Edge detection using integrate and fire neuron model

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dc.contributor.authorİncetaş, Mürsel Ozan
dc.contributor.authorArslan, Rukiye Uzun
dc.date.accessioned2021-02-19T21:28:44Z
dc.date.available2021-02-19T21:28:44Z
dc.date.issued2019
dc.departmentALKÜ
dc.description.abstractEdge detection is one of the most basic stages of image processing and have been used in many areas. Its purpose is to determine the pixels formed the objects. Many researchers have aimed to determine objects' edges correctly, like as they are determined by the human eye. In this study, a new edge detection technique based on spiking neural network is proposed. The proposed model has a different receptor structure than the ones found in literature and also does not use gray level values of the pixels in the receptive field directly. Instead, it takes the gray level differences between the pixel in the center of the receptive field and others as input. The model is tested by using BSDS train dataset. Besides, the obtained results are compared with the results calculated by Canny edge detection method.
dc.identifier.doi10.19113/sdufenbed.570597
dc.identifier.endpage616en_US
dc.identifier.issn1300-7688
dc.identifier.issn1308-6529
dc.identifier.issue2en_US
dc.identifier.startpage611en_US
dc.identifier.urihttps://doi.org/10.19113/sdufenbed.570597
dc.identifier.urihttps://app.trdizin.gov.tr/makale/TXpZNE16UTRPQT09
dc.identifier.urihttps://hdl.handle.net/20.500.12868/776
dc.identifier.volume23en_US
dc.indekslendigikaynakTR-Dizin
dc.institutionauthor0-belirlenecek
dc.language.isoen
dc.relation.ispartofSüleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Eleman
dc.rightsinfo:eu-repo/semantics/openAccess
dc.titleEdge detection using integrate and fire neuron model
dc.typeArticle

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