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 [email protected] 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

Authors

Publication Details

Journal
Artificial Intelligence
Published
2025-09-30
DOI
https://doi.org/10.15407/jai2025.03.103
Primary Topic
Vehicle License Plate Recognition
Type
article
Field-Weighted Citation Impact
0.00
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article

Licence Plate Recognition and Vehicle Identification US-ING Deep Learning

T Filimonova, D Sanzharov
Artificial Intelligence
Vehicle License Plate Recognition
article

Licence Plate Recognition and Vehicle Identification US-ING Deep Learning

T Filimonova, D Sanzharov
article en

Abstract

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 [email protected] 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

Artificial IntelligenceVol. 30(AI.2025.30(3))
Openalex Percentile: Top 58%
Vehicle License Plate Recognition
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Licence Plate Recognition and Vehicle Identification US-ING Deep Learning — T Filimonova, D Sanzharov · Artificial Intelligence (2025) | TGRS Research Map | TGRS