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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
Descripción
Sumario: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.