License Plate Recognition on Low-Cost Devices

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F23%3APU149746" target="_blank" >RIV/00216305:26220/23:PU149746 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
License Plate Recognition on Low-Cost Devices
Original language description
This paper presents a comprehensive approach to vehicle license plate recognition running on low-cost devices. Leveraging convolutional neural networks, we evaluate models like YOLOv7-tiny and YuNet for license plate detection, favoring YuNet's 1080×1080 resolution for the accuracy-computation trade-off. For license plate character recognition, we proposed a YOLOv4-tiny derivation model, achieving good accuracy and fast computation. The proposed approaches were validated on a test set from real traffic using Raspberry Pi 4 as the target computational device.
Czech name
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Czech description
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Project
<a href="/en/project/CK04000027" target="_blank" >CK04000027: Traffic controll system of new generation (SENDER)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2023 15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)
ISBN
979-8-3503-9328-6
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
28-32
Publisher name
IEEE Computer Society
Place of publication
neuveden
Event location
Gent, Belgium
Event date
Oct 30, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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