Automatic number plate recognition using YOLOv10 and OCR Transformation

This paper presented an improved YOLOv10-based approach for high- performance license plate recognition in challenging mass transit environments. The proposed system enhances Detection accuracy through optimized preprocessing, improved feature extraction, and robust recognition techniques. Experimental results confirm that the improved YOLOv10 model significantly out performs traditional methods in terms of accuracy, speed, and reliability. The system can be effectively integrated into intelligent transportation systems for real-time traffic monitoring, automated toll collection, and enhanced public safety. Future work may focus on integrating edge computing and advanced deep learning models to further improve performance in large-scale smart city deployments.

1.   Wang,A.,Chen,H.,Liu,L.,Chen,K., Lin, Z., Han, J., Ding, G.: Yolov10: Real- time end-to-end object detection. arXiv preprint arXiv:2405.14458 (2024) 2.   Bogdoll,D.,Nitsche, M.,Z¨ollner,J.M.: Anomaly detection in autonomous driving: Asurvey. In:ProceedingsoftheIEEE/CVF Conference on Computer Vision and PatternRecognition,pp.4488–4499(2022) 3.    Dos Reis, D.H., Welfer, D., De Souza Leite Cuadros, M.A., Gamarra, D.F.T.: Mobile robot navigation using an object recognition software with rgbd images and the yolo algorithm. Applied Artificial Intelligence 33, 1290–1305 (2019) 4.   Zeng,F.,Dong,B.,Zhang,Y.,Wang,T., Zhang, X., Wei, Y.: Motr: End-to-end multiple-object tracking with transformer. In: European Conference on Computer Vision, pp. 659–675 (2022). Springer 5.   Ettalibi,A.,Elouadi,A.,Mansour,A.:Ai and computer vision-based real-time quality control: A review of industrial applications. Procedia Computer Science 231, 212–220 (2024) 6.     Li,J.,Zhou,Z.,Yang,J.,Pepe,A., Gsaxner,C.,Luijten,G.,Qu,C.,Zhang,T., Chen, X., Li, W., et al.: Medshapenet–a large-scaledatasetof3dmedicalshapesfor computer vision. arXiv preprint arXiv:2308.16139 (2023) 7.     Esser, P., Rombach, R., Ommer, B.: Tamingtransformersforhigh-resolution image synthesis. In: Proceedings of the IEEE/CVF Conference on Computer VisionandPatternRecognition,pp.12873– 12883 (2021) 8.     Ditta, A., Ahmed, M.M., Mazhar, T., Shahzad, T., Alahmed, Y., Hamam, H.: Number plate recognition smart parking management system using iot. Measurement: Sensors 37, 101409 (2025) 9.   Chu, Z.: D-yolo a robust framework for object detection in adverse weather conditions.      arXiv                          preprint arXiv:2403.09233 (2024) 10.   Li, C.,Yang, X., Wang, G., Zheng,A., Tan, C., Tang, J.: Disentangled generation network for enlarged license plate recognitionandaunifieddataset.Computer Vision and Image Understanding 238, 103880 (2024)