{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T15:39:53Z","timestamp":1783611593492,"version":"3.55.0"},"reference-count":69,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,9,17]],"date-time":"2021-09-17T00:00:00Z","timestamp":1631836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,9,17]],"date-time":"2021-09-17T00:00:00Z","timestamp":1631836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Image Video Proc."],"published-print":{"date-parts":[[2021,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Multiple-license plate recognition is gaining popularity in the Intelligent Transport System (ITS) applications for security monitoring and surveillance. Advancements in acquisition devices have increased the availability of high definition (HD) images, which can capture images of multiple vehicles. Since license plate (LP) occupies a relatively small portion of an image, therefore, detection of LP in an image is considered a challenging task. Moreover, the overall performance deteriorates when the aforementioned factor combines with varying illumination conditions, such as night, dusk, and rainy. As it is difficult to locate a small object in an entire image, this paper proposes a two-step approach for plate localization in challenging conditions. In the first step, the Faster-Region-based Convolutional Neural Network algorithm (Faster R-CNN) is used to detect all the vehicles in an image, which results in scaled information to locate plates. In the second step, morphological operations are employed to reduce non-plate regions. Meanwhile, geometric properties are used to localize plates in the HSI color space. This approach increases accuracy and reduces processing time. For character recognition, the look-up table (LUT) classifier using adaptive boosting with modified census transform (MCT) as a feature extractor is used. Both proposed plate detection and character recognition methods have significantly outperformed conventional approaches in terms of precision and recall for multiple plate recognition.<\/jats:p>","DOI":"10.1186\/s13640-021-00572-4","type":"journal-article","created":{"date-parts":[[2021,9,17]],"date-time":"2021-09-17T10:03:29Z","timestamp":1631873009000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Performance enhancement method for multiple license plate recognition in challenging environments"],"prefix":"10.1186","volume":"2021","author":[{"given":"Khurram","family":"Khan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abid","family":"Imran","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hafiz Zia Ur","family":"Rehman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adnan","family":"Fazil","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad","family":"Zakwan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zahid","family":"Mahmood","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,9,17]]},"reference":[{"issue":"1","key":"572_CR1","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1109\/MITS.2013.2292652","volume":"6","author":"C-NE Anagnostopoulos","year":"2014","unstructured":"C.-N.E. Anagnostopoulos, License plate recognition: a brief tutorial. IEEE Intell. Transp. Syst. Mag. 6(1), 59\u201367 (2014). https:\/\/doi.org\/10.1109\/MITS.2013.2292652","journal-title":"IEEE Intell. Transp. Syst. Mag."},{"issue":"8","key":"572_CR2","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1049\/iet-its.2016.0008","volume":"10","author":"MR Asif","year":"2016","unstructured":"M.R. Asif, Q. Chun, S. Hussain, M.S. Fareed, Multiple licence plate detection for Chinese vehicles in dense traffic scenarios. IET Intell. Transp. Syst. 10(8), 535\u2013544 (2016). https:\/\/doi.org\/10.1049\/iet-its.2016.0008","journal-title":"IET Intell. Transp. Syst."