Detection of Copy-Move Forgery Using DoGCode

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Özet

Copy-move forgery is performed as a part of an image is copied and moved to another region within the same image. For the detection of this type of forgery, usually, feature vectors of the image are created by dividing the image into sub-blocks. Then the feature vector of the region is compared with other regions in the image to reach a conclusion if they are matched. In this study, to determine the copy-move forgery, DoG Coding technique which is more resistant to changes in image brightness is used. Coded new image is formed with the help of this technique often preferred in the palmprint recognition systems and features are determined by dividing the image into sub-blocks. Block based region growing segmentation method have been developed to determine the size of the copied region. Proposed this new approach has been successfully applied on images in the CoMoFod dataset prepared by different scenarios.

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RDL Kalıcı Bağlantı (PID)
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AlanDeğerDil
dc.contributor.authorTürk, Salih
dc.contributor.authorBingöl, Ozkan
dc.contributor.authorUlutas, Guzin
dc.contributor.otherIEEE
dc.date.accessioned2026-10-22T10:26:14.681547473Z
dc.date.available2026-10-22T10:26:14.681547473Z
dc.date.issued2015
dc.description.abstractCopy-move forgery is performed as a part of an image is copied and moved to another region within the same image. For the detection of this type of forgery, usually, feature vectors of the image are created by dividing the image into sub-blocks. Then the feature vector of the region is compared with other regions in the image to reach a conclusion if they are matched. In this study, to determine the copy-move forgery, DoG Coding technique which is more resistant to changes in image brightness is used. Coded new image is formed with the help of this technique often preferred in the palmprint recognition systems and features are determined by dividing the image into sub-blocks. Block based region growing segmentation method have been developed to determine the size of the copied region. Proposed this new approach has been successfully applied on images in the CoMoFod dataset prepared by different scenarios.
dc.identifier.endpage2369
dc.identifier.isbn978-1-4673-7386-9
dc.identifier.issn2165-0608
dc.identifier.startpage2366
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/gumushane/15935
dc.identifier.wosWOS:000380500900574
dc.language.isotr
dc.publisherIEEE
dc.relation.conference23nd Signal Processing and Communications Applications Conference (SIU)
dc.relation.ispartof2015 23RD SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectCopy-Move Forgery
dc.subjectDoGCode
dc.subjectRegion Growing Segmentation
dc.subject.classificationEngineering, Electrical & Electronic
dc.subject.classificationTelecommunications
dc.subject.classificationEngineering
dc.titleDetection of Copy-Move Forgery Using DoGCode
dc.typeConference Object
dspace.entity.typePublication
rdl.citation.wos0
rdl.conference.dateMAY 16-19, 2015
rdl.conference.placeInonu Univ, Malatya, TURKEY
rdl.oa.statusclosed
rdl.source.indexWOS
rdl.wos.indexConference Proceedings Citation Index - Science (CPCI-S)