Back to articles
Articles
Volume: 29 | Article ID: art00017
Image
PRNU-based Image Manipulation Localization with Discriminative Random Fields
  DOI :  10.2352/ISSN.2470-1173.2017.7.MWSF-333  Published OnlineJanuary 2017
Abstract

We formulate PRNU-based image manipulation localization as a probabilistic binary labeling task in a flexible discriminative random field (DRF) framework. A novel local discriminator based on the deviation of the measured correlation from the expected local correlation as estimated by a correlation predictor is paired with an explicit pairwise model for dependencies between local decisions. Experimental results from the Dresden Image Database indicate that the DRF outperforms prior art with Markov random field label priors.

Subject Areas :
Views 13
Downloads 1
 articleview.views 13
 articleview.downloads 1
  Cite this article 

Sujoy Chakraborty, Matthias Kirchner, "PRNU-based Image Manipulation Localization with Discriminative Random Fieldsin Proc. IS&T Int’l. Symp. on Electronic Imaging: Media Watermarking, Security, and Forensics,  2017,  pp 113 - 120,  https://doi.org/10.2352/ISSN.2470-1173.2017.7.MWSF-333

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2017
72010604
Electronic Imaging
2470-1173
Society for Imaging Science and Technology