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A dataset of color QR codes generated using back-compatible and random colorization algorithms exposed to different illumination-capture channel conditions

Color QR Codes are often generated to encode digital information, but one also could use colors or to allocate colors in a QR Code to act as a color calibration chart. In this dataset, we present several thousand QR Codes images generated with two different colorization algorithms (random and back-c...

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Detalles Bibliográficos
Autores principales: Benito-Altamirano, Ismael, Martínez-Carpena, David, Casals, Olga, Fàbrega, Cristian, Waag, Andreas, Prades, Joan Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9720510/
https://www.ncbi.nlm.nih.gov/pubmed/36478685
http://dx.doi.org/10.1016/j.dib.2022.108780
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author Benito-Altamirano, Ismael
Martínez-Carpena, David
Casals, Olga
Fàbrega, Cristian
Waag, Andreas
Prades, Joan Daniel
author_facet Benito-Altamirano, Ismael
Martínez-Carpena, David
Casals, Olga
Fàbrega, Cristian
Waag, Andreas
Prades, Joan Daniel
author_sort Benito-Altamirano, Ismael
collection PubMed
description Color QR Codes are often generated to encode digital information, but one also could use colors or to allocate colors in a QR Code to act as a color calibration chart. In this dataset, we present several thousand QR Codes images generated with two different colorization algorithms (random and back-compatible) and several tuning variables in these color encoding. The QR Codes were also exposed to three different channel conditions (empty, augmentation and real-life). Also, we derive the SNR and BER computations for these QR Code in comparison with their black and white versions. Finally, we also show if ZBar, a commercial QR Code scanner, is able to read them.
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spelling pubmed-97205102022-12-06 A dataset of color QR codes generated using back-compatible and random colorization algorithms exposed to different illumination-capture channel conditions Benito-Altamirano, Ismael Martínez-Carpena, David Casals, Olga Fàbrega, Cristian Waag, Andreas Prades, Joan Daniel Data Brief Data Article Color QR Codes are often generated to encode digital information, but one also could use colors or to allocate colors in a QR Code to act as a color calibration chart. In this dataset, we present several thousand QR Codes images generated with two different colorization algorithms (random and back-compatible) and several tuning variables in these color encoding. The QR Codes were also exposed to three different channel conditions (empty, augmentation and real-life). Also, we derive the SNR and BER computations for these QR Code in comparison with their black and white versions. Finally, we also show if ZBar, a commercial QR Code scanner, is able to read them. Elsevier 2022-11-24 /pmc/articles/PMC9720510/ /pubmed/36478685 http://dx.doi.org/10.1016/j.dib.2022.108780 Text en © 2022 Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Benito-Altamirano, Ismael
Martínez-Carpena, David
Casals, Olga
Fàbrega, Cristian
Waag, Andreas
Prades, Joan Daniel
A dataset of color QR codes generated using back-compatible and random colorization algorithms exposed to different illumination-capture channel conditions
title A dataset of color QR codes generated using back-compatible and random colorization algorithms exposed to different illumination-capture channel conditions
title_full A dataset of color QR codes generated using back-compatible and random colorization algorithms exposed to different illumination-capture channel conditions
title_fullStr A dataset of color QR codes generated using back-compatible and random colorization algorithms exposed to different illumination-capture channel conditions
title_full_unstemmed A dataset of color QR codes generated using back-compatible and random colorization algorithms exposed to different illumination-capture channel conditions
title_short A dataset of color QR codes generated using back-compatible and random colorization algorithms exposed to different illumination-capture channel conditions
title_sort dataset of color qr codes generated using back-compatible and random colorization algorithms exposed to different illumination-capture channel conditions
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9720510/
https://www.ncbi.nlm.nih.gov/pubmed/36478685
http://dx.doi.org/10.1016/j.dib.2022.108780
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