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Moment feature based forensic detection of resampled digital images

  • Xi'an Jiaotong University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

20 Scopus citations

Abstract

Forensic detection of resampled digital images has become an important technology among many others to establish the integrity of digital visual content. This paper proposes a moment feature based method to detect resampled digital images. Rather than concentrating on the positions of characteristic resampling peaks, we utilize a moment feature to exploit the periodic interpolation characteristics in the frequency domain. Not only the positions of resampling peaks but also the amplitude distribution is taken into consideration. With the extracted moment feature, a trained SVM classifier is used to detect resampled digital images. Extensive experimental results show the validity and efficiency of the proposed method.

Original languageEnglish
Title of host publicationMM 2013 - Proceedings of the 2013 ACM Multimedia Conference
Pages569-572
Number of pages4
DOIs
StatePublished - 2013
Event21st ACM International Conference on Multimedia, MM 2013 - Barcelona, Spain
Duration: 21 Oct 2013 → 25 Oct 2013

Publication series

NameMM 2013 - Proceedings of the 2013 ACM Multimedia Conference

Conference

Conference21st ACM International Conference on Multimedia, MM 2013
Country/TerritorySpain
CityBarcelona
Period21/10/13 → 25/10/13

Keywords

  • Digital forensic
  • Moment feature
  • Resampling detection

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