Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/192566
Title: | A dataset of color QR codes generated using back-compatible and random colorization algorithms exposed to different illumination-capture channel conditions |
Author: | Benito Altamirano, Ismael Martínez Carpena, David Casals Guillén, Olga Fabrega, Cristian Waag, Andreas Prades García, Juan Daniel |
Keywords: | Visió per ordinador Reconeixement de formes (Informàtica) Computer vision Pattern recognition systems |
Issue Date: | Feb-2023 |
Publisher: | Elsevier |
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. |
Note: | Reproducció del document publicat a: https://doi.org/10.1016/j.dib.2022.108780 |
It is part of: | Data in Brief, 2023, vol. 46, p. 108780 |
URI: | http://hdl.handle.net/2445/192566 |
Related resource: | https://doi.org/10.1016/j.dib.2022.108780 |
ISSN: | 2352-3409 |
Appears in Collections: | Articles publicats en revistes (Enginyeria Electrònica i Biomèdica) |
Files in This Item:
File | Description | Size | Format | |
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727195.pdf | 1.4 MB | Adobe PDF | View/Open |
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