Indian Commercial Truck License Plate Detection and Recognition for Weighbridge Automation
This addresses weighbridge automation and logistics management for Indian commercial vehicles, but is incremental as it applies existing methods to a new domain-specific dataset.
The paper tackled the problem of detecting and recognizing Indian commercial truck license plates, which are challenging due to inadequate datasets and diverse handwritten fonts, by providing a new database and using YOLOv7 and Permuted Autoregressive Sequence Models to achieve 95.82% accuracy, outperforming previous methods with less than 90% accuracy.
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 the 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 SceneText 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. Index Terms- Automatic License Plate Recognition, character recognition, license plate detection, vision transformer.