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BENFORD’S LAW IN IMAGE PROCESSING

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1928/20198

BENFORD’S LAW IN IMAGE PROCESSING

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dc.contributor.author Abdallah, Chaouki T.
dc.contributor.author Heileman, Greg L.
dc.contributor.author Perez-Gonzalez, Fernando
dc.date.accessioned 2012-03-23T23:27:22Z
dc.date.available 2012-03-23T23:27:22Z
dc.date.issued 2007-09-16
dc.identifier.citation IEEE International Conference on Image Processing, 2007. ICIP 2007: 405-408 en_US
dc.identifier.issn 1522-4880
dc.identifier.uri http://hdl.handle.net/1928/20198
dc.description Digital Object Identifier: 10.1109/ICIP.2007.4378977 en_US
dc.description.abstract We present a generalization of Benford’s law for the first significant digit. This generalization is based on keeping two terms of the Fourier expansion of the probability density function of the data in the modular logarithmic domain. We prove that images in the Discrete Cosine Transform domain closely follow this generalization. We use this property to propose an application in image steganalysis, namely, detecting that a given image carries a hidden message. en_US
dc.description.sponsorship IEEE en_US
dc.language.iso en_US en_US
dc.publisher IEEE en_US
dc.subject DCT en_US
dc.subject Fourier series en_US
dc.subject setaganalysis en_US
dc.title BENFORD’S LAW IN IMAGE PROCESSING en_US
dc.type Article en_US


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