Effects of Color Spaces and Distance Norms on Graph-Based Image Segmentation

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dc.contributor.authorSaglam, Ali
dc.contributor.authorBaykan, Nurdan Akhan
dc.date.accessioned2020-03-26T19:35:20Z
dc.date.available2020-03-26T19:35:20Z
dc.date.issued2017
dc.departmentSelçuk Üniversitesien_US
dc.description3rd International Conference on Frontiers of Signal Processing (ICFSP) -- SEP 06-08, 2017 -- Paris, FRANCEen_US
dc.description.abstractUse of the graph theory tools in image processing field is growing up with each passing day. Graph theory makes the operations easier for image processing applications, and can represent digital image components completely. In image segmentation processes, the graph theory tools are also used widely. These kinds of image segmentation processes are called graph-based image segmentation. In many image processing applications, it seems as a problem that which color space the color values of pixels should be considered according to and which distance norm should be used to measure the difference between two points in the space. In this work, a graph-based image segmentation algorithm is tested on several color spaces with different distance norms. The test is carried out on 100 real world images that take part in a general-purposed image segmentation dataset. The average segmentation results are given as F-measure in this work with regard to both color spaces and distance norms. The results show that L*a*b* and L*u*v* color spaces are more appropriate than RGB color space, in general. The squared Euclidean distance norm gives more accurate results than the Euclidean distance norm, used in the source paper, if the Gaussian smoothing is not used as pre-processing.en_US
dc.description.sponsorshipIEEEen_US
dc.description.sponsorshipSelcuk University OYP CoordinationSelcuk University [2016-OYP-061]en_US
dc.description.sponsorshipThis study was supported by Selcuk University OYP Coordination (Project No. 2016-OYP-061).en_US
dc.identifier.endpage135en_US
dc.identifier.isbn978-1-5386-1038-1
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage130en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/35035
dc.identifier.wosWOS:000425242400027en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2017 3RD INTERNATIONAL CONFERENCE ON FRONTIERS OF SIGNAL PROCESSING (ICFSP)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectcolor spacesen_US
dc.subjectdigital image processingen_US
dc.subjectdistance normsen_US
dc.subjectgraph-based segmentationen_US
dc.titleEffects of Color Spaces and Distance Norms on Graph-Based Image Segmentationen_US
dc.typeConference Objecten_US

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