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Volume: 32 | Article ID: art00008
Semi-Blind Image Resampling Factor Estimation for PRNU Computation
  DOI :  10.2352/ISSN.2470-1173.2020.4.MWSF-077  Published OnlineJanuary 2020

Camera sensor fingerprints for digital camera forensics are formed by Photo-Response Non-Uniformity (PRNU), or more precisely, by estimating PRNU from a set of images taken with a camera. These images must be aligned with each other to establish sensor location pixel-to-pixel correspondence. If some of these images have been resized and cropped, the transformations need to be reversed. In this work we deal with estimation of resizing factor in the presence of one reference image from the same camera. For this problem we coin the term semi-blind estimation of resizing factor. We post two requirements that any solution of this problem should meet. It needs to be reasonably fast and exhibit very low estimation error. Our work shows that this problem can be solved using established image matching in Fourier-Mellin transform applied to vertical and horizontal projections of noise residuals (also called linear patterns).

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Morteza Darvish Morshedi Hosseini, Miroslav Goljan, Hui Zeng, "Semi-Blind Image Resampling Factor Estimation for PRNU Computationin Proc. IS&T Int’l. Symp. on Electronic Imaging: Media Watermarking, Security, and Forensics,  2020,  pp 77-1 - 77-11,

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