SEAM CARVING BASED IMAGE RESIZING DETECTION USING HYBRID FEATURES

Basit Öğe Kaydı
dc.contributor.authorŞentürk, Zehra Karapınar
dc.contributor.authorAkgün, Devrim
dc.date.accessioned2020-04-30T23:31:47Z
dc.date.available2020-04-30T23:31:47Z
dc.date.issued2017
dc.departmentDÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.descriptionWOS: 000417121700023en_US
dc.description.abstractDetection of seam carving-based digital image resizing is a challenging task in image processing field since the method investigates the images on hand semantically. Resizing with seam carving is realized by inserting or removing relatively unimportant pixel paths to/from the images and so the changes in image content are mostly unnoticeable. Local Binary Patterns (LBP), a visual descriptor, unearths local changes in image texture. Therefore, using LBP transform of the images besides intensity values contributes to the detection ratio. In this paper, we proposed a hybrid detection mechanism for more accurate seam carving detection especially in low scaling ratios. We extracted LBP-based and non-LBP based features and trained a Support Vector Machine (SVM) with sixty features. We achieved approximately 9 % improvement in low detection ratios. The experimental results show that more satisfactory detection ratios can be obtained by the proposed hybrid approach.en_US
dc.description.sponsorshipSakarya UniversitySakarya University [2015-50-02-019]en_US
dc.description.sponsorshipThis work was supported by Research Fund of the Sakarya University. Project Number: 2015-50-02-019en_US
dc.identifier.doi10.17559/TV-20160804121351en_US
dc.identifier.endpage1832en_US
dc.identifier.issn1330-3651
dc.identifier.issn1848-6339
dc.identifier.issue6en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage1825en_US
dc.identifier.urihttps://doi.org/10.17559/TV-20160804121351
dc.identifier.urihttps://hdl.handle.net/20.500.12684/4471
dc.identifier.volume24en_US
dc.identifier.wosWOS:000417121700023en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherUniv Osijek, Tech Facen_US
dc.relation.ispartofTehnicki Vjesnik-Technical Gazetteen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectforgery detectionen_US
dc.subjectLocal Binary Patternsen_US
dc.subjectseam carvingen_US
dc.subjectSupport Vector Machinesen_US
dc.titleSEAM CARVING BASED IMAGE RESIZING DETECTION USING HYBRID FEATURESen_US
dc.typeArticleen_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim
İsim:
4471.pdf
Boyut:
1.25 MB
Biçim:
Adobe Portable Document Format
Açıklama:
Tam Metin / Full Text
İndir

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Makale Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu