Smart City Gnosys

Smart city article details

Title	Enhanced Yolov8-Based System For Automatic Number Plate Recognition
ID_Doc	23703
Authors	Al-Hasan T.M.; Bonnefille V.; Bensaali F.
Year	2024
Published	Technologies, 12, 9
DOI	http://dx.doi.org/10.3390/technologies12090164
Abstract	This paper presents an advanced automatic number plate recognition (ANPR) system designed specifically for Qatar’s diverse license plate landscape and challenging environmental conditions. Leveraging the YOLOv8 deep learning model, particularly the YOLOv8s variant, we achieve state-of-the-art accuracy in both license plate detection and number recognition. Our innovative approach includes a comprehensive dataset enhancement technique that simulates adverse conditions, significantly improving the model’s robustness in real-world scenarios. We integrate edge computing using a Raspberry Pi with server-side processing, demonstrating an efficient solution for real-time ANPR applications. The system maintains greater than 93% overall performance across various environmental conditions, including night-time and rainy scenarios. We also explore the impact of various pre-processing techniques, including edge detection, k-mean thresholding, DBSCAN, and Gaussian mixture models, on the ANPR system’s performance. Our findings indicate that modern deep learning models like YOLOv8 are sufficiently robust to handle raw input images and do not significantly benefit from additional pre-processing. With its high accuracy and real-time processing capability, the proposed system represents a significant advancement in ANPR technology and is particularly suited for Qatar’s unique traffic management needs and smart city initiatives. © 2024 by the authors.
Author Keywords	ANPR systems; computer vision; image processing; machine learning; Qatari license plates; YOLOv8

Similar Articles

Id	Similarity	Authors	Title	Published
23085	0.908	Rohan Reddy B.; Swathi G.; Himesh E.; Southarrajan S.	Encompassing Yolov8 And Efficientnet B7 For Automatic License Plate Identification	Proceedings - 4th IEEE 2023 International Conference on Computing, Communication, and Intelligent Systems, ICCCIS 2023 (2023)
51292	0.903	Tater R.; Nagrath P.; Mishra J.; de Albuquerque V.H.C.; Menezes J.W.M.	Smart Parking System Using Yolov3 Deep Learning Model	Lecture Notes in Networks and Systems, 787 LNNS (2023)
9657	0.901	Patel D.; Raj A.; Thakkar H.K.	Anprsmac: An Automatic Number Plate Recognizer For Intelligent Transportation In Smart City	2024 International Conference on Computing, Sciences and Communications, ICCSC 2024 (2024)
11398	0.899	Thumthong W.; Meesad P.	Automatic Vehicle License Plate Detection From Security Cameras Using Deep Learning Techniques	5th Research, Invention, and Innovation Congress: Innovative Electricals and Electronics, RI2C 2024 - Proceedings (2024)
62123	0.887	Raza A.; Badidi E.; Badidi B.; Al Zahmi S.	Yolov5 For Automatic License Plate Recognition In Smart Cities	Lecture Notes in Networks and Systems, 768 LNNS (2023)
8890	0.884	Putluru A.R.; Pannuru V.R.; Ashokkumar C.; Kumar C.J.	An Optimized Yolo-Based License Plate Recognition System With Integrated Privacy Safeguards	2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025 - Proceedings (2025)
39268	0.881	Saranya R.; Srimathi B.; Senthil Kumaran R.	No Parking Detection And Security System Using Vehicle Number Plate Recognition	3rd International Conference on Electronics and Sustainable Communication Systems, ICESC 2022 - Proceedings (2022)
22358	0.88	Safran M.; Alajmi A.; Alfarhood S.	Efficient Multistage License Plate Detection And Recognition Using Yolov8 And Cnn For Smart Parking Systems	Journal of Sensors, 2024 (2024)
11353	0.875	Tang J.; Wan L.; Schooling J.; Zhao P.; Chen J.; Wei S.	Automatic Number Plate Recognition (Anpr) In Smart Cities: A Systematic Review On Technological Advancements And Application Cases	Cities, 129 (2022)
7474	0.874	Park S.-H.; Yu S.-B.; Kim J.-A.; Yoon H.	An All-In-One Vehicle Type And License Plate Recognition System Using Yolov4	Sensors, 22, 3 (2022)