},{"key":"572_CR3","doi-asserted-by":"publisher","unstructured":"Shen-Zheng Wang and Hsi-Jian Lee, \u201cDetection and recognition of license plate characters with different appearances,\u201d in Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems, (2003), vol. 2, pp. 979\u2013984. https:\/\/doi.org\/10.1109\/ITSC.2003.1252632","DOI":"10.1109\/ITSC.2003.1252632"},{"issue":"3","key":"572_CR4","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1016\/j.aej.2013.02.005","volume":"52","author":"MA Massoud","year":"2013","unstructured":"M.A. Massoud, M. Sabee, M. Gergais, R. Bakhit, Automated new license plate recognition in Egypt. Alex. Eng. J. 52(3), 319\u2013326 (2013). https:\/\/doi.org\/10.1016\/j.aej.2013.02.005","journal-title":"Alex. Eng. J."},{"issue":"2","key":"572_CR5","doi-asserted-by":"publisher","first-page":"163","DOI":"10.4218\/etrij.17.0115.0766","volume":"39","author":"T Ibrahim","year":"2017","unstructured":"T. Ibrahim, K. Kirami, License plate recognition system using artificial neural networks. ETRI J. 39(2), 163\u2013172 (2017). https:\/\/doi.org\/10.4218\/etrij.17.0115.0766","journal-title":"ETRI J."},{"key":"572_CR6","doi-asserted-by":"publisher","unstructured":"Md. Mostafa Kamal Sarke, Sook Yoon, and Dong Sun Park, A fast and robust license plate detection algorithm based on two-stage cascade AdaBoost, 8(10): 3490\u20133507. https:\/\/doi.org\/10.3837\/tiis.2014.10.012","DOI":"10.3837\/tiis.2014.10.012"},{"key":"572_CR7","doi-asserted-by":"publisher","unstructured":"W.T. Ho, H.W. Lim, and Y.H. Tay, \u201cTwo-stage license plate detection using gentle adaboost and SIFT-SVM,\u201d in 2009 First Asian Conference on Intelligent Information and Database Systems, (2009), pp. 109\u2013114. https:\/\/doi.org\/10.1109\/ACIIDS.2009.25","DOI":"10.1109\/ACIIDS.2009.25"},{"issue":"11","key":"572_CR8","doi-asserted-by":"publisher","first-page":"3014","DOI":"10.1109\/TMM.2020.2967645","volume":"22","author":"C Yan","year":"2020","unstructured":"C. Yan, B. Shao, H. Zhao, R. Ning, Y. Zhang, F. Xu, 3D room layout estimation from a single RGB image. IEEE Trans. Multimed. 22(11), 3014\u20133024 (2020). https:\/\/doi.org\/10.1109\/TMM.2020.2967645","journal-title":"IEEE Trans. Multimed."},{"key":"572_CR9","unstructured":"\u201cA Single Neural Network for Mixed Style License Plate Detection and Recognition | IEEE Journals & Magazine | IEEE Xplore.\u201d https:\/\/ieeexplore.ieee.org\/document\/9337806 (accessed Jul. 16, 2021)"},{"key":"572_CR10","doi-asserted-by":"publisher","unstructured":"S. A. Radzi and M. Khalil-Hani, \u201cCharacter recognition of license plate number using convolutional neural network,\u201d in Visual Informatics: Sustaining Research and Innovations, Berlin, Heidelberg, (2011), pp. 45\u201355. https:\/\/doi.org\/10.1007\/978-3-642-25191-7_6","DOI":"10.1007\/978-3-642-25191-7_6"},{"key":"572_CR11","doi-asserted-by":"publisher","first-page":"100","DOI":"10.3745\/JIPS.04.0022","volume":"12","author":"C Gerber","year":"2016","unstructured":"C. Gerber, M. Chung, Number plate detection with a multi-convolutional neural network approach with optical character recognition for mobile devices. J. Inf. Process. Syst. 12, 100\u2013108 (2016). https:\/\/doi.org\/10.3745\/JIPS.04.0022","journal-title":"J. Inf. Process. Syst."},{"issue":"1","key":"572_CR12","doi-asserted-by":"publisher","DOI":"10.1117\/1.JEI.28.1.013036","volume":"28","author":"K Khan","year":"2019","unstructured":"K. Khan, M.-R. Choi, Automatic license plate detection and recognition framework to enhance security applications. J. Electron. Imaging 28(1), 013036 (2019). https:\/\/doi.org\/10.1117\/1.JEI.28.1.013036","journal-title":"J. Electron. Imaging"},{"issue":"3","key":"572_CR13","doi-asserted-by":"publisher","first-page":"542","DOI":"10.1007\/s12555-011-0314-0","volume":"9","author":"S-K Park","year":"2011","unstructured":"S.