In real world uses, QR Codes are printed or overlaid on top of complex surfaces, like cylindrical bottles or other daily objects with random topographies that pose big challenges to their readout with the conventional planar algorithms proposed in the standard ISO and implemented in most of the available codes. We propose here a general-purpose method to improve the readability of QR Codes placed on these challenging surfaces, by fitting the topography of the underlying arbitrary surface with thin-plate splines. Then, we compare this new method with other alternatives proposed in the literature, like affine, projective and cylindrical transformations. Results demonstrate that our new approach works well under a variety of arbitrary surface topographies including those assumed in former proposals, and improve their readability by a factor of 4, clearly outperforming state-of-the-art decoders.

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.