New local binary pattern approaches based on color channels in texture classification

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dc.authoridTekin, Ramazan/0000-0003-4325-6922
dc.contributor.authorTekin, Ramazan
dc.contributor.authorErtugrul, Omer Faruk
dc.contributor.authorKaya, Yilmaz
dc.date.accessioned2024-12-24T19:24:42Z
dc.date.available2024-12-24T19:24:42Z
dc.date.issued2020
dc.departmentSiirt Üniversitesi
dc.description.abstractIn this paper, four novel, simple and robust approaches, which are left to right local binary patterns (LBPLL2R), top to down local binary patterns (LBPT2D), cube surface local binary pattern (LBPSurfaces), and cube diagonal local binary pattern (LBPDiagonal), were proposed in order to exact texture features in color images. These approaches were based on the local binary pattern (LBP), which is an effective statistical texture descriptor and can be employed in gray images. Proposed approaches were evaluated and validated in four datasets, which are Outex, KTH_TIPS, KTH_TIPS2, and USPtex datasets. The images in these datasets are in RGB, HSV, YIQ, and YCbCr color formats. Achieved results by these approaches were compared with the obtained results by the classical LBP and literature findings. As a result, the proposed approaches performed better than the traditional LBP method and they found effective in the classification of color texture images, especially in images, which are in RGB and HSV formats. Furthermore, noise robustness and time complexity of the proposed approaches were validated.
dc.identifier.doi10.1007/s11042-020-09698-5
dc.identifier.endpage32561
dc.identifier.issn1380-7501
dc.identifier.issn1573-7721
dc.identifier.issue43-44
dc.identifier.scopus2-s2.0-85089967492
dc.identifier.scopusqualityQ1
dc.identifier.startpage32541
dc.identifier.urihttps://doi.org/10.1007/s11042-020-09698-5
dc.identifier.urihttps://hdl.handle.net/20.500.12604/6106
dc.identifier.volume79
dc.identifier.wosWOS:000563606600004
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofMultimedia Tools and Applications
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241222
dc.subjectLocal binary patterns
dc.subjectTexture classification
dc.subjectFeature extraction
dc.subjectImage classification
dc.titleNew local binary pattern approaches based on color channels in texture classification
dc.typeArticle

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