A Comparative Study on Thai License Plate Recognition: Object Detection and Transformer Learning Approaches
Car theft remains a significant issue in Thailand, necessitating advanced security solutions. This research investigates the application of license plate recognition (LPR) technology using deep learning models for vehicle and license plate detection, as well as both YOLO and Transformer models for c...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/11021500/ |
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| author | Kwankamon Dittakan Jirawat Thaenthong Thanakorn Prasomkit |
| author_facet | Kwankamon Dittakan Jirawat Thaenthong Thanakorn Prasomkit |
| author_sort | Kwankamon Dittakan |
| collection | DOAJ |
| description | Car theft remains a significant issue in Thailand, necessitating advanced security solutions. This research investigates the application of license plate recognition (LPR) technology using deep learning models for vehicle and license plate detection, as well as both YOLO and Transformer models for character recognition. Experimental results demonstrate that YOLOv5nu achieved a high Mean Average Precision (mAP) of 0.995 for license plate detection, while the Transformer model excelled in character recognition with an accuracy of 0.9108 and a loss of 0.0326. Despite these promising results, the models faced limitations in low-light conditions and complex plate layouts, affecting detection accuracy. Future work should focus on enhancing the models’ adaptability to real-world environments, expanding datasets to include diverse scenarios, and improving robustness against environmental variations. These findings underscore the potential of AI-driven LPR systems in advancing vehicle security technology. |
| format | Article |
| id | doaj-art-91e664a37a1d423386aa094e7146b79e |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-91e664a37a1d423386aa094e7146b79e2025-08-20T03:50:06ZengIEEEIEEE Access2169-35362025-01-0113998029981510.1109/ACCESS.2025.357581111021500A Comparative Study on Thai License Plate Recognition: Object Detection and Transformer Learning ApproachesKwankamon Dittakan0https://orcid.org/0000-0002-0097-8610Jirawat Thaenthong1https://orcid.org/0000-0001-9341-0524Thanakorn Prasomkit2College of Computing, Prince of Songkla University, Phuket, ThailandCollege of Computing, Prince of Songkla University, Phuket, ThailandCollege of Computing, Prince of Songkla University, Phuket, ThailandCar theft remains a significant issue in Thailand, necessitating advanced security solutions. This research investigates the application of license plate recognition (LPR) technology using deep learning models for vehicle and license plate detection, as well as both YOLO and Transformer models for character recognition. Experimental results demonstrate that YOLOv5nu achieved a high Mean Average Precision (mAP) of 0.995 for license plate detection, while the Transformer model excelled in character recognition with an accuracy of 0.9108 and a loss of 0.0326. Despite these promising results, the models faced limitations in low-light conditions and complex plate layouts, affecting detection accuracy. Future work should focus on enhancing the models’ adaptability to real-world environments, expanding datasets to include diverse scenarios, and improving robustness against environmental variations. These findings underscore the potential of AI-driven LPR systems in advancing vehicle security technology.https://ieeexplore.ieee.org/document/11021500/Object detectiondeep learningimage analysistransformer learninglicense plate |
| spellingShingle | Kwankamon Dittakan Jirawat Thaenthong Thanakorn Prasomkit A Comparative Study on Thai License Plate Recognition: Object Detection and Transformer Learning Approaches IEEE Access Object detection deep learning image analysis transformer learning license plate |
| title | A Comparative Study on Thai License Plate Recognition: Object Detection and Transformer Learning Approaches |
| title_full | A Comparative Study on Thai License Plate Recognition: Object Detection and Transformer Learning Approaches |
| title_fullStr | A Comparative Study on Thai License Plate Recognition: Object Detection and Transformer Learning Approaches |
| title_full_unstemmed | A Comparative Study on Thai License Plate Recognition: Object Detection and Transformer Learning Approaches |
| title_short | A Comparative Study on Thai License Plate Recognition: Object Detection and Transformer Learning Approaches |
| title_sort | comparative study on thai license plate recognition object detection and transformer learning approaches |
| topic | Object detection deep learning image analysis transformer learning license plate |
| url | https://ieeexplore.ieee.org/document/11021500/ |
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