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

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).

Subject Areas :
Views 30
Downloads 6
 articleview.views 30
 articleview.downloads 6
  Cite this article 

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,  https://doi.org/10.2352/ISSN.2470-1173.2020.4.MWSF-077

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2020
72010604
Electronic Imaging
2470-1173
Society for Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151 USA