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Digital Image Forgery Detection by Local Statistical Models

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3 Author(s)
Grim, J. ; Inst. of Inf. Theor. & Autom., Acad. of Sci. of the Czech Republic, Prague, Czech Republic ; Somol, P. ; Pudil, P.

We propose an application of local statistical models in the form of a locally estimated Gaussian mixture to image forgery detection. The estimated mixture is used to compute the so called log-likelihood transformation of the original image. We show that image manipulations of different type may be visible in a suitably designed log-likelihood image. Unlike other methods the forgery detection based on local statistical model is rather non-specific and suitable to emphasize various traces of possible image tampering without any prior information.

Published in:

Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2010 Sixth International Conference on

Date of Conference:

15-17 Oct. 2010

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