A regularization approach to blind deblurring and denoising of QR barcodes

QR bar codes are prototypical images for which part of the image is a priori known (required patterns). Open source bar code readers, such as ZBar, are readily available. We exploit both these facts to provide and assess purely regularization-based methods for blind deblurring of QR bar codes in the...

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Main Authors: van Gennip, Yves, Athavale, Prashant, Gilles, Jérôme, Choksi, Rustum
Format: Article
Published: Institute of Electrical and Electronics Engineers 2015
Subjects:
Online Access:https://eprints.nottingham.ac.uk/30717/
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author van Gennip, Yves
Athavale, Prashant
Gilles, Jérôme
Choksi, Rustum
author_facet van Gennip, Yves
Athavale, Prashant
Gilles, Jérôme
Choksi, Rustum
author_sort van Gennip, Yves
building Nottingham Research Data Repository
collection Online Access
description QR bar codes are prototypical images for which part of the image is a priori known (required patterns). Open source bar code readers, such as ZBar, are readily available. We exploit both these facts to provide and assess purely regularization-based methods for blind deblurring of QR bar codes in the presence of noise.
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institution University of Nottingham Malaysia Campus
institution_category Local University
last_indexed 2025-11-14T19:09:55Z
publishDate 2015
publisher Institute of Electrical and Electronics Engineers
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spelling nottingham-307172020-05-04T20:07:42Z https://eprints.nottingham.ac.uk/30717/ A regularization approach to blind deblurring and denoising of QR barcodes van Gennip, Yves Athavale, Prashant Gilles, Jérôme Choksi, Rustum QR bar codes are prototypical images for which part of the image is a priori known (required patterns). Open source bar code readers, such as ZBar, are readily available. We exploit both these facts to provide and assess purely regularization-based methods for blind deblurring of QR bar codes in the presence of noise. Institute of Electrical and Electronics Engineers 2015-09 Article PeerReviewed van Gennip, Yves, Athavale, Prashant, Gilles, Jérôme and Choksi, Rustum (2015) A regularization approach to blind deblurring and denoising of QR barcodes. IEEE Transactions on Image Processing, 24 (9). pp. 2864-2873. ISSN 1941-0042 QR bar code blind deblurring finder pattern TV regularization TV flow http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7106501 doi:10.1109/TIP.2015.2432675 doi:10.1109/TIP.2015.2432675
spellingShingle QR bar code
blind deblurring
finder pattern
TV regularization
TV flow
van Gennip, Yves
Athavale, Prashant
Gilles, Jérôme
Choksi, Rustum
A regularization approach to blind deblurring and denoising of QR barcodes
title A regularization approach to blind deblurring and denoising of QR barcodes
title_full A regularization approach to blind deblurring and denoising of QR barcodes
title_fullStr A regularization approach to blind deblurring and denoising of QR barcodes
title_full_unstemmed A regularization approach to blind deblurring and denoising of QR barcodes
title_short A regularization approach to blind deblurring and denoising of QR barcodes
title_sort regularization approach to blind deblurring and denoising of qr barcodes
topic QR bar code
blind deblurring
finder pattern
TV regularization
TV flow
url https://eprints.nottingham.ac.uk/30717/
https://eprints.nottingham.ac.uk/30717/
https://eprints.nottingham.ac.uk/30717/