Digital video tamper detection based on multimodal fusion of residue features

Monica Biswas, Girija Chetty, Rashmi Singh

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

13 Citations (Scopus)
2 Downloads (Pure)

Abstract

In this paper, we propose novel algorithmic models based on feature transformation in cross-modal subspace and their multimodal fusion for different types of residue features extracted from several intra-frame and interframe pixel sub-blocks in video sequences for detecting digital video tampering or forgery. An evaluation of proposed residue features - the noise residue features and the quantization features, their transformation in cross-modal subspace, and their multimodal fusion, for emulated copy-move tamper scenario shows a significant improvement in tamper detection accuracy as compared to single mode features without transformation in cross-modal subspace.

Original languageEnglish
Title of host publicationProceedings - 2010 4th International Conference on Network and System Security, NSS 2010
PublisherIEEE
Pages606-613
Number of pages8
ISBN (Print)9780769541594
Publication statusPublished - 1 Sep 2010
Externally publishedYes
Event4th International Conference on Network and System Security, NSS 2010 - Melbourne, VIC, Australia
Duration: 1 Sep 20103 Sep 2010

Conference

Conference4th International Conference on Network and System Security, NSS 2010
CountryAustralia
CityMelbourne, VIC
Period1/09/103/09/10

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Cite this

Biswas, M., Chetty, G., & Singh, R. (2010). Digital video tamper detection based on multimodal fusion of residue features. In Proceedings - 2010 4th International Conference on Network and System Security, NSS 2010 (pp. 606-613). [5635960] IEEE.