StegaStamp: Invisible Hyperlinks in Physical Photographs
| Autor: | Matthew Tancik, Ben Mildenhall, Ren Ng |
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| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
Invisibility Computer science business.industry Computer Vision and Pattern Recognition (cs.CV) Photography Key (cryptography) Computer Science - Computer Vision and Pattern Recognition ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Computer vision Artificial intelligence Hyperlink business |
| Zdroj: | CVPR |
| DOI: | 10.48550/arxiv.1904.05343 |
| Popis: | 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/stegastamp |
| Databáze: | OpenAIRE |
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