A Practical Approach for License Plate Recognition for Non-Helmeted Motorcycle Riders

To protect motorcycle riders, it is now required to detect license plates while they are not wearing helmets. This research uses the real-time object detector YOLOv10 to demonstrate the real time detection of License plate for helmetless motorcyclists. And, a single convolutional neural network was used in the suggested method to automatically identify a non- helmeted motorcyclist’s License Plate from the video stream. Moreover, the false positive caused by the helmeted rider leaving the video frames was removed using the centroid tracking approach and a horizontal reference line. $\mathbf{9 8. 5 2 \%}$ of all License Plate were detected overall.

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Publication Details

Published
2024-09-18
DOI
https://doi.org/10.1109/ic3i61595.2024.10829329
Citations
1
Primary Topic
Vehicle License Plate Recognition
Type
article
Field-Weighted Citation Impact
0.32
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article

A Practical Approach for License Plate Recognition for Non-Helmeted Motorcycle Riders

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1 citations
Vehicle License Plate Recognition
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article

A Practical Approach for License Plate Recognition for Non-Helmeted Motorcycle Riders

T. Poongodi, A Senthil Kumar, Selvaraj Kesavan, Jeremy Nixon, S Nagaraj
article en
1 citations

Abstract

To protect motorcycle riders, it is now required to detect license plates while they are not wearing helmets. This research uses the real-time object detector YOLOv10 to demonstrate the real time detection of License plate for helmetless motorcyclists. And, a single convolutional neural network was used in the suggested method to automatically identify a non- helmeted motorcyclist’s License Plate from the video stream. Moreover, the false positive caused by the helmeted rider leaving the video frames was removed using the centroid tracking approach and a horizontal reference line. $\mathbf{9 8. 5 2 \%}$ of all License Plate were detected overall.

Jain University (IN), Dayananda Sagar University (IN), Dr. Hari Singh Gour University (IN)
Openalex Percentile: Top 33%
Vehicle License Plate Recognition
0.32
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