Lipuš Bogdan, Žalik Borut
Faculty of Electrical Engineering and Computer Science, University of Maribor, Koroška Cesta 46, SI-2000 Maribor, Slovenia.
Sensors (Basel). 2019 Jul 25;19(15):3268. doi: 10.3390/s19153268.
Most 3D point cloud watermarking techniques apply Principal Component Analysis (PCA) to protect the watermark against affine transformation attacks. Unfortunately, they fail in the case of cropping and random point removal attacks. In this work, an alternative approach is proposed that solves these issues efficiently. A point cloud registration technique is developed, based on a 3D convex hull. The scale and the initial rigid affine transformation between the watermarked and the original point cloud can be estimated in this way to obtain a coarse point cloud registration. An iterative closest point algorithm is performed after that to align the attacked watermarked point cloud to the original one completely. The watermark can then be extracted from the watermarked point cloud easily. The extensive experiments confirmed that the proposed approach resists the affine transformation, cropping, random point removal, and various combinations of these attacks. The most dangerous is an attack with noise that can be handled only to some extent. However, this issue is common to the other state-of-the-art approaches.
大多数三维点云水印技术应用主成分分析（PCA）来保护水印免受仿射变换攻击。不幸的是，在裁剪和随机点去除攻击的情况下它们会失效。在这项工作中，提出了一种能有效解决这些问题的替代方法。基于三维凸包开发了一种点云配准技术。通过这种方式可以估计水印点云和原始点云之间的比例以及初始刚性仿射变换，以获得粗略的点云配准。之后执行迭代最近点算法，将受攻击的水印点云与原始点云完全对齐。然后可以轻松地从水印点云中提取水印。大量实验证实，所提出的方法能够抵抗仿射变换、裁剪、随机点去除以及这些攻击的各种组合。最危险的是带有噪声的攻击，只能在一定程度上处理。然而，这个问题是其他现有技术方法所共有的。
