Digital video tamper detection based on multimodal fusion of residue features

Monica Biswas; Girija Chetty; Rashmi Singh

Digital video tamper detection based on multimodal fusion of residue features

Monica Biswas, Girija Chetty, Rashmi Singh

Information Systems

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

24 Citations (Scopus)

76 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 language	English
Title of host publication	Proceedings - 2010 4th International Conference on Network and System Security, NSS 2010
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	606-613
Number of pages	8
ISBN (Print)	9780769541594
Publication status	Published - 1 Sept 2010
Event	4th International Conference on Network and System Security, NSS 2010 - Melbourne, VIC, Australia Duration: 1 Sept 2010 → 3 Sept 2010

Conference

Conference	4th International Conference on Network and System Security, NSS 2010
Country/Territory	Australia
City	Melbourne, VIC
Period	1/09/10 → 3/09/10

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title = "Digital video tamper detection based on multimodal fusion of residue features",

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.",

keywords = "Video analysis",

author = "Monica Biswas and Girija Chetty and Rashmi Singh",

year = "2010",

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pages = "606--613",

booktitle = "Proceedings - 2010 4th International Conference on Network and System Security, NSS 2010",

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note = "4th International Conference on Network and System Security, NSS 2010 ; Conference date: 01-09-2010 Through 03-09-2010",

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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., 5635960, IEEE, Institute of Electrical and Electronics Engineers, pp. 606-613, 4th International Conference on Network and System Security, NSS 2010, Melbourne, VIC, Australia, 1/09/10.

Digital video tamper detection based on multimodal fusion of residue features. / Biswas, Monica; Chetty, Girija; Singh, Rashmi.
Proceedings - 2010 4th International Conference on Network and System Security, NSS 2010. IEEE, Institute of Electrical and Electronics Engineers, 2010. p. 606-613 5635960.

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

TY - GEN

T1 - Digital video tamper detection based on multimodal fusion of residue features

AU - Biswas, Monica

AU - Chetty, Girija

AU - Singh, Rashmi

PY - 2010/9/1

Y1 - 2010/9/1

N2 - 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.

AB - 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.

KW - Video analysis

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M3 - Conference contribution

AN - SCOPUS:78650349641

SN - 9780769541594

SP - 606

EP - 613

BT - Proceedings - 2010 4th International Conference on Network and System Security, NSS 2010

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - 4th International Conference on Network and System Security, NSS 2010

Y2 - 1 September 2010 through 3 September 2010

ER -

Digital video tamper detection based on multimodal fusion of residue features

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