Abstract
This work proposes a solution for developing a license plate detection and recognition system (LPDR). In the first stage, the poly region of the license plate’s word line(s) can be detected by Character-Region Awareness For Text Detection (CRAFT). Specifically, the text line of the one-line license plate and two lines of the multi-line license plate can be detected effectively. Secondly, each region proposed as a plate number region by CRAFT will be passed to Mobilenet architecture to extract features. Finally, these features will be fed to Bi long short-term memory (Bi-LSTM) architecture with Connectionist Temporal Classification to predict output text in each input region. By applying this solution, the problem of multi-line license plates can be appropriately handled.
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Huynh, A.K., Le, T.D., Huynh, KT. (2023). License Plate Detection and Recognition Using CRAFT and LSTM. In: Braubach, L., Jander, K., Bădică, C. (eds) Intelligent Distributed Computing XV. IDC 2022. Studies in Computational Intelligence, vol 1089. Springer, Cham. https://doi.org/10.1007/978-3-031-29104-3_31
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DOI: https://doi.org/10.1007/978-3-031-29104-3_31
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