Detecting the presence of ENF signal in digital videos: A superpixel-based approach
dc.contributor.author | Memon, Nasir | |
dc.contributor.buuauthor | Vatansever, Saffet | |
dc.contributor.buuauthor | Dirik, Ahmet Emir | |
dc.contributor.department | Uludağ Üniversitesi/Mühendislik Fakültesi/Bilgisayar Mühendisliği Bölümü. | tr_TR |
dc.contributor.orcid | 0000-0002-6200-1717 | tr_TR |
dc.contributor.researcherid | K-6977-2012 | tr_TR |
dc.contributor.scopusid | 57190736821 | tr_TR |
dc.contributor.scopusid | 23033658100 | tr_TR |
dc.date.accessioned | 2023-01-02T06:30:19Z | |
dc.date.available | 2023-01-02T06:30:19Z | |
dc.date.issued | 2017-10 | |
dc.description.abstract | Electrical 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.sponsorship | United States Department of Defense Defense Advanced Research Projects Agency (DARPA) | en_US |
dc.description.sponsorship | Air Force Research Laboratory - FA8750-16-2-0173 | en_US |
dc.identifier.citation | Vatansever, S. vd. (2017). ''Detecting the presence of ENF signal in digital videos: A superpixel-based approach''. IEEE Signal Processing Letters, 24(10), 1463-1467. | en_US |
dc.identifier.endpage | 1467 | tr_TR |
dc.identifier.issn | 1070-9908 | |
dc.identifier.issue | 10 | tr_TR |
dc.identifier.scopus | 2-s2.0-85028499689 | tr_TR |
dc.identifier.startpage | 1463 | tr_TR |
dc.identifier.uri | https://doi.org/10.1109/LSP.2017.2741440 | |
dc.identifier.uri | https://ieeexplore.ieee.org/document/8012515 | |
dc.identifier.uri | 1558-2361 | |
dc.identifier.uri | http://hdl.handle.net/11452/30209 | |
dc.identifier.volume | 24 | tr_TR |
dc.identifier.wos | 000408775600003 | tr_TR |
dc.indexed.scopus | Scopus | en_US |
dc.indexed.wos | SCIE | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.relation.collaboration | Yurt dışı | tr_TR |
dc.relation.collaboration | Yurt içi | tr_TR |
dc.relation.journal | IEEE Signal Processing Letters | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi | tr_TR |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Engineering | en_US |
dc.subject | Electrical network frequency (ENF) | en_US |
dc.subject | ENF detection | en_US |
dc.subject | Multimedia forensics | en_US |
dc.subject | Superpixel | en_US |
dc.subject | Video forensics | en_US |
dc.subject | Electric-network frequency | en_US |
dc.subject | Audio | en_US |
dc.subject | Forensics | en_US |
dc.subject | Criterion | en_US |
dc.subject | Cameras | en_US |
dc.subject | Electric network analysis | en_US |
dc.subject | Electric network parameters | en_US |
dc.subject | Estimation | en_US |
dc.subject | Frequency estimation | en_US |
dc.subject | Light sources | en_US |
dc.subject | Lighting | en_US |
dc.subject | Multimedia systems | en_US |
dc.subject | Pixels | en_US |
dc.subject | Signal detection | en_US |
dc.subject | Video recording | en_US |
dc.subject | Circuit theory | en_US |
dc.subject | Forensics | en_US |
dc.subject | Multimedia forensics | en_US |
dc.subject | Network frequency | en_US |
dc.subject | Super pixels | en_US |
dc.subject | Time frequency analysis | en_US |
dc.subject | Video forensics | en_US |
dc.subject | Videos | en_US |
dc.subject | Computer graphics | en_US |
dc.subject | Luminance | en_US |
dc.subject.scopus | Circuit Theory; Audio Recordings; Forensic Science | en_US |
dc.subject.wos | Engineering, electrical & electronic | en_US |
dc.title | Detecting the presence of ENF signal in digital videos: A superpixel-based approach | en_US |
dc.type | Article | |
dc.wos.quartile | Q2 | en_US |