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dc.contributor.authorİncetaş, Mürsel Ozan
dc.contributor.authorDemirci, Recep
dc.contributor.authorYavuzcan, H. Güçlü
dc.date.accessioned2021-02-19T21:28:50Z
dc.date.available2021-02-19T21:28:50Z
dc.date.issued2019
dc.identifier.issn2147-1762
dc.identifier.issn2147-1762
dc.identifier.urihttps://app.trdizin.gov.tr/makale/TXpJME5EVXpNdz09
dc.identifier.urihttps://hdl.handle.net/20.500.12868/850
dc.description.abstractEdge detection is an important step in image processing. As edge is intensity variation with spatial coordinates, the similarities between neighboring pixels could be used for edge detection. It has been observed that the effective results could be attained by thresholding the homogeneity images generated by means of the similarity transformation. Nevertheless, the user-defined normalization coefficient in similarity transform stage seriously effects edge detection performance and it needs to be automatically selected for every particular image. In this study, a new approach in which the normalization coefficient is automatically determined has been presented. The automating process of the similarity transform has been performed according to the gray level values of the neighboring pixels. The gray level differences of the central pixel and other neighboring pixels have been used to determine the similarity coefficient. Subsequently, the binarization process of the homogeneity images obtained with proposed algorithm have been completed with different thresholding techniques. Additionally, the F-score of the proposed edge detection has been obtained with 200 images in the BSDS training dataset. The achieved F-score values have showed that the performance of automatic approach is quite high.en_US
dc.language.isoengen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBiyolojien_US
dc.subjectKimya, Analitiken_US
dc.subjectKimya, Uygulamalıen_US
dc.subjectKimya, İnorganik ve Nükleeren_US
dc.subjectKimya, Tıbbien_US
dc.subjectKimya, Organiken_US
dc.subjectMatematiken_US
dc.subjectFizik, Uygulamalıen_US
dc.subjectFizik, Atomik ve Moleküler Kimyaen_US
dc.subjectFizik, Katı Halen_US
dc.subjectFizik, Akışkanlar ve Plazmaen_US
dc.subjectFizik, Matematiken_US
dc.subjectFizik, Nükleeren_US
dc.subjectFizik, Partiküller ve Alanlaren_US
dc.subjectİstatistik ve Olasılıken_US
dc.subjectMimarlıken_US
dc.subjectBilgisayar Bilimleri, Yapay Zekaen_US
dc.subjectBilgisayar Bilimleri, Sibernitiken_US
dc.subjectBilgisayar Bilimleri, Donanım ve Mimarien_US
dc.subjectBilgisayar Bilimleri, Bilgi Sistemlerien_US
dc.subjectBilgisayar Bilimleri, Yazılım Mühendisliğien_US
dc.subjectBilgisayar Bilimleri, Teori ve Metotlaren_US
dc.subjectMühendislik, Kimyaen_US
dc.subjectİnşaat Mühendisliğien_US
dc.subjectMühendislik, Elektrik ve Elektroniken_US
dc.subjectEndüstri Mühendisliğien_US
dc.subjectİmalat Mühendisliğien_US
dc.subjectMühendislik, Makineen_US
dc.titleAutomatic color edge detection with similarity transformationen_US
dc.typearticleen_US
dc.contributor.departmentALKÜen_US
dc.contributor.institutionauthor0-belirlenecek
dc.identifier.volume32en_US
dc.identifier.issue2en_US
dc.identifier.startpage458en_US
dc.identifier.endpage469en_US
dc.relation.journalGazi University Journal of Scienceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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