A dataset of color QR codes generated using back-compatible and random colorization algorithms exposed to different illumination-capture channel conditions
Ismael Benito-Altamirano,
David Martínez-Carpena,
Olga Casals,
Cristian Fàbrega,
Andreas Waag,
Joan Daniel Prades
Affiliations
Ismael Benito-Altamirano
MIND/IN2UB, Department of Electronic and Biomedical Engineering, Universitat de Barcelona, Carrer de Martí i Franquès, 1, Barcelona, 08028, Barcelona, Spain; ColorSensing SL, Carrer Morales, 21, 1L, Barcelona, 08029, Barcelona, Spain; Corresponding author.
David Martínez-Carpena
ColorSensing SL, Carrer Morales, 21, 1L, Barcelona, 08029, Barcelona, Spain; Department of Mathematics and Computer Science, Universitat de Barcelona, Gran Via de les Corts Catalanes, 585, Barcelona, 08007, Barcelona, Spain
Olga Casals
MIND/IN2UB, Department of Electronic and Biomedical Engineering, Universitat de Barcelona, Carrer de Martí i Franquès, 1, Barcelona, 08028, Barcelona, Spain
Cristian Fàbrega
MIND/IN2UB, Department of Electronic and Biomedical Engineering, Universitat de Barcelona, Carrer de Martí i Franquès, 1, Barcelona, 08028, Barcelona, Spain
Andreas Waag
Institute for Semiconductor Technology, Braunschweig University of Technology, Universitätspl. 2, Braunschweig, 38106, Lower Saxony, Germany
Joan Daniel Prades
MIND/IN2UB, Department of Electronic and Biomedical Engineering, Universitat de Barcelona, Carrer de Martí i Franquès, 1, Barcelona, 08028, Barcelona, Spain; ColorSensing SL, Carrer Morales, 21, 1L, Barcelona, 08029, Barcelona, Spain
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.
