Genetic Algorithm Based Tree Segmentation

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dc.authoridTalu, Muhammed Fatih/0000-0003-1166-8404
dc.authorwosidALTUN GÜVEN, SARA/ABB-9670-2020
dc.authorwosidYeroglu, Celaleddin/ABG-9572-2020
dc.authorwosidTalu, Muhammed Fatih/W-2834-2017
dc.contributor.authorVarjovi, Mahdi Hatami
dc.contributor.authorAltun, Sara
dc.contributor.authorTalu, Muhammed Fatih
dc.contributor.authorYeroglu, Celaleddin
dc.date.accessioned2024-08-04T20:45:50Z
dc.date.available2024-08-04T20:45:50Z
dc.date.issued2018
dc.departmentİnönü Üniversitesien_US
dc.descriptionInternational Conference on Artificial Intelligence and Data Processing (IDAP) -- SEP 28-30, 2018 -- Inonu Univ, Malatya, TURKEYen_US
dc.description.abstractSegmentation of tree images are used in agricultural applications such as harvest estimation. The accuracy of the segmentation process influences the success of such applications. Many methods are used for image segmentation such as thresholding, clustering, edge-based, region-based methods. The region growing algorithm is a very robust and easy to implement method, but the disadvantage of this method is that the threshold value is sensitive to critical and environmental noise. In this study, it is aimed to increase the segmentation quality of tree images. In tree segmentation; the optimum threshold values differ because of the camera's characteristics, the amount of light, the color of the leaf, the type of the fruity, the shadow of the branches and the other greens on the background. The starting point is automatically optimized with the help of genetic algorithms for the threshold values used in the determined region growing method.en_US
dc.description.sponsorshipInonu Univ, Comp Sci Dept,IEEE Turkey Sect,Anatolian Scien_US
dc.identifier.isbn978-1-5386-6878-8
dc.identifier.scopus2-s2.0-85062546576en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://hdl.handle.net/11616/98702
dc.identifier.wosWOS:000458717400100en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherIeeeen_US
dc.relation.ispartof2018 International Conference on Artificial Intelligence and Data Processing (Idap)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectsegmentationen_US
dc.subjectthresholden_US
dc.subjectregion growingen_US
dc.subjectgenetic algorithmen_US
dc.titleGenetic Algorithm Based Tree Segmentationen_US
dc.typeConference Objecten_US

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