Reliable demosaicing detection for image forensics

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Visually plausible image forgeries are easy to create even without particular knowledge or skills. However, most forgeries unknowingly alter the underlying statistics of an image. In particular, demosaicing artefacts created by the camera are usually destroyed or modified when the image is tampered. Most of the literature focus on detecting where these traces are destroyed, and generally do it in a way that still requires a visual interpretation. We introduce an a contrario method which detects global demosaicing parameters, and then checks for regions of the image which are inconsistent with these parameters. Detections are guaranteed in the form of a number of false alarms (NFA), which enables the user to control the false positive rate. Such a guarantee is a useful complement to existing methods, and enables inclusion into fully automatic image authentication processes. The source code and an online demo are provided with the article.

Original languageEnglish
Title of host publicationEUSIPCO 2019 - 27th European Signal Processing Conference
PublisherEuropean Signal Processing Conference, EUSIPCO
ISBN (Electronic)9789082797039
DOIs
Publication statusPublished - 1 Sept 2019
Externally publishedYes
Event27th European Signal Processing Conference, EUSIPCO 2019 - A Coruna, Spain
Duration: 2 Sept 20196 Sept 2019

Publication series

NameEuropean Signal Processing Conference
Volume2019-September
ISSN (Print)2219-5491

Conference

Conference27th European Signal Processing Conference, EUSIPCO 2019
Country/TerritorySpain
CityA Coruna
Period2/09/196/09/19

Keywords

  • A contrario
  • Artefact detection
  • Bayer matrix
  • CFA
  • CFA interpolation
  • Color filter array
  • Demosaicing
  • Demosaicking
  • Filter estimation
  • Forgery
  • Forgery detection
  • Image forgery
  • Linear estimation
  • Tampering

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