  We present a method for reading digital data embedded in planar 3D printed
surfaces. The data are organised in binary arrays and embedded as surface
textures in a way inspired by QR codes. At the core of the retrieval method
lies a Convolutional Neural Network, outputting a confidence map of the
location of the surface textures encoding value 1 bits. Subsequently, the bit
array is retrieved through a series of simple image processing and statistical
operations applied on the confidence map. Extensive experimentation with images
captured from various camera views, under various illumination conditions and
from objects printed with various material colours, shows that the proposed
method generalizes well and achieves the level of accuracy required in
practical applications.
