Licence Plate Recognition and Vehicle Identification US-ING Deep Learning

This paper presents a methodology for automated licence plate recognition and vehicle identification designed for Ukrainian standards. The approach combines YOLOv11 object detection with EasyOCR text recognition, incorporating deskewing and adaptive thresholding preprocessing techniques. A custom dataset of 467 images containing Ukrainian DSTU-compliant licence plates was created from the Auto. RIA platform. The system employs format-specific error correction and character substitution rules. Experimental results demonstrate an F₁ score of 0.92 at IoU@0.5 for detection tasks, with performance variations across vehicle classes revealing challenges in commercial vehicle recognition and motorcycle licence plate processing. This work contributes annotated dataset for Ukrainian licence plate recognition and provides a practical foundation for automated traffic monitoring systems