Image manipulation detection

Sevinç Bayram; Ismail Avcibaş; Bülent Sankur; Nasir Memon

doi:10.1117/1.2401138

Image manipulation detection

Sevinç Bayram, Ismail Avcibaş, Bülent Sankur, Nasir Memon

Center for Cyber Security

Research output: Contribution to journal › Review article › peer-review

Abstract

Techniques and methodologies for validating the authenticity of digital images and testing for the presence of doctoring and manipulation operations on them has recently attracted attention. We review three categories of forensic features and discuss the design of classifiers between doctored and original images. The performance of classifiers with respect to selected controlled manipulations as well as to uncontrolled manipulations is analyzed. The tools for image manipulation detection are treated under feature fusion and decision fusion scenarios.

Original language	English (US)
Article number	041102
Journal	Journal of Electronic Imaging
Volume	15
Issue number	4
DOIs	https://doi.org/10.1117/1.2401138
State	Published - Oct 2006

ASJC Scopus subject areas

Atomic and Molecular Physics, and Optics
Computer Science Applications
Electrical and Electronic Engineering

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10.1117/1.2401138

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title = "Image manipulation detection",

abstract = "Techniques and methodologies for validating the authenticity of digital images and testing for the presence of doctoring and manipulation operations on them has recently attracted attention. We review three categories of forensic features and discuss the design of classifiers between doctored and original images. The performance of classifiers with respect to selected controlled manipulations as well as to uncontrolled manipulations is analyzed. The tools for image manipulation detection are treated under feature fusion and decision fusion scenarios.",

author = "Sevin{\c c} Bayram and Ismail Avciba{\c s} and B{\"u}lent Sankur and Nasir Memon",

note = "Funding Information: This work has been supported by TUBITAK under research grant KARIYER 104E056. One of the authors (N.M.) was partially supported by a grant from AFOSR",

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AU - Bayram, Sevinç

AU - Avcibaş, Ismail

AU - Sankur, Bülent

AU - Memon, Nasir

N1 - Funding Information: This work has been supported by TUBITAK under research grant KARIYER 104E056. One of the authors (N.M.) was partially supported by a grant from AFOSR

PY - 2006/10

Y1 - 2006/10

N2 - Techniques and methodologies for validating the authenticity of digital images and testing for the presence of doctoring and manipulation operations on them has recently attracted attention. We review three categories of forensic features and discuss the design of classifiers between doctored and original images. The performance of classifiers with respect to selected controlled manipulations as well as to uncontrolled manipulations is analyzed. The tools for image manipulation detection are treated under feature fusion and decision fusion scenarios.

AB - Techniques and methodologies for validating the authenticity of digital images and testing for the presence of doctoring and manipulation operations on them has recently attracted attention. We review three categories of forensic features and discuss the design of classifiers between doctored and original images. The performance of classifiers with respect to selected controlled manipulations as well as to uncontrolled manipulations is analyzed. The tools for image manipulation detection are treated under feature fusion and decision fusion scenarios.

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DO - 10.1117/1.2401138

M3 - Review article

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JF - Journal of Electronic Imaging

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Image manipulation detection

Abstract

ASJC Scopus subject areas

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