Proceedings of the 2017 2nd International Conference on Electrical, Control and Automation Engineering (ECAE 2017)

Analysis on the Copy-move and Splicing Forgery of Fragile Watermarking Based on Local Binary Pattern

Authors
Peifei Song, Zhen Yue, Rundong Yang, Jie Shi, Zichen Li
Corresponding Author
Peifei Song
Available Online December 2017.
DOI
https://doi.org/10.2991/ecae-17.2018.50How to use a DOI?
Keywords
fragile watermarking; local binary pattern; copy-move forgery; splicing forgery
Abstract

In the process of transmission, the various factors can effect easily the multimedia information. The receiver can't distinguish whether the received multimedia data has been tampered. The fragile watermarking can authenticate the authenticity and integrality of the multimedia data. The paper analyzes the fragile watermarking based on local binary pattern. Experimental results demonstrate that, in a copy-move and splicing forgery, the existing algorithms can't determine whether a digital image is original or doctored.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 2nd International Conference on Electrical, Control and Automation Engineering (ECAE 2017)
Series
Advances in Engineering Research
Publication Date
December 2017
ISBN
978-94-6252-458-3
ISSN
2352-5401
DOI
https://doi.org/10.2991/ecae-17.2018.50How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Peifei Song
AU  - Zhen Yue
AU  - Rundong Yang
AU  - Jie Shi
AU  - Zichen Li
PY  - 2017/12
DA  - 2017/12
TI  - Analysis on the Copy-move and Splicing Forgery of Fragile Watermarking Based on Local Binary Pattern
BT  - Proceedings of the 2017 2nd International Conference on Electrical, Control and Automation Engineering (ECAE 2017)
PB  - Atlantis Press
SP  - 238
EP  - 240
SN  - 2352-5401
UR  - https://doi.org/10.2991/ecae-17.2018.50
DO  - https://doi.org/10.2991/ecae-17.2018.50
ID  - Song2017/12
ER  -