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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.

ABSTRACT: 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.

SUBMITTER: Benito-Altamirano I

PROVIDER: S-EPMC9720510 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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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.

Benito-Altamirano Ismael I Martínez-Carpena David D Casals Olga O Fàbrega Cristian C Waag Andreas A Prades Joan Daniel JD

Data in brief 20221124

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 B ...[more]

PMID: 36478685

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