Edge detection method driven by knowledge-based neighborhood rules

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dc.authorid0000-0002-2126-8757en_US
dc.authorwosidGMC-3454-2022en_US
dc.contributor.authorÇapkan, Yavuz
dc.contributor.authorAltun, Halis
dc.contributor.authorFidan, Can Bülent
dc.date.accessioned2022-12-16T13:18:30Z
dc.date.available2022-12-16T13:18:30Z
dc.date.issued2023en_US
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Yazılım Mühendisliği Bölümüen_US
dc.description.abstractEdge detection is a fundamental process, and therefore there are still demands to improve its efficiency and computational complexity. This study proposes a knowledge-based edge detection method to meet this requirement by introducing a set of knowledge-based rules. The methodology to derive the rules is based on the observed continuity properties and the neighborhood characteristics of the edge pixels, which are expressed as simple arithmetical operations to improve computational complexity. The results show that the method has an advantage over the gradient-based methods in terms of performance and computational load. It is appropriately four times faster than Canny method and shows superior performance compared to the gradient-based methods in general. Furthermore, the proposed method provides robustness to effectively identify edges at the corners. Due to its light computational requirement and inherent parallelization properties, the method would be also suitable for hardware implementation on field-programmable gate arrays (FPGA).en_US
dc.identifier.citationÇapkan, Y., Altun, H. & Fidan, C. B. (2023). Edge detection method driven by knowledge-based neighborhood rules. International Journal of Engineering and Technology Innovation, 13(1), pp. 1-13. https://doi.org/10.46604/ijeti.2023.9710en_US
dc.identifier.doi10.46604/ijeti.2023.9710en_US
dc.identifier.endpage13en_US
dc.identifier.issn2223-5329
dc.identifier.issn2226-809X
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85144781114en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage1en_US
dc.identifier.urihttps://doi.org/10.46604/ijeti.2023.9710
dc.identifier.urihttps://hdl.handle.net/20.500.13055/332
dc.identifier.volume13en_US
dc.identifier.wosWOS:000809593400001en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynak.otherESCI - Emerging Sources Citation Indexen_US
dc.institutionauthorAltun, Halis
dc.language.isoenen_US
dc.publisherThe Taiwan Association of Engineering and Technology Innovation (TAETI)en_US
dc.relation.ispartofInternational Journal of Engineering and Technology Innovationen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectImage Processingen_US
dc.subjectEdge Detectionen_US
dc.subjectComputer Visionen_US
dc.subjectImage Analysisen_US
dc.titleEdge detection method driven by knowledge-based neighborhood rulesen_US
dc.typeArticleen_US
dspace.entity.typePublication

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