Detail publikace
Geometric Alignment by Deep Learning for Recognition of Challenging License Plates
ŠPAŇHEL, J. SOCHOR, J. JURÁNEK, R. HEROUT, A.
Originální název
Geometric Alignment by Deep Learning for Recognition of Challenging License Plates
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
In this paper, we explore the problem of license
plate recognition in-the-wild (in the meaning of capturing data
in unconstrained conditions, taken from arbitrary viewpoints
and distances). We propose a method for automatic license
plate recognition in-the-wild based on a geometric alignment
of license plates as a preceding step for holistic license plate
recognition. The alignment is done by a Convolutional Neural
Network that estimates control points for rectifying the image
and the following rectification step is formulated so that the
whole alignment and recognition process can be assembled into
one computational graph of a contemporary neural network
framework, such as Tensorflow. The experiments show that the
use of the aligner helps the recognition considerably: the error
rate dropped from 9.6 % to 2.1 % on real-life images of license
plates. The experiments also show that the solution is fast - it
is capable of real-time processing even on an embedded and
low-power platform (Jetson TX2). We collected and annotated
a dataset of license plates called CamCar6k, containing 6,064
images with annotated corner points and ground truth texts.
We make this dataset publicly available.
Klíčová slova
License Plate Recognition, CNN, License Plate
Dataset, Image Alignment, Intelligent Transportation Systems
Autoři
ŠPAŇHEL, J.; SOCHOR, J.; JURÁNEK, R.; HEROUT, A.
Vydáno
4. 11. 2018
Nakladatel
IEEE Intelligent Transportation Systems Society
Místo
Lahaina, Maui
ISBN
978-1-72810-321-1
Kniha
2018 21st International Conference on Intelligent Transportation Systems (ITSC)
ISSN
2153-0017
Číslo
21
Strany od
3524
Strany do
3529
Strany počet
6
URL
BibTex
@inproceedings{BUT155105,
author="Jakub {Špaňhel} and Jakub {Sochor} and Roman {Juránek} and Adam {Herout}",
title="Geometric Alignment by Deep Learning for Recognition of Challenging License Plates",
booktitle="2018 21st International Conference on Intelligent Transportation Systems (ITSC)",
year="2018",
number="21",
pages="3524--3529",
publisher="IEEE Intelligent Transportation Systems Society",
address="Lahaina, Maui",
doi="10.1109/ITSC.2018.8569259",
isbn="978-1-72810-321-1",
issn="2153-0017",
url="https://ieeexplore.ieee.org/document/8569259"
}