Vehicle Number Plate Recognition System to Identify the Authenticated Owner of Vehicles
DOI:
https://doi.org/10.61841/2j9b2s66Keywords:
Automatic Number Plate Recognition, Vehicle Number Plate Recognition, Image Processing, ML Kit, Vehicle ThefAbstract
Automatic Number Plate Recognition (ANPR) is the primary source of the Vehicle Number Plate Recognition System. The number plate recognition system is a security system that plays a significant role in identifying the owner of a vehicle. In case of suspicion, the traffic policemen verify the license copy and other documents related to the vehicle. As it is time-consuming and difficult, the Number Plate Recognition system is suggested in this paper. The images of the number plates of the vehicles are scanned and stored in a repository in the system along with the information of the owner. When a suspected vehicle is scanned by the policemen, it generates a one-time password for the owner of the vehicle. Once it is processed, the information about the vehicle and the owner will be displayed. Thus, it helps to identify whether the vehicle is used by the authenticated user and thus helps to find the vehicles that are stolen. The ML Kit algorithm is used for the implementation process.
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[1] Anuja P. Nagare, "License Plate Character Recognition System using Neural Network," International Journal of Computer Application (0975-8887), Volume 25, No. 10, July 2011.
[2] Amit Kukreja Indian vehicle number plate detection using image processing, Vol. 2014; p-ISSN:2395-0072.
[3] Anand sumatilal Jain, Jayashree M. Kundargi Automatic number plate recognition using Artificial Neural Network Vol.2 2015, p- 2395-0072
[4] Aniruddh Puranic, Vehicle Number Plate Recognition System: A Literature Review and Implementation using Template Matching, International Journal of Computer Applications (0975–8887) Volume 134 –No. 1, January 2016
[5] Baoming Shan, "Vehicle License Plate Recognition Based on Text-line Construction and Multilevel RBF
Neural Network," Journal of Computer Science, Vol. No. 6, pp. 246-253, February 2011.
[6] Ch Jaya Lakshmi, Dr. A. DrA.Jhansi Rani, Dr. K. Sri Ramakrishna, M. Lantikiran, and V. R. Siddhartha, A Novel Approach for Indian License Plate Recognition System,” IJAEST, Vol. 2, Issue I, 2011, pp. 010-014.
[7] Deniing Jiang, Tulu Muluneh Mekonnen, Tiruneth Embiale, and Ashenafi Gebrehiwot, “Car Plate Recognition System,” in Fifth International Conference on Intelligent Networks and Intelligent Systems, IEEE, 978-0-7695-4855-5/12, 2012.
[8] Jatinder Singh Vinay Bhardwaj ” Automated Car Number Plate Detection System to Detect Far Number Plates.” International Journal of Research, Volume 03, Issue 11 2016.
[9] Rasheed, S., and O. Ishaq, “Automated Number Plate Recognition using Hough Lines and Template Matching,” Proceedings of the World Congress on Engineering and Computer Sciences, WCECS 2012, San Francisco, USA, vol. 1, 2012, pp. 1-5.
[10] Shokri Gendy, Clifton L. Smith, and Stefan Lachowicz, “Automatic Car Registration Plate Using Fast Hough Transform,” IEEE, 0-7803-3913-4-9/97, 1997, pp. 209-218.
[11] Sourav Roy, Amitava Choudhury, Joydeep Mukherjee, “An Approach towards Detection of Indian Number Plate from Vehicle,” International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-2, Issue-4, March 2013.
[12] Tahir and M. Asif. “Automatic Number Plate Recognition System for Vehicle Identification Using Optical Character Recognition,” Proceedings of the International Conference on Education Technology and Computer, 2009, pp. 335-338.
[13] Vedika Kamble “A Review Paper on Vehicle Number Plate Recognition” IJERT, ISSN: 2278-0181.
[14] Yilmaz, K. "A Smart Hybrid License Plate Recognition System Based on Image Processing Using Neural Network and Image Correlation," pp. 148-153, IEEE 2011.
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