-K. Park, D.-G. Sim, New MCT-based face recognition under varying lighting conditions. Int. J. Control Autom. Syst. 9(3), 542\u2013549 (2011). https:\/\/doi.org\/10.1007\/s12555-011-0314-0","journal-title":"Int. J. Control Autom. Syst."},{"issue":"1","key":"572_CR14","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1109\/TVT.2012.2222454","volume":"62","author":"AM Al-Ghaili","year":"2013","unstructured":"A.M. Al-Ghaili, S. Mashohor, A.R. Ramli, A. Ismail, Vertical-edge-based car-license-plate detection method. IEEE Trans. Veh. Technol. 62(1), 26\u201338 (2013). https:\/\/doi.org\/10.1109\/TVT.2012.2222454","journal-title":"IEEE Trans. Veh. Technol."},{"issue":"6","key":"572_CR15","doi-asserted-by":"publisher","first-page":"542","DOI":"10.1049\/iet-its.2017.0224","volume":"12","author":"J Yepez","year":"2018","unstructured":"J. Yepez, S.-B. Ko, Improved license plate localisation algorithm based on morphological operations. IET Intell. Transp. Syst. 12(6), 542\u2013549 (2018). https:\/\/doi.org\/10.1049\/iet-its.2017.0224","journal-title":"IET Intell. Transp. Syst."},{"key":"572_CR16","doi-asserted-by":"publisher","unstructured":"Hsi-Jian Lee, Si-Yuan Chen, and Shen-Zheng Wang, \u201cExtraction and recognition of license plates of motorcycles and vehicles on highways,\u201d in Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004., (2004), vol. 4, pp. 356\u2013359. https:\/\/doi.org\/10.1109\/ICPR.2004.1333776","DOI":"10.1109\/ICPR.2004.1333776"},{"issue":"3","key":"572_CR17","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1109\/TITS.2008.922938","volume":"9","author":"C-NE Anagnostopoulos","year":"2008","unstructured":"C.-N.E. Anagnostopoulos, I.E. Anagnostopoulos, I.D. Psoroulas, V. Loumos, E. Kayafas, License plate recognition from still images and video sequences: a survey. IEEE Trans. Intell. Transp. Syst. 9(3), 377\u2013391 (2008). https:\/\/doi.org\/10.1109\/TITS.2008.922938","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"issue":"2","key":"572_CR18","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1007\/s12239-011-0033-9","volume":"12","author":"BK Cho","year":"2011","unstructured":"B.K. Cho, S.H. Ryu, D.R. Shin, J.I. Jung, License plate extraction method for identification of vehicle violations at a railway level crossing. Int. J. Automot. Technol. 12(2), 281\u2013289 (2011). https:\/\/doi.org\/10.1007\/s12239-011-0033-9","journal-title":"Int. J. Automot. Technol."},{"issue":"6","key":"572_CR19","first-page":"3144","volume":"13","author":"MU Haq","year":"2019","unstructured":"M.U. Haq, A. Shahzad, Z. Mahmood, A.A. Shah, Boosting the face recognition performance of ensemble based LDA for pose, non-uniform illuminations, and low-resolution images. KSII Trans. Internet Inf. Syst. 13(6), 3144\u20133164 (2019)","journal-title":"KSII Trans. Internet Inf. Syst."},{"key":"572_CR20","doi-asserted-by":"publisher","unstructured":"Sang Kyoon Kim, Dae Wook Kim, and Hang Joon Kim, \u201cA recognition of vehicle license plate using a genetic algorithm based segmentation,\u201d in Proceedings of 3rd IEEE International Conference on Image Processing, (1996), vol. 2, pp. 661\u2013664. https:\/\/doi.org\/10.1109\/ICIP.1996.560964.","DOI":"10.1109\/ICIP.1996.560964"},{"issue":"2","key":"572_CR21","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1049\/iet-ipr.2017.0368","volume":"12","author":"MA Khan","year":"2018","unstructured":"M.A. Khan, M. Sharif, M.Y. Javed, T. Akram, M. Yasmin, T. Saba, License number plate recognition system using entropy-based features selection approach with SVM. IET Image Process. 12(2), 200\u2013209 (2018). https:\/\/doi.org\/10.1049\/iet-ipr.2017.0368","journal-title":"IET Image Process."