Abstract:
Detection and recognition of a licence plate is important when automating weighbridge services. While many large databases are available for Latin and Chinese alphanumeri...Show MoreMetadata
Abstract:
Detection and recognition of a licence plate is important when automating weighbridge services. While many large databases are available for Latin and Chinese alphanumeric license plates, data for Indian License Plates is inadequate. In particular, databases of Indian commercial truck license plates are inadequate, despite the fact that commercial vehicle license plate recognition plays a profound role in terms of logistics management and weighbridge automation. Moreover, models to recognise license plates are not effectively able to generalise to such data due to its challenging nature, and due to the abundant frequency of handwritten license plates, leading to usage of diverse font styles. Thus, a database and effective models to recognise and detect such license plates are crucial. This paper provides a database on commercial truck license plates, and using state-of-the-art models in real-time Object Detection: You Only Look Once Version 7, and Scene Text Recognition: Permuted Autoregressive Sequence Models, our method outperforms the other cited references where the maximum accuracy obtained was less than 90%, while we have achieved 95.82% accuracy in our algorithm implementation on the presented challenging license plate dataset.
Published in: 2022 28th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)
Date of Conference: 16-18 November 2022
Date Added to IEEE Xplore: 16 February 2023
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