Real-Time License Plate Recognition using YOLOv9 and Embedded Systems

This research develops an optimized deep learning-based License Plate Recognition (LPR) system, comparing YOLOv8 and YOLOv9 with integrated OCR for improved text extraction. The YOLOv9-OCR combination outperforms YOLOv8 in detection accuracy and efficiency, especially in challenging conditions. The implementation phase involves deploying the trained model on a Raspberry Pi, creating an autonomous, embedded LPR system. Results and performance analysis show that YOLOv9, when combined with OCR, outperforms YOLOv8 in terms of detection accuracy and efficiency, particularly in challenging conditions such as low lighting and occlusions.