Practical License Plate Recognition in Unconstrained Surveillance Systems with Adversarial Super-Resolution

Younkwan Lee, Jiwon Jun, Yoojin Hong, Moongu Jeon

2019

Abstract

Although most current license plate (LP) recognition applications have been significantly advanced, they are still limited to ideal environments where training data are carefully annotated with constrained scenes. In this paper, we propose a novel license plate recognition method to handle unconstrained real world traffic scenes. To overcome these difficulties, we use adversarial super-resolution (SR), and one-stage character segmentation and recognition. Combined with a deep convolutional network based on VGG-net, our method provides simple but reasonable training procedure. Moreover, we introduce GIST-LP, a challenging LP dataset where image samples are effectively collected from unconstrained surveillance scenes. Experimental results on AOLP and GIST-LP dataset illustrate that our method, without any scene-specific adaptation, outperforms current LP recognition approaches in accuracy and provides visual enhancement in our SR results that are easier to understand than original data.

Paper Citation

in Harvard Style

Lee Y., Jun J., Hong Y. and Jeon M. (2019). Practical License Plate Recognition in Unconstrained Surveillance Systems with Adversarial Super-Resolution. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP; ISBN 978-989-758-354-4, SciTePress, pages 68-76. DOI: 10.5220/0007378300680076

in Bibtex Style

@conference{visapp19,
author={Younkwan Lee and Jiwon Jun and Yoojin Hong and Moongu Jeon},
title={Practical License Plate Recognition in Unconstrained Surveillance Systems with Adversarial Super-Resolution},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP},
year={2019},
pages={68-76},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007378300680076},
isbn={978-989-758-354-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP
TI - Practical License Plate Recognition in Unconstrained Surveillance Systems with Adversarial Super-Resolution
SN - 978-989-758-354-4
AU - Lee Y.
AU - Jun J.
AU - Hong Y.
AU - Jeon M.
PY - 2019
SP - 68
EP - 76
DO - 10.5220/0007378300680076
PB - SciTePress