Splicing forgeries localization through the use of first digit features
- 1 December 2014
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE) in 2014 IEEE International Workshop on Information Forensics and Security (WIFS)
Abstract
One of the principal problems in image forensics is determining if a particular image is authentic or not and, if manipulated, to localize which parts have been altered. In fact, localization is basic within the process of image examination because it permits to link the modified zone with the corresponding image area and, above all, with the meaning of it. Forensic instruments dealing with copy-move manipulation quite always provides a localization map, but, on the contrary, only a few tools, devised to detect a splicing operation, are able to give information about localization too. In this paper, a method to distinguish and then localize a single and a double JPEG compression in portions of an image through the use of the DCT coefficients first digit features and employing a Support Vector Machine (SVM) classifier is proposed. Experimental results and a comparison with a state-of-the-art technique are provided to witness the performances offered by the proposed method in terms of forgery localization.Keywords
This publication has 10 references indexed in Scilit:
- Exposing photo manipulation with inconsistent shadowsACM Transactions on Graphics, 2013
- Information Forensics: An Overview of the First DecadeIEEE Access, 2013
- Copy-move forgery detection and localization by means of robust clustering with J-LinkageSignal Processing: Image Communication, 2013
- An Evaluation of Popular Copy-Move Forgery Detection ApproachesIEEE Transactions on Information Forensics and Security, 2012
- Digital image splicing detection based on Markov features in DCT and DWT domainPattern Recognition, 2012
- Discriminating multiple JPEG compression using first digit featuresPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2012
- Image Forgery Localization via Block-Grained Analysis of JPEG ArtifactsIEEE Transactions on Information Forensics and Security, 2012
- The 'Dresden Image Database' for benchmarking digital image forensicsPublished by Association for Computing Machinery (ACM) ,2010
- Fast, automatic and fine-grained tampered JPEG image detection via DCT coefficient analysisPattern Recognition, 2009
- Statistical Tools for Digital ForensicsLecture Notes in Computer Science, 2004