},{"issue":"12","key":"572_CR22","first-page":"6069","volume":"11","author":"Z Mahmood","year":"2017","unstructured":"Z. Mahmood, T. Ali, N. Muhammad, N. Bibi, I. Shahzad, S. Azmat, EAR: enhanced augmented reality system for sports entertainment applications. KSII Trans. Internet Inf. Syst. 11(12), 6069\u20136091 (2017)","journal-title":"KSII Trans. Internet Inf. Syst."},{"key":"572_CR23","doi-asserted-by":"publisher","first-page":"11203","DOI":"10.1109\/ACCESS.2020.3047929","volume":"9","author":"J Shashirangana","year":"2021","unstructured":"J. Shashirangana, H. Padmasiri, D. Meedeniya, C. Perera, Automated license plate recognition: a survey on methods and techniques. IEEE Access 9, 11203\u201311225 (2021). https:\/\/doi.org\/10.1109\/ACCESS.2020.3047929","journal-title":"IEEE Access"},{"key":"572_CR24","unstructured":"H. Li and C. Shen, \u201cReading car license plates using deep convolutional neural networks and LSTMs,\u201d ArXiv160105610 Cs, (2016), Accessed: Dec. 10, 2019. [Online]. http:\/\/arxiv.org\/abs\/1601.05610"},{"issue":"5","key":"572_CR25","doi-asserted-by":"publisher","DOI":"10.1117\/1.JEI.26.5.053027","volume":"26","author":"H Xiang","year":"2017","unstructured":"H. Xiang, Y. Yuan, Y. Zhao, Z. Fu, License plate detection based on fully convolutional networks. J. Electron. Imaging 26(5), 053027 (2017). https:\/\/doi.org\/10.1117\/1.JEI.26.5.053027","journal-title":"J. Electron. Imaging"},{"key":"572_CR26","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-017-2696-2","author":"MA Rafique","year":"2018","unstructured":"M.A. Rafique, W. Pedrycz, M. Jeon, Vehicle license plate detection using region-based convolutional neural networks. Soft Comput. (2018). https:\/\/doi.org\/10.1007\/s00500-017-2696-2","journal-title":"Soft Comput."},{"issue":"6","key":"572_CR27","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2017","unstructured":"S. Ren, K. He, R. Girshick, J. Sun, Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Trans. Pattern Anal. Mach. Intell. 39(6), 1137\u20131149 (2017). https:\/\/doi.org\/10.1109\/TPAMI.2016.2577031","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"2","key":"572_CR28","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1109\/TITS.2017.2784093","volume":"19","author":"L Xie","year":"2018","unstructured":"L. Xie, T. Ahmad, L. Jin, Y. Liu, S. Zhang, A new CNN-based method for multi-directional car license plate detection. IEEE Trans. Intell. Transp. Syst. 19(2), 507\u2013517 (2018). https:\/\/doi.org\/10.1109\/TITS.2017.2784093","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"issue":"3","key":"572_CR29","doi-asserted-by":"publisher","first-page":"1126","DOI":"10.1109\/TITS.2018.2847291","volume":"20","author":"H Li","year":"2019","unstructured":"H. Li, P. Wang, C. Shen, Toward end-to-end car license plate detection and recognition with deep neural networks. IEEE Trans. Intell. Transp. Syst. 20(3), 1126\u20131136 (2019). https:\/\/doi.org\/10.1109\/TITS.2018.2847291","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"issue":"4","key":"572_CR30","doi-asserted-by":"publisher","first-page":"1445","DOI":"10.1109\/TPAMI.2020.2975798","volume":"43","author":"C Yan","year":"2021","unstructured":"C. Yan, B. Gong, Y. Wei, Y. Gao, Deep multi-view enhancement hashing for image retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 43(4), 1445\u20131451 (2021). https:\/\/doi.org\/10.1109\/TPAMI.2020.2975798","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"4","key":"572_CR31","doi-asserted-by":"publisher","first-page":"122:1","DOI":"10.1145\/3404374","volume":"16","author":"C Yan","year":"2020","unstructured":"C. Yan, Z. Li, Y. Zhang, Y. Liu, X. Ji, Y. Zhang, Depth image denoising using nuclear norm and learning graph model. ACM Trans. Multimed. Comput. Commun. Appl. 16(4), 122:1-122:17 (2020). https:\/\/doi.org\/10.1145\/3404374","journal-title":"ACM Trans. Multimed. Comput. Commun. Appl."