A classifier design for detecting image manipulations

Ismail Avcibas, Sevinc Bayram, Nasir Memon, Mahalingam Ramkumar, Bulent Sankur

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper we present a framework for digital image forensics. Based on the assumptions that some processing operations must be done on the image before it is doctored, and an expected measurable distortion after processing an image, we design classifiers that discriminates between original and processed images. We propose a novel way of measuring the distortion between two images, one being the original and the other processed. The measurements are used as features in classifier design. Using these classifiers we test whether a suspicious part of a given image has been processed with a particular method or not. Experimental results show that with a high accuracy we are able to tell if some part of an image has undergone a particular or a combination of processing methods.

Original languageEnglish (US)
Title of host publication2004 International Conference on Image Processing, ICIP 2004
Pages2645-2648
Number of pages4
DOIs
StatePublished - 2004
Event2004 International Conference on Image Processing, ICIP 2004 - , Singapore
Duration: Oct 18 2004Oct 21 2004

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume4
ISSN (Print)1522-4880

Other

Other2004 International Conference on Image Processing, ICIP 2004
CountrySingapore
Period10/18/0410/21/04

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Avcibas, I., Bayram, S., Memon, N., Ramkumar, M., & Sankur, B. (2004). A classifier design for detecting image manipulations. In 2004 International Conference on Image Processing, ICIP 2004 (pp. 2645-2648). (Proceedings - International Conference on Image Processing, ICIP; Vol. 4). https://doi.org/10.1109/ICIP.2004.1421647