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A Blind Watermarking Model of the 3D Object and the Polygonal Mesh Objects for Securing Copyright

In this paper, we propose a novel model for 3D object watermarking. The proposed method is based on the properties of the discrete cosine transform (DCT) of the 3D object vertices to embed a secret grayscale image three times. The watermarking process takes place by using the vertices coefficients a...

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Detalles Bibliográficos
Autores principales: Al-Saadi, Hanan S., Ghareeb, A., Elhadad, Ahmed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8651367/
https://www.ncbi.nlm.nih.gov/pubmed/34887910
http://dx.doi.org/10.1155/2021/1392903
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author Al-Saadi, Hanan S.
Ghareeb, A.
Elhadad, Ahmed
author_facet Al-Saadi, Hanan S.
Ghareeb, A.
Elhadad, Ahmed
author_sort Al-Saadi, Hanan S.
collection PubMed
description In this paper, we propose a novel model for 3D object watermarking. The proposed method is based on the properties of the discrete cosine transform (DCT) of the 3D object vertices to embed a secret grayscale image three times. The watermarking process takes place by using the vertices coefficients and the encrypted image pixels. Moreover, the extraction process is totally blind based on the reverse steps of the embedding process to recover the secret grayscale image. Various performance aspects of the method are measured and compared between the original 3D object and the watermarked one using Euclidean distance, Manhattan distance, cosine distance, and correlation distance. The obtained results show that the proposed model provides better performances in terms of execution time and invisibility.
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spelling pubmed-86513672021-12-08 A Blind Watermarking Model of the 3D Object and the Polygonal Mesh Objects for Securing Copyright Al-Saadi, Hanan S. Ghareeb, A. Elhadad, Ahmed Comput Intell Neurosci Research Article In this paper, we propose a novel model for 3D object watermarking. The proposed method is based on the properties of the discrete cosine transform (DCT) of the 3D object vertices to embed a secret grayscale image three times. The watermarking process takes place by using the vertices coefficients and the encrypted image pixels. Moreover, the extraction process is totally blind based on the reverse steps of the embedding process to recover the secret grayscale image. Various performance aspects of the method are measured and compared between the original 3D object and the watermarked one using Euclidean distance, Manhattan distance, cosine distance, and correlation distance. The obtained results show that the proposed model provides better performances in terms of execution time and invisibility. Hindawi 2021-11-30 /pmc/articles/PMC8651367/ /pubmed/34887910 http://dx.doi.org/10.1155/2021/1392903 Text en Copyright © 2021 Hanan S. Al-Saadi et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Al-Saadi, Hanan S.
Ghareeb, A.
Elhadad, Ahmed
A Blind Watermarking Model of the 3D Object and the Polygonal Mesh Objects for Securing Copyright
title A Blind Watermarking Model of the 3D Object and the Polygonal Mesh Objects for Securing Copyright
title_full A Blind Watermarking Model of the 3D Object and the Polygonal Mesh Objects for Securing Copyright
title_fullStr A Blind Watermarking Model of the 3D Object and the Polygonal Mesh Objects for Securing Copyright
title_full_unstemmed A Blind Watermarking Model of the 3D Object and the Polygonal Mesh Objects for Securing Copyright
title_short A Blind Watermarking Model of the 3D Object and the Polygonal Mesh Objects for Securing Copyright
title_sort blind watermarking model of the 3d object and the polygonal mesh objects for securing copyright
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8651367/
https://www.ncbi.nlm.nih.gov/pubmed/34887910
http://dx.doi.org/10.1155/2021/1392903
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