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@article{154955,
        author = {B. Naga Sravan Kumar and B. Naga Sravani and K. Karthik and Y. Surya Dev Varma and A. Deepika Priya and Srikanth Nalluri},
        title = {Vehicle Theft Prevention using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {12},
        pages = {819-823},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=154955},
        abstract = {It is evident that the usage of vehicles has been increasing gradually. The vehicle thefts are also hiking every day. Majority of the cases are reporting related to thefts at parking lots. The already existing vehicle number plate detection systems are proving to be inefficient. Thus there is a strong requirement for improved mechanism to prevent these thefts. In this paper, we develop an automatic facial and number plate recognition system. Here we combine the number plate recognition mechanism with driver face recognition, to keep track of the vehicle along with driver at both entry and exit points of parking premises. This works by detecting the vehicle number plate and driver’s face in the initial step. In the second step, it recognizes the characters in the number plate through Optimal Character Recognition (OCR) and maps the corresponding driver’s face to the number plate and stores this data in the database repository. Finally, at the exit point of the premises, the number plate and driver’s face are once again detected and compared with the data in the database. If the driver’s face matches with the number plate in the database, the vehicle will be allowed to leave the premises, otherwise the driver will be questioned further. This reduces the vehicle thefts by a large margin.},
        keywords = {detection, database repository, Optimal Character Recognition (OCR), recognition.},
        month = {},
        }