},{"key":"572_CR32","doi-asserted-by":"publisher","unstructured":"C. Xue, S. Lu, and W. Zhang, \u201cMSR: multi-scale shape regression for scene text detection,\u201d (2019). https:\/\/doi.org\/10.24963\/ijcai.2019\/139","DOI":"10.24963\/ijcai.2019\/139"},{"issue":"07","key":"572_CR33","doi-asserted-by":"publisher","first-page":"11474","DOI":"10.1609\/aaai.v34i07.6812","volume":"34","author":"M Liao","year":"2020","unstructured":"M. Liao, Z. Wan, C. Yao, K. Chen, X. Bai, Real-time scene text detection with differentiable binarization. Proc. AAAI Conf. Artif. Intell. 34(07), 11474\u201311481 (2020). https:\/\/doi.org\/10.1609\/aaai.v34i07.6812","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"572_CR34","doi-asserted-by":"publisher","unstructured":"K. K. Kim, K. I. Kim, J. B. Kim, and H. J. Kim, \u201cLearning-based approach for license plate recognition,\u201d in Neural Networks for Signal Processing X. Proceedings of the 2000 IEEE Signal Processing Society Workshop (Cat. No.00TH8501), (2000), vol. 2, pp. 614\u2013623, https:\/\/doi.org\/10.1109\/NNSP.2000.890140","DOI":"10.1109\/NNSP.2000.890140"},{"issue":"1","key":"572_CR35","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","volume":"9","author":"N Otsu","year":"1979","unstructured":"N. Otsu, A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. 9(1), 62\u201366 (1979). https:\/\/doi.org\/10.1109\/TSMC.1979.4310076","journal-title":"IEEE Trans. Syst. Man Cybern."},{"issue":"11","key":"572_CR36","doi-asserted-by":"publisher","first-page":"1961","DOI":"10.1016\/j.patcog.2005.01.026","volume":"38","author":"S Nomura","year":"2005","unstructured":"S. Nomura, K. Yamanaka, O. Katai, H. Kawakami, T. Shiose, A novel adaptive morphological approach for degraded character image segmentation. Pattern Recognit. 38(11), 1961\u20131975 (2005). https:\/\/doi.org\/10.1016\/j.patcog.2005.01.026","journal-title":"Pattern Recognit."},{"key":"572_CR37","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1016\/j.eswa.2017.12.015","volume":"96","author":"Y Zhang","year":"2018","unstructured":"Y. Zhang et al., Multi-kernel extreme learning machine for EEG classification in brain-computer interfaces. Expert Syst. Appl. 96, 302\u2013310 (2018). https:\/\/doi.org\/10.1016\/j.eswa.2017.12.015","journal-title":"Expert Syst. Appl."},{"key":"572_CR38","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1016\/j.procs.2017.10.068","volume":"116","author":"J Tarigan","year":"2017","unstructured":"J. Tarigan, Nadia, R. Diedan, Y. Suryana, Plate recognition using backpropagation neural network and genetic algorithm. Procedia Comput. Sci. 116, 365\u2013372 (2017). https:\/\/doi.org\/10.1016\/j.procs.2017.10.068","journal-title":"Procedia Comput. Sci."},{"issue":"3","key":"572_CR39","doi-asserted-by":"publisher","first-page":"830","DOI":"10.1109\/TITS.2011.2114346","volume":"12","author":"Y Wen","year":"2011","unstructured":"Y. Wen, Y. Lu, J. Yan, Z. Zhou, K.M. von Deneen, P. Shi, An algorithm for license plate recognition applied to intelligent transportation system. IEEE Trans. Intell. Transp. Syst. 12(3), 830\u2013845 (2011). https:\/\/doi.org\/10.1109\/TITS.2011.2114346","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"issue":"3","key":"572_CR40","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1049\/trit.2018.1015","volume":"3","author":"P Shivakumara","year":"2018","unstructured":"P. Shivakumara, D. Tang, M. Asadzadehkaljahi, T. Lu, U. Pal, M. Hossein Anisi, CNN-RNN based method for license plate recognition. CAAI Trans. Intell. Technol. 3(3), 169\u2013175 (2018). https:\/\/doi.org\/10.1049\/trit.2018.1015","journal-title":"CAAI Trans. Intell. Technol."