1 research outputs found
StegaStamp: Invisible Hyperlinks in Physical Photographs
Printed and digitally displayed photos have the ability to hide imperceptible
digital data that can be accessed through internet-connected imaging systems.
Another way to think about this is physical photographs that have unique QR
codes invisibly embedded within them. This paper presents an architecture,
algorithms, and a prototype implementation addressing this vision. Our key
technical contribution is StegaStamp, a learned steganographic algorithm to
enable robust encoding and decoding of arbitrary hyperlink bitstrings into
photos in a manner that approaches perceptual invisibility. StegaStamp
comprises a deep neural network that learns an encoding/decoding algorithm
robust to image perturbations approximating the space of distortions resulting
from real printing and photography. We demonstrates real-time decoding of
hyperlinks in photos from in-the-wild videos that contain variation in
lighting, shadows, perspective, occlusion and viewing distance. Our prototype
system robustly retrieves 56 bit hyperlinks after error correction - sufficient
to embed a unique code within every photo on the internet.Comment: CVPR 2020, Project page: http://www.matthewtancik.com/stegastam