Article

Exposing digital forgeries through chromatic aberration

Authors:

Micah K. Johnson,

Hany FaridAuthors Info & Claims

MM&Sec '06: Proceedings of the 8th workshop on Multimedia and security

Pages 48 - 55

https://doi.org/10.1145/1161366.1161376

Published: 26 September 2006 Publication History

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Abstract

Virtually all optical imaging systems introduce a variety of aberrations into an image. Chromatic aberration, for example, results from the failure of an optical system to perfectly focus light of different wavelengths. Lateral chromatic aberration manifests itself, to a first-order approximation, as an expansion/contraction of color channels with respect to one another. When tampering with an image, this aberration is often disturbed and fails to be consistent across the image. We describe a computational technique for automatically estimating lateral chromatic aberration and show its efficacy in detecting digital tampering.

References

[1]

T.E. Boult and G. Wolberg. Correcting chromatic aberrations using image warping. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 684--687, 1992.

Crossref

Google Scholar

[2]

H. Farid and E. Simoncelli. Differentiation of multi-dimensional signals. IEEE Transactions on Image Processing, 13(4):496--508, 2004.

Digital Library

Google Scholar

[3]

J. Fridrich, D. Soukal, and J. Lukáš. Detection of copy-move forgery in digital images. In Proceedings of DFRWS, 2003.

Google Scholar

[4]

E. Hecht. Optics. Addison-Wesley Publishing Company, Inc., 4th edition, 2002.

Google Scholar

[5]

M.K. Johnson and H. Farid. Exposing digital forgeries by detecting inconsistencies in lighting. In ACM Multimedia and Security Workshop, New York, NY, 2005.

Digital Library

Google Scholar

[6]

J. Lukáš, J. Fridrich, and M. Goljan. Detecting digital image forgeries using sensor pattern noise. In Proceedings of the SPIE, volume 6072, 2006.

Google Scholar

[7]

T. Ng and S. Chang. A model for image splicing. In IEEE International Conference on Image Processing, Singapore, 2004.

Google Scholar

[8]

A.C. Popescuand, H. Farid. Exposing digital forgeries by detecting duplicated image regions. Technical Report TR2004- 15, Department of Computer Science, Dartmouth College, 2004.

Google Scholar

[9]

A.C. Popescuand, H. Farid. Exposing digital forgeries by detecting traces of resampling. IEEE Transactions on Signal Processing, 53(2):758--767, 2005.

Digital Library

Google Scholar

[10]

A.C. Popescu and H. Farid. Exposing digital forgeries in color filter array interpolated images. IEEE Transactions on Signal Processing, 53(10):3948--3959, 2005.

Digital Library

Google Scholar

[11]

P. Viola and W.M. Wells, III. Alignment by maximization of mutual information. International Journal of Computer Vision, 24(2):137--154, 1997.

Digital Library

Google Scholar

[12]

R.G. Willson and S.A. Shafer. What is the center of the image? Journal of the Optical Society of America A, 11(11):2946--2955, November 1994.

Crossref

Google Scholar

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Capasso PCattaneo GDe Marsico M(2024)A Comprehensive Survey on Methods for Image IntegrityACM Transactions on Multimedia Computing, Communications, and Applications10.1145/363320320:11(1-34)Online publication date: 12-Sep-2024
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Index Terms

Exposing digital forgeries through chromatic aberration
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
  2. Computer graphics
    1. Image manipulation
      1. Image processing

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Published In

MM&Sec '06: Proceedings of the 8th workshop on Multimedia and security

September 2006

244 pages

ISBN:1595934936

DOI:10.1145/1161366

General Chair:
Slava Voloshynovskiy
University of Geneva, Switzerland
,
Program Chairs:
Jana Dittmann
Otto-von-Guericke University, Magdeburg, Germany
,
Jessica Fridrich
SUNY Binghamton, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 26 September 2006

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September 26 - 27, 2006

Geneva, Switzerland

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Overall Acceptance Rate 128 of 318 submissions, 40%

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Capasso PCattaneo GDe Marsico M(2024)A Comprehensive Survey on Methods for Image IntegrityACM Transactions on Multimedia Computing, Communications, and Applications10.1145/363320320:11(1-34)Online publication date: 12-Sep-2024
https://dl.acm.org/doi/10.1145/3633203
Zabin ABourlai T(2024)FaceSensor-ID: A High Precision Approach on Multi-Spectral (Visible and NIR) Camera Sensor Origin IdentificationSoutheastCon 202410.1109/SoutheastCon52093.2024.10500114(1046-1053)Online publication date: 15-Mar-2024
https://doi.org/10.1109/SoutheastCon52093.2024.10500114
Duan HJiang QJin XWozniak MZhao YWu LYao SZhou W(2024)Mf-net: multi-feature fusion network based on two-stream extraction and multi-scale enhancement for face forgery detectionComplex & Intelligent Systems10.1007/s40747-024-01634-611:1Online publication date: 9-Nov-2024
https://doi.org/10.1007/s40747-024-01634-6
Bhowal ANeogy SNaskar R(2024)Deep Learning-based forgery detection and localization for compressed images using a hybrid optimization modelMultimedia Systems10.1007/s00530-024-01336-630:3Online publication date: 21-Apr-2024
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Bharathiraja SRajesh Kanna BGeetha SAnusooya G(2023)Unmasking the digital deception - a comprehensive survey on image forgery and detection techniquesAustralian Journal of Forensic Sciences10.1080/00450618.2023.227057556:6(635-683)Online publication date: 15-Nov-2023
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Huang ZFessler JNorris T(2022)Focal stack based image forgery localizationApplied Optics10.1364/AO.45065461:14(4030)Online publication date: 2-May-2022
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Liu LSun PLang YLi JShi S(2022)Splicing forgery localization via noise fingerprint incorporated with CFA configurationForensic Science International10.1016/j.forsciint.2022.111464340(111464)Online publication date: Nov-2022
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Exposing digital forgeries in color filter array interpolated images

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Exposing digital forgeries in color filter array interpolated images

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