Publication detail

Geometric Alignment by Deep Learning for Recognition of Challenging License Plates

ŠPAŇHEL, J. SOCHOR, J. JURÁNEK, R. HEROUT, A.

Original Title

Geometric Alignment by Deep Learning for Recognition of Challenging License Plates

Type

conference paper

Language

English

Original Abstract

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.

Keywords

License Plate Recognition, CNN, License Plate Dataset, Image Alignment, Intelligent Transportation Systems

Authors

ŠPAŇHEL, J.; SOCHOR, J.; JURÁNEK, R.; HEROUT, A.

Released

4. 11. 2018

Publisher

IEEE Intelligent Transportation Systems Society

Location

Lahaina, Maui

ISBN

978-1-72810-321-1

Book

2018 21st International Conference on Intelligent Transportation Systems (ITSC)

ISBN

2153-0017

Number

21

Pages from

3524

Pages to

3529

Pages count

6

URL

https://ieeexplore.ieee.org/document/8569259

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"
}