},{"issue":"9","key":"572_CR41","doi-asserted-by":"publisher","first-page":"2351","DOI":"10.1109\/TITS.2016.2639020","volume":"18","author":"O Bulan","year":"2017","unstructured":"O. Bulan, V. Kozitsky, P. Ramesh, M. Shreve, Segmentation- and annotation-free license plate recognition with deep localization and failure identification. IEEE Trans. Intell. Transp. Syst. 18(9), 2351\u20132363 (2017). https:\/\/doi.org\/10.1109\/TITS.2016.2639020","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"issue":"2","key":"572_CR42","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1109\/TCSVT.2012.2203741","volume":"23","author":"S Du","year":"2013","unstructured":"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(2), 311\u2013325 (2013). https:\/\/doi.org\/10.1109\/TCSVT.2012.2203741","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"3","key":"572_CR43","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1049\/iet-its.2017.0136","volume":"12","author":"Y Yang","year":"2018","unstructured":"Y. Yang, D. Li, Z. Duan, Chinese vehicle license plate recognition using kernel-based extreme learning machine with deep convolutional features. IET Intell. Transp. Syst. 12(3), 213\u2013219 (2018). https:\/\/doi.org\/10.1049\/iet-its.2017.0136","journal-title":"IET Intell. Transp. Syst."},{"key":"572_CR44","unstructured":"C. Xue, S. Lu, S. Bai, W. Zhang, and C. Wang, \u201cI2C2W: image-to-character-to-word transformers for accurate scene text recognition,\u201d ArXiv210508383 Cs, (2021), Accessed: Jul. 15, 2021. [Online]. http:\/\/arxiv.org\/abs\/2105.08383"},{"key":"572_CR45","doi-asserted-by":"crossref","unstructured":"D. Yu et al., \u201cTowards accurate scene text recognition with semantic reasoning networks,\u201d 2020, pp. 12113\u201312122. Accessed: Jul. 15, 2021. [Online]. https:\/\/openaccess.thecvf.com\/content_CVPR_2020\/html\/Yu_Towards_Accurate_Scene_Text_Recognition_With_Semantic_Reasoning_Networks_CVPR_2020_paper.html","DOI":"10.1109\/CVPR42600.2020.01213"},{"key":"572_CR46","doi-asserted-by":"publisher","unstructured":"B. Su and S. Lu, \u201cAccurate scene text recognition based on recurrent neural network,\u201d in Computer Vision\u2014ACCV 2014, (Cham, 2015), pp. 35\u201348. https:\/\/doi.org\/10.1007\/978-3-319-16865-4_3","DOI":"10.1007\/978-3-319-16865-4_3"},{"key":"572_CR47","unstructured":"\u201cIET Digital Library: towards a fully automated car parking system.\u201d https:\/\/digital-library.theiet.org\/content\/journals\/10.1049\/iet-its.2018.5021 (accessed Jul. 19, 2021)"},{"key":"572_CR48","doi-asserted-by":"publisher","unstructured":"R. Girshick, J. Donahue, T. Darrell, and J. Malik, \u201cRich feature hierarchies for accurate object detection and semantic segmentation,\u201d in 2014 IEEE Conference on Computer Vision and Pattern Recognition, (Columbus, 2014), pp. 580\u2013587. https:\/\/doi.org\/10.1109\/CVPR.2014.81","DOI":"10.1109\/CVPR.2014.81"},{"key":"572_CR49","doi-asserted-by":"publisher","unstructured":"J. Redmon, S. Divvala, R. Girshick, and A. Farhadi, \u201cYou only look once: unified, real-time object detection,\u201d in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (2016), pp. 779\u2013788. https:\/\/doi.org\/10.1109\/CVPR.2016.91","DOI":"10.1109\/CVPR.2016.91"},{"key":"572_CR50","unstructured":"K. Simonyan and A. Zisserman, \u201cVery deep convolutional networks for large-scale image recognition,\u201d presented at the ICLR, (2015)"},{"key":"572_CR51","volume-title":"Digital image processing","author":"RC Gonzalez","year":"2006","unstructured":"R.C. Gonzalez, R.E. Woods, Digital Image Processing, 3rd edn. (Prentice-Hall Inc, Upper Saddle River, 2006)","edition":"3"},{"issue":"1","key":"572_CR52","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1049\/iet-cvi:20050132","volume":"1","author":"B-F Wu","year":"2007","unstructured":"B.