Robust ANPR System Using YOLOv8 and TrOCR with Aspect-Ratio-Based Splitting and Post-Processing

In this paper we present a modular and efficient Automatic Number Plate Recognition (ANPR) system which combines YOLOv8 - based plate detection and transformer-based OCR via TrOCR. A novel aspect-ratio-based splitting strategy helps it recognize vertically stacked number plates. The system has webcam capture and logs cleaned time-stamped output as part of a clear process to follow at some later point in time. Our approach has significant improvements to accuracy and robustness.

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-09-25
DOI
https://doi.org/10.22214/ijraset.2025.74265
Primary Topic
Machine Learning and ELM
Type
article
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article

Robust ANPR System Using YOLOv8 and TrOCR with Aspect-Ratio-Based Splitting and Post-Processing

Deon Menezes
International Journal for Research in Applied Science and Engineering Technology
Machine Learning and ELM
article

Robust ANPR System Using YOLOv8 and TrOCR with Aspect-Ratio-Based Splitting and Post-Processing

Deon Menezes
article en

Abstract

In this paper we present a modular and efficient Automatic Number Plate Recognition (ANPR) system which combines YOLOv8 - based plate detection and transformer-based OCR via TrOCR. A novel aspect-ratio-based splitting strategy helps it recognize vertically stacked number plates. The system has webcam capture and logs cleaned time-stamped output as part of a clear process to follow at some later point in time. Our approach has significant improvements to accuracy and robustness.

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(9)
Openalex Percentile: Top 86%
Machine Learning and ELM
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Robust ANPR System Using YOLOv8 and TrOCR with Aspect-Ratio-Based Splitting and Post-Processing — Deon Menezes · International Journal for Research in Applied Science and Engineering Technology (2025) | TGRS Research Map | TGRS