Convolutional Neural Networks for Direct Text Deblurring

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F15%3APU117023" target="_blank" >RIV/00216305:26230/15:PU117023 - isvavai.cz</a>

Alternative codes found

RIV/67985556:_____/15:00450667

Result on the web

<a href="http://www.bmva.org/bmvc/2015/papers/paper006/index.html" target="_blank" >http://www.bmva.org/bmvc/2015/papers/paper006/index.html</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5244/C.29.6" target="_blank" >10.5244/C.29.6</a>

Result language

angličtina

Original language name

Convolutional Neural Networks for Direct Text Deblurring

Original language description

In this work we address the problem of blind deconvolution and denoising. We focus on restoration of text documents and we show that this type of highly structured data can be successfully restored by a convolutional neural network. The networks are trained to reconstruct high-quality images directly from blurry inputs without assuming any specific blur and noise models. We demonstrate the performance of the convolutional networks on a large set of text documents and on a combination of realistic de-focus and camera shake blur kernels. On this artificial data, the convolutional networks significantly outperform existing blind deconvolution methods, including those optimized for text, in terms of image quality and OCR accuracy. In fact, the networks outperform even state-of-the-art non-blind methods for anything but the lowest noise levels. The approach is validated on real photos taken by various devices. Further information including test data and trained networks can be found on the [PROJECT PAGE] (http://www.fit.vutbr.cz/~ihradis/CNN-Deblur/).

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2015

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of BMVC 2015

ISBN

1-901725-53-7

ISSN

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e-ISSN

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Number of pages

13

Pages from-to

1-13

Publisher name

The British Machine Vision Association and Society for Pattern Recognition

Place of publication

Swansea

Event location

Swansea

Event date

Sep 7, 2015

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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