Conference proceeding
Anti-Forensics of Chromatic Aberration
MEDIA WATERMARKING, SECURITY, AND FORENSICS 2015, v 9409, pp 94090M-94090M-9
01 Jan 2015
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Over the past decade, a number of information forensic techniques have been developed to identify digital image manipulation and falsification. Recent research has shown, however, that an intelligent forger can use anti-forensic countermeasures to disguise their forgeries. In this paper, an anti-forensic technique is proposed to falsify the lateral chromatic aberration present in a digital image. Lateral chromatic aberration corresponds to the relative contraction or expansion between an image's color channels that occurs due to a lens's inability to focus all wavelengths of light on the same point. Previous work has used localized inconsistencies in an image's chromatic aberration to expose cut-and-paste image forgeries. The anti-forensic technique presented in this paper operates by estimating the expected lateral chromatic aberration at an image location, then removing deviations from this estimate caused by tampering or falsification. Experimental results are presented that demonstrate that our anti-forensic technique can be used to effectively disguise evidence of an image forgery.
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Details
- Title
- Anti-Forensics of Chromatic Aberration
- Creators
- Owen Mayer - Drexel UniversityMatthew C. Stamm - Drexel University
- Contributors
- A M Alattar (Editor)N D Memon (Editor)C D Heitzenrater (Editor)
- Publication Details
- MEDIA WATERMARKING, SECURITY, AND FORENSICS 2015, v 9409, pp 94090M-94090M-9
- Series
- Proceedings of SPIE
- Publisher
- Spie-Int Soc Optical Engineering
- Number of pages
- 9
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000354264600018
- Scopus ID
- 2-s2.0-84932140369
- Other Identifier
- 991019167886504721
UN Sustainable Development Goals (SDGs)
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Theory & Methods
- Imaging Science & Photographic Technology
- Optics