Using noise inconsistencies for blind image forensics
Result description
A commonly used tool to conceal the traces of tampering is the addition of locally random noise to the altered image regions. The noise degradation is the main cause of failure of many active or passive image forgery detection methods. The amount of noise is uniform across the entire authentic image. Adding locally random noise may cause inconsistencies in the image?s noise. Therefore, the detection of various noise levels in an image may signify tampering. In this paper, we propose a novel method capable of dividing an investigated image into various partitions with homogenous noise levels. In other words, we introduce a segmentation method detecting changes in noise level. We assume the additive white Gaussian noise. Several examples are shown to demonstrate the proposed method?s output. An extensive quantitative measure of the efficiency of the noise estimation part as a function of different noise standard deviations, region sizes and various JPEG compression qualities is proposed
Keywords
Image forensicsDigital forgeryImage tamperingImage segmentation
The result's identifiers
Result code in IS VaVaI
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Using noise inconsistencies for blind image forensics
Original language description
A commonly used tool to conceal the traces of tampering is the addition of locally random noise to the altered image regions. The noise degradation is the main cause of failure of many active or passive image forgery detection methods. The amount of noise is uniform across the entire authentic image. Adding locally random noise may cause inconsistencies in the image?s noise. Therefore, the detection of various noise levels in an image may signify tampering. In this paper, we propose a novel method capable of dividing an investigated image into various partitions with homogenous noise levels. In other words, we introduce a segmentation method detecting changes in noise level. We assume the additive white Gaussian noise. Several examples are shown to demonstrate the proposed method?s output. An extensive quantitative measure of the efficiency of the noise estimation part as a function of different noise standard deviations, region sizes and various JPEG compression qualities is proposed
Czech name
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Czech description
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Classification
Type
Jx - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
GA102/08/0470: Detection of digital image forgeries by passive-blind image authentication
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Image and Vision Computing
ISSN
0262-8856
e-ISSN
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Volume of the periodical
27
Issue of the periodical within the volume
10
Country of publishing house
US - UNITED STATES
Number of pages
8
Pages from-to
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UT code for WoS article
000268403800008
EID of the result in the Scopus database
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Basic information
Result type
Jx - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP
IN - Informatics
Year of implementation
2009