Detecting the Presence of ENF Signal in Digital Videos: A Superpixel-Based Approach

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dc.authorid0000-0002-4680-1263en_US
dc.contributor.authorVatansever, Saffet
dc.contributor.authorDirik, Ahmet Emir
dc.contributor.authorMemon, Nasir
dc.date.accessioned2021-03-20T20:13:42Z
dc.date.available2021-03-20T20:13:42Z
dc.date.issued2017
dc.departmentBTÜ, Mühendislik ve Doğa Bilimleri Fakültesi, Mekatronik Mühendisliği Bölümüen_US
dc.descriptionDirik, Ahmet/0000-0002-6200-1717en_US
dc.description.abstractElectrical network frequency (ENF) instantaneously fluctuates around its nominal value (50/60 Hz) due to a continuous disparity between generated power and consumed power. Consequently, luminous intensity of a mains-powered light source varies depending on ENF fluctuations in the grid network. Variations in the luminance over time can be captured from video recordings and ENF can be estimated through content analysis of these recordings. In ENF-based video forensics, it is critical to check whether a given video file is appropriate for this type of analysis. That is, if ENF signal is not present in a given video, it would be useless to apply ENF-based forensic analysis. In this letter, an ENF signal presence detection method is introduced for videos. The proposed method is based on multiple ENF signal estimations from steady super pixels, i.e., pixels that are most likely uniform in color, brightness, and texture, and intra-class similarity of the estimated signals. Subsequently, consistency among these estimates is then used to determine the presence or absence of an ENF signal in a given video. The proposed technique can operate on video clips as short as 2 min and is independent of the camera sensor type, i.e., CCD or CMOS.en_US
dc.description.sponsorshipDARPAUnited States Department of DefenseDefense Advanced Research Projects Agency (DARPA); Air Force Research Laboratory [FA8750-16-2-0173]en_US
dc.description.sponsorshipThis work was supported in part by the DARPA and in part by the Air Force Research Laboratory under Agreement FA8750-16-2-0173. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. V. Monga.en_US
dc.identifier.doi10.1109/LSP.2017.2741440en_US
dc.identifier.endpage1467en_US
dc.identifier.issn1070-9908
dc.identifier.issn1558-2361
dc.identifier.issue10en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage1463en_US
dc.identifier.urihttp://doi.org/10.1109/LSP.2017.2741440
dc.identifier.urihttps://hdl.handle.net/20.500.12885/923
dc.identifier.volume24en_US
dc.identifier.wosWOS:000408775600003en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorVatansever, Saffet
dc.language.isoenen_US
dc.publisherIeee-Inst Electrical Electronics Engineers Incen_US
dc.relation.ispartofIeee Signal Processing Lettersen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectElectrical network frequency (ENF)en_US
dc.subjectENF detectionen_US
dc.subjectmultimedia forensicsen_US
dc.subjectsuperpixelen_US
dc.subjectvideo forensicsen_US
dc.titleDetecting the Presence of ENF Signal in Digital Videos: A Superpixel-Based Approachen_US
dc.typeArticleen_US

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