3D mesh robust watermarking technique for ownership protection

Farhan A. Alenizi; Fadi Kurdahi; Ahmed Eltawil

doi:10.1109/ACSSC.2017.8335170

3D mesh robust watermarking technique for ownership protection

Farhan A. Alenizi, Fadi Kurdahi, Ahmed Eltawil

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

A 3d mesh blind optimized watermarking technique is proposed in this paper. The technique relies on the displacement process of the vertices locations depending on the modification of the variances of the vertices's norms. Statistical analysis were performed to establish the proper distributions that best fit each mesh, and hence establishing the bins sizes. Several optimizing approaches were introduces in the realms of mesh local roughness, the statistical distributions of the norms, and the displacements in the mesh centers. Experimental results showed that the approach is robust in terms of both the perceptual and the quantitative qualities. Moreover, it was also robust against both the geometry and connectivity attacks.

Original language	English (US)
Title of host publication	Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)	9781538618233
DOIs	https://doi.org/10.1109/ACSSC.2017.8335170
State	Published - Apr 10 2018
Externally published	Yes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2019-11-20

Access to Document

10.1109/ACSSC.2017.8335170

Cite this

@inproceedings{2fd63a6a672b4ad7bfecf3d02f678204,

title = "3D mesh robust watermarking technique for ownership protection",

abstract = "A 3d mesh blind optimized watermarking technique is proposed in this paper. The technique relies on the displacement process of the vertices locations depending on the modification of the variances of the vertices's norms. Statistical analysis were performed to establish the proper distributions that best fit each mesh, and hence establishing the bins sizes. Several optimizing approaches were introduces in the realms of mesh local roughness, the statistical distributions of the norms, and the displacements in the mesh centers. Experimental results showed that the approach is robust in terms of both the perceptual and the quantitative qualities. Moreover, it was also robust against both the geometry and connectivity attacks.",

author = "Alenizi, {Farhan A.} and Fadi Kurdahi and Ahmed Eltawil",

note = "Generated from Scopus record by KAUST IRTS on 2019-11-20",

year = "2018",

month = apr,

day = "10",

doi = "10.1109/ACSSC.2017.8335170",

language = "English (US)",

isbn = "9781538618233",

booktitle = "Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

}

TY - GEN

T1 - 3D mesh robust watermarking technique for ownership protection

AU - Alenizi, Farhan A.

AU - Kurdahi, Fadi

AU - Eltawil, Ahmed

N1 - Generated from Scopus record by KAUST IRTS on 2019-11-20

PY - 2018/4/10

Y1 - 2018/4/10

N2 - A 3d mesh blind optimized watermarking technique is proposed in this paper. The technique relies on the displacement process of the vertices locations depending on the modification of the variances of the vertices's norms. Statistical analysis were performed to establish the proper distributions that best fit each mesh, and hence establishing the bins sizes. Several optimizing approaches were introduces in the realms of mesh local roughness, the statistical distributions of the norms, and the displacements in the mesh centers. Experimental results showed that the approach is robust in terms of both the perceptual and the quantitative qualities. Moreover, it was also robust against both the geometry and connectivity attacks.

AB - A 3d mesh blind optimized watermarking technique is proposed in this paper. The technique relies on the displacement process of the vertices locations depending on the modification of the variances of the vertices's norms. Statistical analysis were performed to establish the proper distributions that best fit each mesh, and hence establishing the bins sizes. Several optimizing approaches were introduces in the realms of mesh local roughness, the statistical distributions of the norms, and the displacements in the mesh centers. Experimental results showed that the approach is robust in terms of both the perceptual and the quantitative qualities. Moreover, it was also robust against both the geometry and connectivity attacks.

UR - http://ieeexplore.ieee.org/document/8335170/

UR - http://www.scopus.com/inward/record.url?scp=85050973933&partnerID=8YFLogxK

U2 - 10.1109/ACSSC.2017.8335170

DO - 10.1109/ACSSC.2017.8335170

M3 - Conference contribution

SN - 9781538618233

BT - Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

3D mesh robust watermarking technique for ownership protection

Abstract

Bibliographical note

Access to Document

Other files and links

Fingerprint

Cite this