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Abstract
In this paper we present a novel method based on singular value decomposition (SVD) for forensic analysis of digital images. We show that image tampering distorts linear dependencies of image rows/columns and derived features can be accurate enough to detect image manipulations and digital forgeries. Extensive experiments show that the proposed approach can outperform the counterparts in the literature.
Original language | English |
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Title of host publication | 2010 IEEE International Conference on Image Processing: proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1765-1768 |
Number of pages | 4 |
ISBN (Electronic) | 9781424479948, 9781424479931 |
ISBN (Print) | 9781424479924 |
DOIs | |
Publication status | Published - 03 Dec 2010 |
Event | 2010 IEEE 17th International Conference on Image Processing - Hong Kong, Hong Kong Duration: 26 Sept 2010 → 29 Sept 2010 |
Publication series
Name | IEEE International Conference on Image Processing |
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Publisher | IEEE |
ISSN (Print) | 1522-4880 |
ISSN (Electronic) | 2381-8549 |
Conference
Conference | 2010 IEEE 17th International Conference on Image Processing |
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Country/Territory | Hong Kong |
City | Hong Kong |
Period | 26/09/2010 → 29/09/2010 |
Keywords
- SVD
- image manipulation detection
- singular value decomposition
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R1118ECI: Centre for Secure Information Technologies (CSIT)
McCanny, J. V. (PI), Cowan, C. (CoI), Crookes, D. (CoI), Fusco, V. (CoI), Linton, D. (CoI), Liu, W. (CoI), Miller, P. (CoI), O'Neill, M. (CoI), Scanlon, W. (CoI) & Sezer, S. (CoI)
01/08/2009 → 30/06/2014
Project: Research