An Efficient and Robust ALPR Model Using YOLOv8 and LPRNet
- Resource Type
- Conference
- Authors
- Subhahan, D. Abdus; Divya, S. Raga; Sree, U. Kavya; Kiriti, T.; Sarthik, Y.
- Source
- 2023 International Conference on Recent Advances in Information Technology for Sustainable Development (ICRAIS) Recent Advances in Information Technology for Sustainable Development (ICRAIS), 2023 International Conference on. :260-265 Nov, 2023
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
General Topics for Engineers
YOLO
Law enforcement
Streaming media
Logic gates
Licenses
Real-time systems
Convolutional neural networks
Deep Learning
License plate detection
license plate recognition
YOLOv8
LPRNet
- Language
ALPR has many applications in the real world like automatic toll collection, traffic management, and law enforcement. This is generally achieved by two basic steps that are detecting the license plate from the image or video footage and then recognizing the characters on it. In this work, we are going to propose a real-time accurate system using two convolutional neural networks (CNN) that are named YOLOV8 and LPRNet. YOLOV8 is the improved and updated version of YOLO algorithms which has shown improvement in recognition and recall rate and also has better recognition speed compared to other versions with a better accuracy rate.