Image segmentation using color and texture features

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dc.contributor.authorĂ–zden, Mustafa
dc.contributor.authorPolat, Ediz
dc.date.accessioned2020-06-25T15:13:27Z
dc.date.available2020-06-25T15:13:27Z
dc.date.issued2005
dc.departmentKırıkkale Üniversitesi
dc.descriptionEuropean Association for Signal Processing (EURASIP);KAREL;TUBITAK;NORTEL Networks - Business Without Boundaries;ARGELA Technologies
dc.description13th European Signal Processing Conference, EUSIPCO 2005 -- 4 September 2005 through 8 September 2005 -- Antalya -- 91025
dc.description.abstractThis paper describes a new color image segmentation method based on low-level features including color, texture and spatial information. The mean-shift algorithm with color and spatial information in color image segmentation is in general successful, however, in some cases, the color and spatial information are not sufficient for superior segmentation. The proposed method addresses this problem and employs texture as an additional feature. The method uses wavelet frames that provide translation invariant texture analysis. The method integrates additional texture feature to the color and spatial space of standard mean shift segmentation algorithm. The new algorithm with high dimensional extended feature space provides better results than standard mean shift segmentation algorithm as shown in experimental results.en_US
dc.identifier.citationclosedAccessen_US
dc.identifier.endpage2229en_US
dc.identifier.isbn1604238216; 9781604238211
dc.identifier.scopus2-s2.0-84863706758
dc.identifier.scopusqualityN/A
dc.identifier.startpage2226en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12587/1802
dc.indekslendigikaynakScopus
dc.language.isoen
dc.relation.ispartof13th European Signal Processing Conference, EUSIPCO 2005
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titleImage segmentation using color and texture featuresen_US
dc.typeConference Object

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