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dc.contributorDepartment of Computingen_US
dc.creatorChan, Kin-sun-
dc.publisherHong Kong Polytechnic University-
dc.rightsAll rights reserveden_US
dc.titleImage forensics by detecting blurred regionsen_US
dcterms.abstractTo review and assay the genuineness of device-independent images, blur estimation by relative frequency and semantic features (BERFS) [1] is proposed. BERFS system is a tool that can detect the correctness of forged images. It introduces the concept of relative frequency feature which can show the difference between the blurred region and non-blurred region. It is claimed that estimation of blurred regions can be made with high precisions [1]. In this project, a detail investigation is carried out to understand how BERFS system can work well on the forged images. Parameter analysis is a main focus of this study. In the BERFS system, there exist several input parameters and our objective is to analyze their sensitivity to the overall performance. Besides, the semantic features contained in the image are investigated. Although there are some suggested methods to select the regions that contain similar semantic regions [1] , they are still estimation based and it is possible that some selected regions contain different semantic regions. If the size of blur region increases, the performance of BERFS may be changed also. In addition, we evaluate the image content that will affect the performance of image forensics based on BERFS. Experiments were conducted to evaluate the BERFS system with respect to the concerns stated above and the results shield light on fine tuning the BERFS method.en_US
dcterms.extentix, 85 leaves : ill. ; 30 cm.en_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.educationalLevelAll Masteren_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.LCSHImage analysis.en_US
dcterms.LCSHImage processing -- Digital techniquesen_US
dcterms.LCSHPattern recognition systems -- Mathematical models.en_US
dcterms.accessRightsrestricted accessen_US

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Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/5646