3D Convex Hull-Based Registration Method for Point Cloud Watermark Extraction

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...

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Main Authors: Bogdan Lipuš, Borut Žalik
Format: Article
Language:English
Published: MDPI AG 2019-07-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/19/15/3268
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spelling doaj-9bc2f261e715414dbe276af9ffc828d82020-11-25T01:25:42ZengMDPI AGSensors1424-82202019-07-011915326810.3390/s19153268s191532683D Convex Hull-Based Registration Method for Point Cloud Watermark ExtractionBogdan Lipuš0Borut Žalik1Faculty of Electrical Engineering and Computer Science, University of Maribor, Koroška Cesta 46, SI-2000 Maribor, SloveniaFaculty of Electrical Engineering and Computer Science, University of Maribor, Koroška Cesta 46, SI-2000 Maribor, SloveniaMost 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.https://www.mdpi.com/1424-8220/19/15/3268point cloud registrationmulti-scale registrationpoint cloud alignmentpoint cloud watermarkingremote sensing
collection DOAJ
language English
format Article
sources DOAJ
author Bogdan Lipuš
Borut Žalik
spellingShingle Bogdan Lipuš
Borut Žalik
3D Convex Hull-Based Registration Method for Point Cloud Watermark Extraction
Sensors
point cloud registration
multi-scale registration
point cloud alignment
point cloud watermarking
remote sensing
author_facet Bogdan Lipuš
Borut Žalik
author_sort Bogdan Lipuš
title 3D Convex Hull-Based Registration Method for Point Cloud Watermark Extraction
title_short 3D Convex Hull-Based Registration Method for Point Cloud Watermark Extraction
title_full 3D Convex Hull-Based Registration Method for Point Cloud Watermark Extraction
title_fullStr 3D Convex Hull-Based Registration Method for Point Cloud Watermark Extraction
title_full_unstemmed 3D Convex Hull-Based Registration Method for Point Cloud Watermark Extraction
title_sort 3d convex hull-based registration method for point cloud watermark extraction
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2019-07-01
description 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.
topic point cloud registration
multi-scale registration
point cloud alignment
point cloud watermarking
remote sensing
url https://www.mdpi.com/1424-8220/19/15/3268
work_keys_str_mv AT bogdanlipus 3dconvexhullbasedregistrationmethodforpointcloudwatermarkextraction
AT borutzalik 3dconvexhullbasedregistrationmethodforpointcloudwatermarkextraction
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