License Plate Recognition for Traffic Management
DOI:
https://doi.org/10.54060/JMSS/001.02.001Keywords:
Machine Learning, Detection, Segmentation, Prediction, Training Model, RecognitionAbstract
The objective of this report is to present an overview of the project, license plate recognition. This system is to basically detect a vehicle using the information of the license plate in order to use the information at various valid sites. This tool can work as a part of other big projects in the industry for security purposes as well as for analysis purposes. There is a detailed insight of the project in several different chapters throughout the report. This project is based on detection and recognition algorithms; using several libraries of python to work on images and videos and thereafter using the processed image to further train and test a model using machine learning algorithm such that the recognition is done with higher accuracy. The beginning outlines the introduction to the topic and its importance in the real world by highlighting some other applications using similar approach. Later it highlights the technology and skills in use in order to completely deploy the idea. Further there is an explanation to the feasibility study as well as the requirement specification while system design revolves around the basic designing of several modules which would integrate to work as the whole system and test cases. Implementation and testing approach is being discussed and thereby light has been thrown on the results and conclusion thus bringing attention to system’s limitation and its future scope.
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H. Karwal and A. Girdhar, "Vehicle Number Plate Detection System for Indian Vehicles," 2015 IEEE International Conference on Computational Intelligence & Communication Technology, 2015, pp. 8-12, doi: 10.1109/CICT.2015.13.
S. Saraswathi, R. Subban, T. Shanmugasundari and S. Manogari, "Research on License Plate Recognition Using Digital Image Processing," 2017 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), 2017, pp. 1-6, doi: 10.1109/ICCIC.2017.8524147.
Q. Wang, "License plate recognition via convolutional neural networks," 2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS), 2017, pp. 926-929, doi: 10.1109/ICSESS.2017.8343061
S. N. H. S. Abdullah, K. Omar, S. Sahran and M. Khalid, "License plate recognition based on support vector machine," 2009 International Conference on Electrical Engineering and Informatics, 2009, pp. 78-82, doi: 10.1109/ICEEI.2009.5254811.
R. Boutaba, M. A. Salahuddin, N. Limam et al., “A comprehensive survey on machine learning for networking: evolution, applications and research opportunities”, J Internet Serv Appl, vol. 9, no. 16, 2018.
A. Singh and P. Singh, “A Comprehensive Survey on Machine Learning”, Journal of Management and Service Science, vol. 1, no. 1, pp. 1-17, 2021.
Z. Huang and L. Hou, "Chinese License Plate Detection Based on Deep Neural Network," 2018 International Conference on Control and Robots (ICCR), 2018, pp. 84-88, doi: 10.1109/ICCR.2018.8534484.
L. Li, Y. Wu, Y. Ou, Q. Li, Y. Zhou and D. Chen, "Research on machine learning algorithms and feature extraction for time series," 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), 2017, pp. 1-5, doi: 10.1109/PIMRC.2017.8292668.
L. Zheng and X. He, "Number Plate Recognition Based on Support Vector Machines," 2006 IEEE International Conference on Video and Signal Based Surveillance, 2006, pp. 13-13, doi: 10.1109/AVSS.2006.82.
H. Obeid and R. Zantout, “Line Processing: An Approach to ALPR Character Recognition”, 2007 ACS/IEEE International Con-ference on Computer Systems and Applications, Amman, Jordan, 2007.
O. Obulesu, M. Mahendra and M. T. Reddy, "Machine Learning Techniques and Tools: A Survey," 2018 International Conference on Inventive Research in Computing Applications (ICIRCA), 2018, pp. 605-611, doi: 10.1109/ICIRCA.2018.8597302.
A. Singh, P. Singh, “Image Classification: A Survey”, Journal of Informatics Electrical and Electronics Engineering, vol. 1, no. 1, pp. 1-9, 2020.
P. Singhal, P. Singh and A. Vidyarthi, “Interpretation and localization of Thorax diseases using DCNN in Chest X-Ray”, Journal of Informatics Electrical and Electronics Engineering, vol. 1, no. 1, pp. 1-7, 2020.
A. Singh and P. Singh, “A Comprehensive Survey on Machine Learning”, Journal of Management and Service Science, vol. 1, no. 1, pp. 1-17, 2021.
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