
- C. Li, W. Zhang, Y. Zhao, Digitization of historical documents using OCR. Elsevier (2022). https://www.elsevier.com/books/optical-character-recognition/978-0128149649 [Google Scholar]
- Q. Zhang, J. Liu, K. Yang, A survey of deep learning approaches for OCR and document understanding. ScienceDirect Neurocomputing 523, (2020). https://www.sciencedirect.com/science/article/abs/pii/S0925231223008251 [Google Scholar]
- N. Yousaf, W. Sultani, S. Hussein, OCR optimization using fuzzy logic. DataKnow (2024). https://dataknow.io/en/optimization-of-optical-character-recognition-with-fuzzy-logic [Google Scholar]
- M. Hussein, A. Khan, R. Aziz, Optimized OCR with classifier combination and normalized weights. ResearchGate (2023). https://www.researchgate.net/publication/387271276_Optimizing_OCR_with_Classifi er_Combination_and_Normalized_Weights [Google Scholar]
- T. Kumar, Vehicle license plate detection: A survey. J. Mech. Contin. Math. Sci. 16, (2021). https://doi.org/10.26782/jmcms.2021.10.00004 [Google Scholar]
- K. Kumawat, A. Jain, N. Tiwari, Relevance of automatic number plate recognition systems in vehicle theft detection. RAiSE-2023 Proc. 185, (2024). https://doi.org/10.3390/engproc2023059185 [Google Scholar]
- Y. Wang, Z.-P. Bian, Y. Zhou, L.-P. Chau, Rethinking and designing a high- performing automatic license plate recognition approach. IEEE Trans. Intell. Transp. Syst. (2021) [Google Scholar]
- Lubna, N. Mufti, S.A.A. Shah, Automatic number plate recognition: A detailed survey of relevant algorithms. Sensors 21, 3028 (2021). https://doi.org/10.3390/s21093028 [Google Scholar]
- J. Tang, L. Wan, J. Schooling, P. Zhao, J. Chen, S. Wei, Automatic number plate recognition (ANPR) in smart cities: A systematic review on technological advancements and application cases. Cities 129, 103833 (2022). https://doi.org/10.1016/j.cities.2022 [Google Scholar]
- Z.-P. Bian, Y. Wang, Research on image adaptive enhancement algorithm under low light in license plate recognition system. (2023). [Google Scholar]
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