Abstract
The main intention of this study paper is to explore and analyze the numerous methods that are used for license plate extraction and identification. Analysis is done by detailed study of the prevailing methodologies and their drawbacks were duly notified. Various concepts such as OCR reading, bounding method and other computational techniques were thoroughly studied and are recorded below. Thus, with the knowledge gained from this review, a pristine and a noble method were developed for the same by utilizing the concept of API. This not only involves extraction of characters from the license plate but also aids in the identification of the vehicle model, as a whole, with the help of image processing. This method is not merely effective for detection but also holds good for certain amount of automation with the aid of the upheld database. These techniques of detection backboned by databases can prove to be very effective in a wide range of use-cases in the current world. Such identification as well as compilation of useful data can be implemented in applications such as automatic toll system, fee collection in parking areas, traffic disciplinary maintenance, vehicle monitoring inside a premise and much more.
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Akshayan, R., Vishnu Prashad, S.L., Soundarya, S., Malarvezhi, P., Dayana, R. (2019). Review Paper: Licence Plate and Car Model Recognition. In: Mallick, P., Balas, V., Bhoi, A., Zobaa, A. (eds) Cognitive Informatics and Soft Computing. Advances in Intelligent Systems and Computing, vol 768. Springer, Singapore. https://doi.org/10.1007/978-981-13-0617-4_30
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DOI: https://doi.org/10.1007/978-981-13-0617-4_30
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