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-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. (c) 2022 Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

Automated summary

This article introduces the application and research of color QR Codes. Thousands of QR Codes images were generated using different algorithms and variables, and the signal-to-noise ratio and bit error rate were calculated. The reading performance of a commercial QR Code scanner was also tested.