License plate recognition is a mandatory task in evolved traffic management systems, and automating this process reduces human errors or oversights. This paper describes the development of an automatic system that uses license plate recognition to send real-time notifications to drivers. The system combines two convolutional neural network architectures to perform accurate single and multiple license plate detection and recognition. The license plates are first detected from the acquired image, then the characters and digits are extracted, and the owner is identified in the database. Incorporating the database that stores driver information represents the innovative addition: after extracting the information from the license plate, the system accesses the database and automatically generates e-mail notifications for drivers whose insurance and/or vignette are near their expiration date. The performance evaluation based on precision, recall and F1-score proves the high detection and recognition capabilities of the proposed system, while requiring minimal computational resources.
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Andreș et al. (2024) studied this question.
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