Faculty of Information Technology, BUT

Publication Details

CNN for license plate motion deblurring

SVOBODA Pavel, HRADIŠ Michal, MARŠÍK Lukáš and ZEMČÍK Pavel. CNN for license plate motion deblurring. In: IEEE International Conference on Image Processing (ICIP). Phoenix: IEEE Signal Processing Society, 2016, pp. 1-4. ISBN 978-1-4673-9961-6. Available from: http://ieeexplore.ieee.org/document/7533077/
Czech title
Konvoluční neuronové sítě pro restauraci registračních značek rozmazání pohybem
Type
conference paper
Language
english
Authors
URL
Keywords
Convolutional neural network, Motion blur, Image reconstruction, Blind deconvolution, License plate
Abstract
In this work we explore the previously proposed approach of direct blind deconvolution and denoising with convolutional neural networks (CNN) in a situation where the blur kernels are partially constrained. We focus on blurred images from a real-life traffic surveillance system, on which we, for the first time, demonstrate that neural networks trained on artificial data provide superior reconstruction quality on real images compared to traditional blind deconvolution methods. The training data is easy to obtain by blurring sharp photos from a target system with a very rough approximation of the expected blur kernels, thereby allowing custom CNNs to be trained for a specific application (image content and blur range). Additionally, we evaluate the behavior and limits of the CNNs with respect to blur direction range and length.
Published
2016
Pages
1-4
Proceedings
IEEE International Conference on Image Processing (ICIP)
Conference
International Conference on Image Processing (ICIP) 2016, Phoenix, US
ISBN
978-1-4673-9961-6
Publisher
IEEE Signal Processing Society
Place
Phoenix, US
DOI
BibTeX
@INPROCEEDINGS{FITPUB11280,
   author = "Pavel Svoboda and Michal Hradi\v{s} and Luk\'{a}\v{s} Mar\v{s}\'{i}k and Pavel Zem\v{c}\'{i}k",
   title = "CNN for license plate motion deblurring",
   pages = "1--4",
   booktitle = "IEEE International Conference on Image Processing (ICIP)",
   year = 2016,
   location = "Phoenix, US",
   publisher = "IEEE Signal Processing Society",
   ISBN = "978-1-4673-9961-6",
   doi = "10.1109/ICIP.2016.7533077",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/11280"
}
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