-F. Wu, S.-P. Lin, C.-C. Chiu, Extracting characters from real vehicle licence plates out-of-doors. IET Comput. Vis. 1(1), 2\u201310 (2007). https:\/\/doi.org\/10.1049\/iet-cvi:20050132","journal-title":"IET Comput. Vis."},{"issue":"3","key":"572_CR53","doi-asserted-by":"publisher","first-page":"1102","DOI":"10.1109\/TIP.2016.2631901","volume":"26","author":"Y Yuan","year":"2017","unstructured":"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. 26(3), 1102\u20131114 (2017). https:\/\/doi.org\/10.1109\/TIP.2016.2631901","journal-title":"IEEE Trans. Image Process."},{"issue":"2","key":"572_CR54","doi-asserted-by":"publisher","first-page":"552","DOI":"10.1109\/TVT.2012.2226218","volume":"62","author":"G-S Hsu","year":"2013","unstructured":"G.-S. Hsu, J.-C. Chen, Y.-Z. Chung, Application-oriented license plate recognition. IEEE Trans. Veh. Technol. 62(2), 552\u2013561 (2013). https:\/\/doi.org\/10.1109\/TVT.2012.2226218","journal-title":"IEEE Trans. Veh. Technol."},{"issue":"3","key":"572_CR55","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1109\/TITS.2006.880641","volume":"7","author":"CNE Anagnostopoulos","year":"2006","unstructured":"C.N.E. Anagnostopoulos, I.E. Anagnostopoulos, V. Loumos, E. Kayafas, A license plate-recognition algorithm for intelligent transportation system applications. IEEE Trans. Intell. Transp. Syst. 7(3), 377\u2013392 (2006). https:\/\/doi.org\/10.1109\/TITS.2006.880641","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"572_CR56","doi-asserted-by":"crossref","unstructured":"Z. Xu et al., \u201cTowards end-to-end license plate detection and recognition: a large dataset and baseline,\u201d (2018), pp. 255\u2013271. Accessed: Jul. 15, 2021. [Online]. https:\/\/openaccess.thecvf.com\/content_ECCV_2018\/html\/Zhenbo_Xu_Towards_End-to-End_License_ECCV_2018_paper.html","DOI":"10.1007\/978-3-030-01261-8_16"},{"key":"572_CR57","doi-asserted-by":"publisher","unstructured":"J. Zhuang, S. Hou, Z. Wang, and Z.-J. Zha, \u201cTowards human-level license plate recognition,\u201d in Computer Vision\u2014ECCV 2018, (Cham, 2018), pp. 314\u2013329. https:\/\/doi.org\/10.1007\/978-3-030-01219-9_19","DOI":"10.1007\/978-3-030-01219-9_19"},{"key":"572_CR58","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3000072","author":"L Zhang","year":"2020","unstructured":"L. Zhang, P. Wang, H. Li, Z. Li, C. Shen, Y. Zhang, A robust attentional framework for license plate recognition in the wild. IEEE Trans. Intell. Transp. Syst. (2020). https:\/\/doi.org\/10.1109\/TITS.2020.3000072","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"issue":"4","key":"572_CR59","first-page":"3438","volume":"35","author":"Y Zhang","year":"2021","unstructured":"Y. Zhang, Z. Wang, J. Zhuang, Efficient license plate recognition via holistic position attention. Proc. AAAI Conf. Artif. Intell. 35(4), 3438\u20133446 (2021)","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"572_CR60","doi-asserted-by":"crossref","unstructured":"Y. Lee, J. Lee, H. Ahn, and M. Jeon, \u201cSNIDER: single noisy image denoising and rectification for improving license plate recognition,\u201d (2019), pp. 0\u20130. Accessed: Jul. 19, 2021. [Online]. https:\/\/openaccess.thecvf.com\/content_ICCVW_2019\/html\/RLQ\/Lee_SNIDER_Single_Noisy_Image_Denoising_and_Rectification_for_Improving_License_ICCVW_2019_paper.html","DOI":"10.1109\/ICCVW.2019.00131"},{"issue":"4","key":"572_CR61","doi-asserted-by":"publisher","first-page":"1690","DOI":"10.1109\/TITS.2013.2267054","volume":"14","author":"B Li","year":"2013","unstructured":"B. Li, B. Tian, Y. Li, D. Wen, Component-based license plate detection using conditional random field model. IEEE Trans. Intell. Transp. Syst. 14(4), 1690\u20131699 (2013). https:\/\/doi.org\/10.1109\/TITS.2013.2267054","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"572_CR62","doi-asserted-by":"publisher","unstructured":"S. M. Silva and C. R. Jung, \u201cLicense plate detection and recognition in unconstrained scenarios,\u201d in Computer Vision\u2014ECCV 2018, (Cham, 2018), pp. 593\u2013609. https:\/\/doi.org\/10.1007\/978-3-030-01258-8_36","DOI":"10.1007\/978-3-030-01258-8_36"},{"key":"572_CR63","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/j.patcog.2019.01.020","volume":"90","author":"C Luo","year":"2019","unstructured":"C. Luo, L. Jin, Z. Sun, MORAN: a multi-object rectified attention network for scene text recognition. Pattern Recognit. 90, 109\u2013118 (2019). https:\/\/doi.org\/10.1016\/j.patcog.2019.01.020","journal-title":"Pattern Recognit."},{"issue":"07","key":"572_CR64","doi-asserted-by":"publisher","first-page":"12216","DOI":"10.1609\/aaai.v34i07.6903","volume":"34","author":"T Wang","year":"2020","unstructured":"T. Wang et al., Decoupled attention network for text recognition. Proc. AAAI Conf. Artif. Intell. 34(07), 12216\u201312224 (2020). https:\/\/doi.org\/10.1609\/aaai.v34i07.6903","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"572_CR65","unstructured":"S. Zherzdev and A. Gruzdev, \u201cLPRNet: license plate recognition via deep neural networks,\u201d ArXiv180610447 Cs, (2018), Accessed: Jul. 15, 2021. [Online]. http:\/\/arxiv.org\/abs\/1806.10447"},{"key":"572_CR66","doi-asserted-by":"crossref","unstructured":"\u201cEnd-to-end system of license plate localization and recognition.\u201d https:\/\/www.spiedigitallibrary.org\/journals\/Journal-of-Electronic-Imaging\/volume-24\/issue-2\/023020\/End-to-end-system-of-license-plate-localization-and-recognition\/10.1117\/1.JEI.24.2.023020.short?SSO=1 (accessed Jul. 15, 2021)","DOI":"10.1117\/1.JEI.24.2.023020"},{"issue":"4","key":"572_CR67","doi-asserted-by":"publisher","first-page":"971","DOI":"10.1007\/s10044-014-0416-4","volume":"18","author":"Z Mahmood","year":"2015","unstructured":"Z. Mahmood, T. Ali, S. Khattak, L. Hasan, S.U. Khan, Automatic player detection and identification for sports entertainment applications. Pattern Anal. Appl. 18(4), 971\u2013982 (2015). https:\/\/doi.org\/10.1007\/s10044-014-0416-4","journal-title":"Pattern Anal. Appl."},{"key":"572_CR68","doi-asserted-by":"publisher","unstructured":"W. Liu et al., \u201cSSD: single shot multibox detector,\u201d in Computer Vision\u2014ECCV 2016, (Cham, 2016), pp. 21\u201337. https:\/\/doi.org\/10.1007\/978-3-319-46448-0_2","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"572_CR69","unstructured":"J. Redmon and A. Farhadi, \u201cYOLOv3: an Incremental Improvement,\u201d ArXiv180402767 Cs, (2018), Accessed: Jul. 15, 2021. [Online]. http:\/\/arxiv.org\/abs\/1804.02767"}],"container-title":["EURASIP Journal on Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13640-021-00572-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13640-021-00572-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13640-021-00572-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,17]],"date-time":"2021-09-17T10:19:10Z","timestamp":1631873950000},"score":1,"resource":{"primary":{"URL":"https:\/\/jivp-eurasipjournals.springeropen.com\/articles\/10.1186\/s13640-021-00572-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,17]]},"references-count":69,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,12]]}},"alternative-id":["572"],"URL":"https:\/\/doi.org\/10.1186\/s13640-021-00572-4","relation":{},"ISSN":["1687-5281"],"issn-type":[{"value":"1687-5281","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,9,17]]},"assertion":[{"value":"25 April 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 September 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 September 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"30"}}