Отрывок: The major key-points for matching are recognized in the image. These key-points are usually chosen by ana- lyzing the edges, corners, blobs or even ridges. The first step of the finding the image key-points is to find the maximum and minimum pixels from all its neighbors. II) Key points localization The edges need to be eliminated. For this reason, a concept of a Harris corner detector is used. A 2×2 Hes- sian matrix (H) is used to compute the principal...
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dc.contributor.authorRajalakshmi, C.-
dc.contributor.authorGermanus, Al.M.-
dc.contributor.authorBalasubramanian, R.-
dc.date.accessioned2019-05-27 10:43:44-
dc.date.available2019-05-27 10:43:44-
dc.date.issued2019-04-
dc.identifierDspace\SGAU\20190524\77078ru
dc.identifier.citationRajalakshmi C, Alex MG, Balasubramanian R. Copy move forgery detection using key point localized super pixel based on texture features. Computer Optics 2019; 43(2): 270-276. DOI: 10.18287/2412-6179-2019-43-2-270-276.ru
dc.identifier.urihttps://dx.doi.org/10.18287/2412-6179-2019-43-2-270-276-
dc.identifier.urihttp://repo.ssau.ru/handle/Zhurnal-Komputernaya-optika/Copy-move-forgery-detection-using-key-point-localized-super-pixel-based-on-texture-features-77078-
dc.description.abstractThe most important barrier in the image forensic is to ensue a forgery detection method such can detect the copied region which sustains rotation, scaling reflection, compressing or all. Traditional SIFT method is not good enough to yield good result. Matching accuracy is not good. In order to improve the accuracy in copy move forgery detection, this paper suggests a forgery detection method especially for copy move attack using Key Point Localized Super Pixel (KLSP). The proposed approach harmonizes both Super Pixel Segmentation using Lazy Random Walk (LRW) and Scale Invariant Feature Transform (SIFT) based key point extraction. The experimental result indicates the proposed KLSP approach achieves better performance than the previous well known approaches.ru
dc.language.isoenru
dc.publisherНовая техникаru
dc.relation.ispartofseries43;2-
dc.subjectcopy moveru
dc.subjectsegmentationru
dc.subjectSIFTru
dc.subjectKLSPru
dc.titleCopy move forgery detection using key point localized super pixel based on texture featuresru
dc.typeArticleru
dc.textpartThe major key-points for matching are recognized in the image. These key-points are usually chosen by ana- lyzing the edges, corners, blobs or even ridges. The first step of the finding the image key-points is to find the maximum and minimum pixels from all its neighbors. II) Key points localization The edges need to be eliminated. For this reason, a concept of a Harris corner detector is used. A 2×2 Hes- sian matrix (H) is used to compute the principal...-
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