Robust watermarking algorithm based on mahalanobis distance and ISS feature point for 3D point cloud data-Reference-Cited by-同舟云学术

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Robust watermarking algorithm based on mahalanobis distance and ISS feature point for 3D point cloud data

Published:2023-12-27 Issue:1 Volume:17 Page:783-796
ISSN:1865-0473
Container-title:Earth Science Informatics
language:en
Short-container-title:Earth Sci Inform

Author:

Zhang Ziyi,Zhang Liming,Wang Pengbin,Zhang Mingwang,Tan Tao

Funder

National Natural Science Foundation of China

Guidance Project of Universities in Gansu Province

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences

Link

https://link.springer.com/content/pdf/10.1007/s12145-023-01206-1.pdf

Reference32 articles.

1. Asikuzzaman M, Pickering MR (2017) An overview of digital video watermarking. IEEE Trans Circuits Syst Video Technol 28(9):2131–2153. https://doi.org/10.1109/TCSVT.2017.2712162

2. Chen H, Xie T, Liang M, Liu W, Liu P (2023) A local tangent plane distance-based approach to 3D point cloud segmentation via clustering. Pattern Recogn 137:109307. https://doi.org/10.1016/j.patcog.2023.109307

3. Cotting D, Weyrich T, Pauly M, Gross M (2004) Robust watermarking of point-sampled geometry. In: Proceedings Shape Modeling Applications. IEEE, 233–242. https://doi.org/10.1109/SMI.2004.1314510

4. De M, Jouan-Rimbaud D, Massart D (2000) The mahalanobis distance. Chemom Intell Lab Syst 50(1):1–18. https://doi.org/10.1016/S0169-7439(99)00047-7

5. Feng X (2015) A new watermarking algorithm for point model using angle quantization index modulation. 2015 4th National Conference on Electrical Electronics and Computer Engineering 963–968. https://doi.org/10.2991/nceece-15.2016.173

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