Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/2011
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dc.contributor.authorTaşpınar, Samet-
dc.contributor.authorSencar, Hüsrev Taha-
dc.contributor.authorBayram, Sevinç-
dc.contributor.authorMemon, Nasir-
dc.date.accessioned2019-07-10T14:42:45Z
dc.date.available2019-07-10T14:42:45Z
dc.date.issued2017
dc.identifier.citationTaspinar, S., Sencar, H. T., Bayram, S., & Memon, N. (2017, September). Fast camera fingerprint matching in very large databases. In 2017 IEEE International Conference on Image Processing (ICIP) (pp. 4088-4092). IEEE.en_US
dc.identifier.isbn978-1-5090-2175-8
dc.identifier.issn1522-4880
dc.identifier.urihttps://ieeexplore.ieee.org/document/8297051/-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/2011-
dc.description24th IEEE International Conference on Image Processing (2017 : Beijing; China)
dc.description.abstractGiven a query image or video, or a known camera fingerprint, there is a lack of capabilities for fast identification of media, from a large repository of images and videos, that match the query fingerprint. This work introduces a new approach that improves the computation efficiency of pairwise camera fingerprint matching and incorporates group testing to make the search more effective. More specifically, we jointly leverage the individual strengths of composite fingerprints and fingerprint digests in a novel manner and design two methods that are superior to existing approaches. The results show that under very high-performance requirements, where the probability of correct identification is close to one with a false-positive rate of zero, the proposed search methods are 2-8 times faster than the state-of-art search methods.en_US
dc.description.sponsorshipThe Institute of Electrical and Electronics Engineers Signal Processing Society
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofIEEE International Conference on Image Processing ICIPen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectSensor noiseen_US
dc.subjectPRNU noiseen_US
dc.subjectcamera fingerprinten_US
dc.subjectcomposite fingerprinten_US
dc.subjectfingerprint digestsen_US
dc.titleFast camera fingerprint matching in very large databasesen_US
dc.typeConference Objecten_US
dc.departmentFaculties, Faculty of Engineering, Department of Computer Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümütr_TR
dc.identifier.startpage4088
dc.identifier.endpage4092
dc.authorid0000-0001-6910-6194-
dc.identifier.wosWOS:000428410704044en_US
dc.identifier.scopus2-s2.0-85045335199en_US
dc.institutionauthorSencar, Hüsrev Taha-
dc.identifier.doi10.1109/ICIP.2017.8297051-
dc.authorscopusid8616233200-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.scopusquality--
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairetypeConference Object-
item.cerifentitytypePublications-
item.languageiso639-1en-
crisitem.author.dept02.3. Department of Computer Engineering-
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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