Imperceptible QR Watermarks in High-Resolution Videos

Tymoteusz Lindner, Tymoteusz Lindner, Tomasz Hawro, Piotr Syga, Piotr Syga

2024

Abstract

The recent advancements in watermarking have indicated the capacity of deep learning for video copyright protection. We introduce a novel deep neural network architecture that uses QR-coded-based messages for video watermarking. Our framework encompasses an encoder-decoder structure, integrating two noiser components, to adeptly increase the robustness against attacks, including MPEG compression. Our solution is aimed at real-life applications; hence we focus on high-resolution videos and intend the encoded image to be indistinguishable from the cover image. To that end, we perform a subjective evaluation on a group of 72 volunteers as well as calculate objective quality metrics obtaining 0.000241 LPIPS, 1.000 SSIM, and 63.8dB PSNR for the best scenario. The obtained results improve PSNR reported by REVMark (Y. Zhang et al., 2023) by around 30dB and LPIPS by a factor of 100. Furthermore, extensive evaluation on both standard COCO dataset and high-resolution videos underlines the method's high robustness against image distortion attacks, achieving over 0.9 bit accuracy for JPEG (q=90), Dropout (p=0.85) and chroma subsampling (4:2:0).

Paper Citation

in Harvard Style

Lindner T., Hawro T. and Syga P. (2024). Imperceptible QR Watermarks in High-Resolution Videos. In Proceedings of the 21st International Conference on Security and Cryptography - Volume 1: SECRYPT; ISBN 978-989-758-709-2, SciTePress, pages 310-322. DOI: 10.5220/0012849300003767

in Bibtex Style

@conference{secrypt24,
author={Tymoteusz Lindner and Tomasz Hawro and Piotr Syga},
title={Imperceptible QR Watermarks in High-Resolution Videos},
booktitle={Proceedings of the 21st International Conference on Security and Cryptography - Volume 1: SECRYPT},
year={2024},
pages={310-322},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012849300003767},
isbn={978-989-758-709-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 21st International Conference on Security and Cryptography - Volume 1: SECRYPT
TI - Imperceptible QR Watermarks in High-Resolution Videos
SN - 978-989-758-709-2
AU - Lindner T.
AU - Hawro T.
AU - Syga P.
PY - 2024
SP - 310
EP - 322
DO - 10.5220/0012849300003767
PB - SciTePress