Edge detection of aerial images using artificial bee colony algorithm

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dc.authorid0000-0002-3645-3445
dc.authorid0000-0002-3645-3445en_US
dc.contributor.authorYelmenoğlu, Elif Denizen_US
dc.contributor.authorAkhan Baykan, Nurdanen_US
dc.date.accessioned2022-10-19T14:35:39Z
dc.date.available2022-10-19T14:35:39Z
dc.date.issued2022-06-30
dc.departmentIşık Üniversitesi, İktisadi, İdari ve Sosyal Bilimler Fakültesi, Enformasyon Teknolojileri Bölümüen_US
dc.departmentIşık University, Faculty of Economics, Administrative and Social Sciences, Department of Information Technologiesen_US
dc.description.abstractEdge detection techniques are the one of the best popular and significant implementation areas of the image processing. Moreover, image processing is very widely used in so many fields. Therefore, lots of methods are used in the development and the developed studies provide a variety of solutions to problems of computer vision systems. In many studies, metaheuristic algorithms have been used for obtaining better results. In this paper, aerial images are used for edge information extraction by using Artificial Bee Colony (ABC) Optimization Algorithm. Procedures were performed on gray scale aerial images which are taken from RADIUS/DARPA-IU Fort Hood database. Initially bee colony size was specified according to sizes of images. Then a threshold value was set for each image, which related with images’ standard deviation of gray scale values. After the bees were distributed, fitness values and probability values were computed according to gray scale value. While appropriate pixels were specified, the other ones were being abandoned and labeled as banned pixels therefore bees never located on these pixels again. So the edges were found without the need to examine all pixels in the image. Our improved method’s results are compared with other results found in the literature according to detection error and similarity calculations’. All the experimental results show that ABC can be used for obtaining edge information from images.en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationYelmenoğlu, E. D. & Akhan Baykan, N. (2022). Edge detection of aerial images using artificial bee colony algorithm. MANAS Journal of Engineering, 10(1), 73-80. doi:10.51354/mjen.1053446en_US
dc.identifier.endpage80
dc.identifier.issn1694-7398en_US
dc.identifier.issue1
dc.identifier.startpage73
dc.identifier.urihttps://hdl.handle.net/11729/5038
dc.identifier.urihttp://dx.doi.org/10.51354/mjen.1053446
dc.identifier.urihttps://search.trdizin.gov.tr/yayin/detay/1138766
dc.identifier.volume10
dc.indekslendigikaynakTR-Dizinen_US
dc.institutionauthorYelmenoğlu, Elif Denizen_US
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherKırgızistan Türkiye Manas Üniversitesien_US
dc.relation.ispartofMANAS Journal of Engineeringen_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectImage processingen_US
dc.subjectEdge detectionen_US
dc.subjectArtificial bee colony optimizationen_US
dc.subjectAerial imagesen_US
dc.titleEdge detection of aerial images using artificial bee colony algorithmen_US
dc.typeArticleen_US

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