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RESEARCH PRODUCT
Copy–Move Forgery Detection by Matching Triangles of Keypoints
Edoardo ArdizzoneAlessandro BrunoGiuseppe Mazzolasubject
Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer Networks and CommunicationsComputer scienceDelaunay triangulationbusiness.industryFeature vectorSURFFeature extractionScale-invariant feature transformPattern recognitionDelaunay TriangulationDigital Image ForensicVisualizationVertex (geometry)Copy-move ForgeryDigital imageComputer Networks and CommunicationHarriSIFTComputer visionArtificial intelligenceSafety Risk Reliability and QualitybusinessCopy-move Forgery; Delaunay Triangulation; Digital Image Forensics; Harris; SIFT; SURF; Computer Networks and Communications; Safety Risk Reliability and QualityTransformation geometrydescription
Copy-move forgery is one of the most common types of tampering for digital images. Detection methods generally use block-matching approaches, which first divide the image into overlapping blocks and then extract and compare features to find similar ones, or point-based approaches, in which relevant keypoints are extracted and matched to each other to find similar areas. In this paper, we present a very novel hybrid approach, which compares triangles rather than blocks, or single points. Interest points are extracted from the image, and objects are modeled as a set of connected triangles built onto these points. Triangles are matched according to their shapes (inner angles), their content (color information), and the local feature vectors extracted onto the vertices of the triangles. Our methods are designed to be robust to geometric transformations. Results are compared with a state-of-the-art block matching method and a point-based method. Furthermore, our data set is available for use by academic researchers.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2015-09-01 | IEEE Transactions on Information Forensics and Security |