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Automatic Detection of Demosaicing Image Artifacts and Its Use in Tampering Detection

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

Even novice people can nowadays do convincing forged images. However, most forgeries alter the underlying statistics of the image, and in particular the slight artifacts caused by the demosaicing method. Demosaicing transforms the undersampled image acquired by the CFA into a three channel color image. Two problems arise: The first one is to identify the underlying CFA configuration, which classifies pixels according to whether they acquired a red, green or blue value. The second one is to detect anomalies in the regularity of the "demosaicing artifacts" that may reveal tampered image regions. We review the state of the art of detection methods, but point out that none of the proposed methods yields guaranteed detections for the CFA configuration or for the tampered areas. The methods generally yield an output that must still be evaluated visually. We therefore introduce an a contrario method that yields guaranteed detections, namely detections with a very low number of false alarms (NFA). Obtaining such an NFA is a useful complement to existing detection methods and should enable these methods to be included into automatic image evaluation processes. © 2018 IEEE.
Original languageEnglish
Title of host publicationProceedings - IEEE 1st Conference on Multimedia Information Processing and Retrieval, MIPR 2018
PublisherIEEE
Pages424-429
ISBN (Print)9781538618578
DOIs
Publication statusPublished - 26 Jun 2018
Externally publishedYes
Event1st IEEE Conference on Multimedia Information Processing and Retrieval, MIPR 2018 - Miami, United States
Duration: 10 Apr 2018 → 12 Apr 2018

Publication series

NameProceedings - IEEE 1st Conference on Multimedia Information Processing and Retrieval, MIPR 2018

Conference

Conference1st IEEE Conference on Multimedia Information Processing and Retrieval, MIPR 2018
PlaceUnited States
CityMiami
Period10/04/18 → 12/04/18

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

  • a contrario
  • artifact detection
  • Bayer matrix
  • CFA interpolation
  • color filter array
  • demosaicing
  • demosaicking
  • filter estimation
  • forgery
  • forgery detection
  • image forgery
  • linear estimation
  • tampering

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