Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/3401
DC FieldValueLanguage
dc.contributor.advisorDagher, Issamen_US
dc.contributor.authorSaliba, Caroleen_US
dc.contributor.authorShahin, Eliasen_US
dc.date.accessioned2020-12-23T14:35:49Z-
dc.date.available2020-12-23T14:35:49Z-
dc.date.issued2015-
dc.identifier.urihttps://scholarhub.balamand.edu.lb/handle/uob/3401-
dc.descriptionIncludes bibliographical references (p.29-31).en_US
dc.descriptionSupervised by Dr. Issam Dagher.en_US
dc.description.abstractAdvance in technology and editing tools yields to easy manipulation in images. Nowadays, digital images usage is very common thus the importance of detection of forgeries to assure the authenticity of images. Since image tampering are hard to be noticed by the human eye, authenticity of an unknown source image is nearly impossible to detect. Copymove forgery is a very common type of digital image forgery where a part of an image is copied and pasted in another part in the same image for the purpose of hiding or adding something to the image. This paper deals with this type of forgeries and presents several detection methods such as SIFT and SURF. The offered detection is robust to rotating, scaling, horizontal and vertical translation and noise. Moreover, our algorithm can deal with multiple cloning cases. On the whole, the methods presented in this paper proved to be efficient with a rate of 99.53% (for SIFT) and 97.77% (for SURF) for a random set used in [11] of 220 images. Index terms: forgery, SIFT, detector, copy-move, authenticity, feature, matching, clusters.en_US
dc.description.statementofresponsibilityby Carole Saliba, Elias Shahinen_US
dc.format.extentx, 48 p. :ill., tables ;30 cmen_US
dc.language.isoengen_US
dc.rightsThis object is protected by copyright, and is made available here for research and educational purposes. Permission to reuse, publish, or reproduce the object beyond the personal and educational use exceptions must be obtained from the copyright holderen_US
dc.subject.lcshDigital images--Forgeryen_US
dc.titleAn improved copy-move forgery detection algorithmen_US
dc.typeProjecten_US
dc.contributor.departmentDepartment of Electrical Engineeringen_US
dc.contributor.facultyFaculty of Engineeringen_US
dc.contributor.institutionUniversity of Balamanden_US
dc.date.catalogued2016-01-15-
dc.description.degreeMS in Electrical Engineeringen_US
dc.description.statusPublisheden_US
dc.identifier.ezproxyURLhttp://ezsecureaccess.balamand.edu.lb/login?url=http://olib.balamand.edu.lb/projects_and_theses/GP-EE-182.pdfen_US
dc.identifier.OlibID164817-
dc.provenance.recordsourceOliben_US
Appears in Collections:UOB Theses and Projects
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