Vehicle Number Plate Recognition System

Vehicle Number Plate Recognition (VNPR), also known as Automatic Number Plate Recognition (ANPR), identifies vehicleregistration numbers from images or video frames. It can support parking management, access control, traffic monitoring, andauthorised vehicle tracking. This paper proposes a system that detects a plate region, preprocesses the cropped image,recognises alphanumeric characters using Optical Character Recognition (OCR), validates confidence, and stores permittedresults securely. The methodology covers image acquisition, plate localisation, enhancement, character recognition, andevaluation. Performance may be affected by poor lighting, motion blur, plate angle, occlusion, and regional plate variations. Noexperimental results are claimed because the proposed system has not been benchmarked in a controlled experiment.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-19
DOI
https://doi.org/10.5281/zenodo.23484188
Primary Topic
Vehicle License Plate Recognition
Type
article
Field-Weighted Citation Impact
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article

Vehicle Number Plate Recognition System

Manjit Ghule
Zenodo (CERN European Organization for Nuclear Research)
Vehicle License Plate Recognition
article

Vehicle Number Plate Recognition System

Manjit Ghule
article en

Abstract

Vehicle Number Plate Recognition (VNPR), also known as Automatic Number Plate Recognition (ANPR), identifies vehicleregistration numbers from images or video frames. It can support parking management, access control, traffic monitoring, andauthorised vehicle tracking. This paper proposes a system that detects a plate region, preprocesses the cropped image,recognises alphanumeric characters using Optical Character Recognition (OCR), validates confidence, and stores permittedresults securely. The methodology covers image acquisition, plate localisation, enhancement, character recognition, andevaluation. Performance may be affected by poor lighting, motion blur, plate angle, occlusion, and regional plate variations. Noexperimental results are claimed because the proposed system has not been benchmarked in a controlled experiment.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 14%
Vehicle License Plate Recognition
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