Digital image tamper detection based on multimodal fusion of residue features

Girija Chetty, Julian Goodwin, Monica Singh

Research output: A Conference proceeding or a Chapter in BookConference contribution

2 Citations (Scopus)

Abstract

In this paper, we propose a novel formulation involving fusion of noise and quantization residue features for detecting tampering or forgery in video sequences. We reiterate the importance of feature selection techniques in conjunction with fusion to enhance the tamper detection accuracy. We examine three different feature selection techniques, the independent component analysis (ICA), fisher linear discriminant analysis (FLD) and canonical correlation analysis (CCA) for achieving a more discriminate subspace for extracting tamper signatures from quantization and noise residue features. The evaluation of proposed residue features, the feature selection techniques and their subsequent fusion for copy-move tampering emulated on low bandwidth Internet video sequences, show a significant improvement in tamper detection accuracy with fusion formulation.
Original languageEnglish
Title of host publicationAdvanced Concepts for Intelligent Vision Systems: 12th International Conference, ACIVS 2010 Sydney, Australia, December 13-16, 2010 Proceedings, Part II
EditorsJacques Blanc-Talon, Don Bone, Wilfred Philips, Dan Popescu, Paul Scheunders
Place of PublicationBerlin, Germany
PublisherSpringer Verlag
Pages79-87
Number of pages9
Volume6475
ISBN (Print)9783642176906
DOIs
Publication statusPublished - 2010
EventACIVS 2010: 12th International Conference Advanced Concepts for Intelligent Vision Systems - Sydney, Australia
Duration: 13 Dec 201016 Dec 2010

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume6475
ISSN (Print)0302-9743

Conference

ConferenceACIVS 2010: 12th International Conference Advanced Concepts for Intelligent Vision Systems
CountryAustralia
CitySydney
Period13/12/1016/12/10

Fingerprint

Fusion reactions
Feature extraction
Independent component analysis
Discriminant analysis
Internet
Bandwidth

Cite this

Chetty, G., Goodwin, J., & Singh, M. (2010). Digital image tamper detection based on multimodal fusion of residue features. In J. Blanc-Talon, D. Bone, W. Philips, D. Popescu, & P. Scheunders (Eds.), Advanced Concepts for Intelligent Vision Systems: 12th International Conference, ACIVS 2010 Sydney, Australia, December 13-16, 2010 Proceedings, Part II (Vol. 6475, pp. 79-87). (Lecture Notes in Computer Science; Vol. 6475). Berlin, Germany: Springer Verlag. https://doi.org/10.1007/978-3-642-17691-3_8
Chetty, Girija ; Goodwin, Julian ; Singh, Monica. / Digital image tamper detection based on multimodal fusion of residue features. Advanced Concepts for Intelligent Vision Systems: 12th International Conference, ACIVS 2010 Sydney, Australia, December 13-16, 2010 Proceedings, Part II. editor / Jacques Blanc-Talon ; Don Bone ; Wilfred Philips ; Dan Popescu ; Paul Scheunders. Vol. 6475 Berlin, Germany : Springer Verlag, 2010. pp. 79-87 (Lecture Notes in Computer Science).
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abstract = "In this paper, we propose a novel formulation involving fusion of noise and quantization residue features for detecting tampering or forgery in video sequences. We reiterate the importance of feature selection techniques in conjunction with fusion to enhance the tamper detection accuracy. We examine three different feature selection techniques, the independent component analysis (ICA), fisher linear discriminant analysis (FLD) and canonical correlation analysis (CCA) for achieving a more discriminate subspace for extracting tamper signatures from quantization and noise residue features. The evaluation of proposed residue features, the feature selection techniques and their subsequent fusion for copy-move tampering emulated on low bandwidth Internet video sequences, show a significant improvement in tamper detection accuracy with fusion formulation.",
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Chetty, G, Goodwin, J & Singh, M 2010, Digital image tamper detection based on multimodal fusion of residue features. in J Blanc-Talon, D Bone, W Philips, D Popescu & P Scheunders (eds), Advanced Concepts for Intelligent Vision Systems: 12th International Conference, ACIVS 2010 Sydney, Australia, December 13-16, 2010 Proceedings, Part II. vol. 6475, Lecture Notes in Computer Science, vol. 6475, Springer Verlag, Berlin, Germany, pp. 79-87, ACIVS 2010: 12th International Conference Advanced Concepts for Intelligent Vision Systems, Sydney, Australia, 13/12/10. https://doi.org/10.1007/978-3-642-17691-3_8

Digital image tamper detection based on multimodal fusion of residue features. / Chetty, Girija; Goodwin, Julian; Singh, Monica.

Advanced Concepts for Intelligent Vision Systems: 12th International Conference, ACIVS 2010 Sydney, Australia, December 13-16, 2010 Proceedings, Part II. ed. / Jacques Blanc-Talon; Don Bone; Wilfred Philips; Dan Popescu; Paul Scheunders. Vol. 6475 Berlin, Germany : Springer Verlag, 2010. p. 79-87 (Lecture Notes in Computer Science; Vol. 6475).

Research output: A Conference proceeding or a Chapter in BookConference contribution

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AB - In this paper, we propose a novel formulation involving fusion of noise and quantization residue features for detecting tampering or forgery in video sequences. We reiterate the importance of feature selection techniques in conjunction with fusion to enhance the tamper detection accuracy. We examine three different feature selection techniques, the independent component analysis (ICA), fisher linear discriminant analysis (FLD) and canonical correlation analysis (CCA) for achieving a more discriminate subspace for extracting tamper signatures from quantization and noise residue features. The evaluation of proposed residue features, the feature selection techniques and their subsequent fusion for copy-move tampering emulated on low bandwidth Internet video sequences, show a significant improvement in tamper detection accuracy with fusion formulation.

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Chetty G, Goodwin J, Singh M. Digital image tamper detection based on multimodal fusion of residue features. In Blanc-Talon J, Bone D, Philips W, Popescu D, Scheunders P, editors, Advanced Concepts for Intelligent Vision Systems: 12th International Conference, ACIVS 2010 Sydney, Australia, December 13-16, 2010 Proceedings, Part II. Vol. 6475. Berlin, Germany: Springer Verlag. 2010. p. 79-87. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-642-17691-3_8