A Vehicle License Plate Detection and Recognition Method Using Log Gabor Features and Convolutional Neural Networks

References

• Ahsan, M., M. A. Based, and J. Haider. 2021. Intelligent system for vehicles number plate detection and recognition using convolutional neural networks. Technologies 9 (1):9. doi:10.3390/technologies9010009.
   Web of Science ®Google Scholar
• Al-Hmouz, R, and K. Aboura. 2014. License plate localization using a statistical analysis of Discrete Fourier Transform signal. Computers & Electrical Engineering 40 (3):982–92. doi:10.1016/j.compeleceng.2014.01.001.
   Web of Science ®Google Scholar
• Al-Shemarry, M., Y. Li, and S. Abdulla. 2019. An efficient texture descriptor for the detection of license plates from vehicle images in difficult conditions. IEEE Transactions on Intelligent Transportation Systems 21 (2):553–64. doi:10.1109/TITS.2019.2897990.
   Google Scholar
• Anagnostopoulos, C., I. Anagnostopoulos, V. Loumos, and E. Kayafas. 2006. A license plate-recognition algorithm for intelligent transportation system application. IEEE Transactions on Intelligent Transportation Systems 7 (3):377–92. doi:10.1109/TITS.2006.880641.
   Web of Science ®Google Scholar
• Asif, R., Q. Chun, S. Hussain, M. S. Fareed, and S. Khan. 2017. Multinational vehicle license plate detection in complex backgrounds. Journal of Visual Communication and Image Representation 46:176–86. doi:10.1016/j.jvcir.2017.03.020.
   Web of Science ®Google Scholar
• Bai, H. and L. Changping. 2004. A hybrid license plate extraction method based on edge statistics and morphology. In Proc. Conf. on Pattern Recognition (ICPR), 831–4.
   Google Scholar
• Becerikli, Y. A. Olgac, E. Sen, and F. Coskun. 2007. Neural network based license plate recognition system. In Proceeding of the international joint conference on neural networks, Orlando, Florida. 3057–61.
   Google Scholar
• Bulan, O., V. Kozitsky, P. Ramesh, and M. Shreve. 2017. Segmentation and annotation-free license plate recognition with deep localization and failure identification. IEEE Transactions on Intelligent Transportation Systems 18 (9):2351–63. doi:10.1109/TITS.2016.2639020.
   Web of Science ®Google Scholar
• Chen, H, and R. Ching. 2019. Automatic license plate recognition via sliding-window darknet-YOLO deep learning. Image and Vision Computing (87). :47–56. doi:10.1016/j.imavis.2019.04.007.
   Web of Science ®Google Scholar
• Deb, K. M. H. Le, B.-S. Woo, and K. Jo. 2011. Automatic vehicle identification by plate recognition for intelligent transportation system applications. Part II, LNAI6704. Springer-Verlag, Berlin, Heidelberg. 163–72.
   Google Scholar
• Jia, W., H. Zhang, and X. He. 2007. Region-based license plate detection. Journal of Network and Computer Applications 30 (4):1324–33. doi:10.1016/j.jnca.2006.09.010.
   Web of Science ®Google Scholar
• Jianbin, J., Y. Qixiang, and H. Qingming. 2009. A configurable method for multi-style license plate recognition. Pattern Recognition 42:358–69. doi:10.1016/j.patcog.2008.08.016.
   Web of Science ®Google Scholar
• Jing, H., J. Yao, J. Zhao, J. Tu, and Y. Liu. 2019. Multi-oriented and scale-invariant license plate detection based on convolutional neural networks. Sensors 19 (5):1175. doi:10.3390/s19051175.
   PubMed Web of Science ®Google Scholar
• Kahraman, F. B. Kurt, and M. Gökmen. 2003. License plate character segmentation based on the gabor transform and vector quantization. In International Symposium on Computer and Information Sciences, 381–88. Berlin, Heidelberg: Springer. doi:10.1007/978-3-540-39737-348.
   Google Scholar
• Kayal, S. 2012. Automatic license plate detection using gabor filtering and crosscuts. In Conference: Signal Processing, Pattern Recognition and Applications. doi:10.2316/p,40.
   Google Scholar
• Kovesi, P. 1999. Image features from phase congruency. Videre: Journal of Computer Vision Research (1):1–26.
   Google Scholar
• Ktata, S., F. Benzarti, and H. Amiri. 2013. License plate localization using Gabor filters and neural networks. Journal of Computer Science 10:1341–7. doi:10.3844/jcssp.2013.1341.1347.
   Google Scholar
• Lalimi, A., S. Ghofrani, and D. McLernon. 2013. A vehicle license plate detection method using region and edge based methods. Computers & Electrical Engineering 39 (3):834–45. doi:10.1016/j.compeleceng.2012.09.015.
   Web of Science ®Google Scholar
• LeCun, Y, and Y. Bengio. 1995. Convolutional networks for images, speech, and time series. The handbook of brain theory and neural network. MIT Press.
   Google Scholar
• Li, H., W. Peng, Y. Mingyu, and S. Chunhua. 2018. Reading car license plates using deep neural networks. Image and Vision Computing 72:14–23. doi:10.1016/j.imavis.2018.02.002.
   Web of Science ®Google Scholar
• Li, H. P. Wang, and C. Shen. 2017. Towards end-to-end car license plates detection and recognition with deep neural networks”, CoRR, vol. abs/1709.08828. [Online]. Available: http://arxiv.org/abs/1709.08828.
