Publication:
The effect of inverse square law of light on enf in videos exposed by rolling shutter

dc.contributor.authorVatansever, Saffet
dc.contributor.authorDirik, Ahmet Emir
dc.contributor.authorMemon, Nasir
dc.contributor.buuauthorDİRİK, AHMET EMİR
dc.contributor.departmentMühendislik Fakültesi
dc.contributor.departmentBilgisayar Mühendisliği Bölümü
dc.contributor.orcid0000-0002-6200-1717
dc.contributor.researcheridKIK-4851-2024
dc.date.accessioned2024-10-14T07:46:24Z
dc.date.available2024-10-14T07:46:24Z
dc.date.issued2023-01-01
dc.description.abstractDue to a constant imbalance between demand and supply of power, ENF (Electric Network Frequency) fluctuates around a nominal value of 50 or 60 Hz. These variations in ENF cause the luminance intensity of a mains-powered light source, having no AC/DC converter inside, also to fluctuate. As a result, a video of a scene illuminated by a mains-powered light source can be used to estimate these fluctuations. As a consequence, the ENF signal within the time period when the video was captured can be estimated. This work explores the effects of frame rate harmonics that emerge when a rolling shutter based approach is used for ENF estimation from videos captured using CMOS cameras. These harmonics are a problem, especially for videos whose frame rate is a divisor of the nominal ENF because the frame rate harmonics and the ENF harmonics overlap. It is discovered that a key reason for the presence of the harmonics is the inverse square law of light that results in some repeating patterns of luminance variation across frames. This paper presents an analysis of the effect of the inverse square law of light on ENF estimation. A technique for refined ENF-related luminance signal estimation is proposed that attenuates these frame rate harmonics. This enables more accurate ENF estimates. The work also proposes an approach to estimate ENF-related luminance waveform cycles within each video frame, and a method to compute the confidence score for the estimated cycles. It provides insight into the reliability of the extracted ENF signal from a video, in the sense of its usefulness for ENF forensics, and consequently for ENF detection, which is an important precursor to ENF-based video forensics.
dc.description.sponsorshipUnited States Department of Defense Defense Advanced Research Projects Agency (DARPA)
dc.description.sponsorshipAir Force Research Laboratory - FA8750-16-2-0173
dc.identifier.doi10.1109/TIFS.2022.3220029
dc.identifier.endpage260
dc.identifier.issn1556-6013
dc.identifier.startpage248
dc.identifier.urihttps://doi.org/10.1109/TIFS.2022.3220029
dc.identifier.uri1556-6021
dc.identifier.urihttps://ieeexplore.ieee.org/document/9940312
dc.identifier.urihttps://hdl.handle.net/11452/46341
dc.identifier.volume18
dc.identifier.wos000905076700015
dc.indexed.wosWOS.SCI
dc.language.isoen
dc.publisherIEEE
dc.relation.journalIeee Transactions on Information Forensics and Security
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectElectric-network frequency
dc.subjectDigital videos
dc.subjectSignal
dc.subjectVideos
dc.subjectHarmonic analysis
dc.subjectEstimation
dc.subjectLight sources
dc.subjectCameras
dc.subjectForensics
dc.subjectFrequency estimation
dc.subjectEnf
dc.subjectElectric network frequency
dc.subjectVideo forensics
dc.subjectMultimedia forensics
dc.subjectCamera forensics
dc.subjectRolling shutter
dc.subjectIdle period
dc.subjectFrame rate harmonics
dc.subjectTime-of-recording
dc.subjectTime-stamp verification
dc.subjectScience & technology
dc.subjectTechnology
dc.subjectComputer science, theory & methods
dc.subjectEngineering, electrical & electronic
dc.subjectComputer science
dc.subjectEngineering
dc.titleThe effect of inverse square law of light on enf in videos exposed by rolling shutter
dc.typeArticle
dspace.entity.typePublication
local.contributor.departmentMühendislik Fakültesi/Bilgisayar Mühendisliği Bölümü
relation.isAuthorOfPublication37bb7eb8-5671-4304-8f09-5f48c51ec56f
relation.isAuthorOfPublication.latestForDiscovery37bb7eb8-5671-4304-8f09-5f48c51ec56f

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