Publication Details

Perceptual license plate super-resolution with CTC loss

BÍLKOVÁ Zuzana and HRADIŠ Michal. Perceptual license plate super-resolution with CTC loss. In: IS and T International Symposium on Electronic Imaging Science and Technology. Springfield, USA: Society for Imaging Science and Technology, 2020, pp. 52-57. ISSN 2470-1173.
Czech title
Percepční superrozlišení registračních značek s chybovou funkcí CTC
Type
conference paper
Language
english
Authors
Bílková Zuzana, RNDr. (MFF CUNI)
Hradiš Michal, Ing., Ph.D. (DCGM FIT BUT)
Keywords

superresolution, license plate recognition, GAN, deblurring

Abstract

We present a novel method for super-resolution (SR) of license plate images based on an end-to-end convolutional neural networks (CNN) combining generative adversial networksn(GANs) and optical character recognition (OCR). License plate SR systems play an important role in number of security applications such as improvement of road safety, traffic monitoring or surveillance. The specific task requires not only realistic-looking reconstructed images but it also needs to preserve the text information. Standard CNN SR and GANs fail to accomplish this requirment. The incorporation of the OCR pipeline into the method also allows training of the network without the need of ground truth high resolution data which enables easy training on real data with all the real image degradations including compression.

Published
2020
Pages
52-57
Journal
Electronic Imaging, vol. 2020, no. 6, ISSN 2470-1173
Proceedings
IS and T International Symposium on Electronic Imaging Science and Technology
Conference
INTELLIGENT ROBOTICS AND INDUSTRIAL APPLICATIONS USING COMPUTER VISION 2020, Burlingame, CA, USA, US
Publisher
Society for Imaging Science and Technology
Place
Springfield, USA, US
DOI
10.2352/ISSN.2470-1173.2020.6.IRIACV-052
EID Scopus
2-s2.0-85111182509
BibTeX 
@INPROCEEDINGS{FITPUB12938,
   author = "Zuzana B\'{i}lkov\'{a} and Michal Hradi\v{s}",
   title = "Perceptual license plate super-resolution with CTC loss",
   pages = "52--57",
   booktitle = "IS and T International Symposium on Electronic Imaging Science and Technology",
   journal = "Electronic Imaging",
   volume = 2020,
   number = 6,
   year = 2020,
   location = "Springfield, USA, US",
   publisher = "Society for Imaging Science and Technology",
   ISSN = "2470-1173",
   doi = "10.2352/ISSN.2470-1173.2020.6.IRIACV-052",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/12938"
}
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