   Google Scholar
• Menotti, D. G. Chiachia, A. Falcao, and O. Neto. 2014. Vehicle license plate recognition with random convolutional networks. In 27th SIBGRAPI Conference on Graphics, Patterns and Images, 298–303.
   Google Scholar
• Montazzolli, S, and R. Jung. 2017. Real-time brazilian license plate detection and recognition using deep convolutional neural networks. In 30th SIBGRAPI Conference on Graphics, Patterns and Images, 55–62.
   Google Scholar
• Montazzolli, S, and J. C. Rosito. 2020. Real-time license plate detection and recognition using deep convolutional neural networks. Journal of Visual Communication and Image Representation (71):102–773. doi:10.1016/j.jvcir.2020.102773.
   Web of Science ®Google Scholar
• Norul, S., H. Sheikh, A. M. Khalid, and R. Yusof. 2006. License plate recognition using multi- cluster and multilayer neural networks. In IEEE 2nd International Conference on Information & Communication Technologies, 1818–23.
   Google Scholar
• Omar, N., S. Abdulkadir, and A.-A. Saeed. 2020. Cascaded deep learning-based efficient approach for license plate detection and recognition. Expert Systems with Applications 149:113280. doi:10.1016/j.eswa.2020.113280.
   Web of Science ®Google Scholar
• Rafique, A., W. Pedrycz, and M. Jeon. 2018. Vehicle license plate detection using region-based convolutional neural networks. Soft Computing 22 (19):6429–40. doi:10.1007/s00500-017-2696-2.
   Web of Science ®Google Scholar
• Redmon, J. K. Divvala, R. B. Girshick, and A. Farhadi. 2016. You only look once: Unified, real-time object detection. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, 779–88.
   Google Scholar
• Sauvola, J, and M. Pietikainen. 2000. Adaptive document image binarization. Pattern Recognition 33 (2):225–36. doi:10.1016/S0031-3203(99)00055-2.
   Web of Science ®Google Scholar
• Selmi, Z., M. B. Halima, U. Pal, and A. Alimi. 2020. DELP-DAR system for license plate detection and recognition. Pattern Recognition Letters (129):213–23. doi:10.1016/j.patrec.2019.11.007.
   Web of Science ®Google Scholar
• Sherin, Y, and S. B. Abderahman. 2008. A smart access control using an efficient license plate location and recognition approach. Expert Systems with Applications 34:256–65. doi:10.1016/j.eswa.2006.09.013.
   Web of Science ®Google Scholar
• Shyang, C., C. Li-Shien, C. Yun, and C. Sei-Wan. 2004. Automatic license plate recognition. IEEE Transactions on Intelligent Transportations Systems 5 (1):42–53. doi:10.1109/TITS.2004.825086.
   Web of Science ®Google Scholar
• Srivastava, G, and R. Srivastava. 2019. Salient object detection using background subtraction, Gabor filters, objectness and minimum directional backgroundness. Journal of Visual Communication and Image Representation 62:330–9. doi:10.1016/j.jvcir.2019.06.005.
   Web of Science ®Google Scholar
• Tadic, V., M. Popovic, and P. Odry. 2016. Fuzzified Gabor filter for license plate detection. Engineering Applications of Artificial Intelligence 48 (48):40–58. doi:10.1016/j.engappai.2015.09.009.
   Web of Science ®Google Scholar
• Wang, T. N. Feng-Chou, L. Keh-Tsong, and C. Yon-Ping. 2004. Robust license plate recognition based on dynamic projection warping. In Proceedings of the IEEE International Conference on Networking, Sensing & Control. 784–8.
   Google Scholar
• Wei, W. M. J. Wang, and Z. X. Huang. 2001. An automatic method of location for number-plate using color features. In Proceedings of the International Conference on Image Processing, vol. 1: 782–5. doi:10.1109/ICIP.2001.959162.
   Google Scholar
• Yu, S., B. Li, Q. Zhang, C. Liu, and H. Meng. 2015. A novel license plate location method based on wavelet transform and EMD analysis. Pattern Recognition 48 (1):114–25. doi:10.1016/j.patcog.2014.07.027.
   Web of Science ®Google Scholar
• Yuan, Y., W. Zou, Z. Yong, X. Wang, X. Hu, and N. Komodakis. 2016. A robust and efficient approach to license plate detection. IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society 26 (3):1102–14. doi:10.1109/TIP.2016.2631901.
   PubMed Web of Science ®Google Scholar
• Zaafouri, A., M. Sayadi, F. Fnaiech, O. Al Jarrah, and W. Wei. 2015. A new method for expiration code detection and recognition using Gabor features based collaborative representation. Advanced Engineering Informatics 29 (4):1072–82. doi:10.1016/j.aei.2015.07.009.
   Web of Science ®Google Scholar
• Zhang, H. W. Jia, X. He, and Q. Wu. 2006. Learning-based license plate detection using global and local features. In International Conference on Pattern Recognition. 1102–5. doi:10.1109/ICPR.2006.758.
   Google Scholar
• Zheng, D., Z. Yannan, and W. Jiaxin. 2005. An efficient method of license plate location. Pattern Recognition Letters 26 (15):2431–8. doi:10.1016/j.patrec.2005.04.014.
   Web of Science ®Google Scholar