Ship Classification Based On Co-Occurrence Matrix and Support Vector Machines

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dc.authorid0000-0003-1374-1417
dc.authorid0000-0002-8546-9662
dc.contributor.authorHanbay, Kazım
dc.contributor.authorÖzdemir, Taha Burak
dc.date.accessioned2026-01-21T11:33:44Z
dc.date.available2026-01-21T11:33:44Z
dc.date.issued2024
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractSynthetic aperture radar (SAR) is an important and efficient imaging technology. This system provides robust information for various applications such as ship detection, climate change, and agricultural land modeling. Ship detection and classification problem is an important object detection problem that involves difficulties. There are deep-learning-based studies to solve this problem. However, mathematical and statistical methods should be developed for ship classification applications. In this paper, gray-level co-occurrence matrix-based method is proposed. The gradient of the input SAR image was calculated using Gaussian derivative filters. The gradient magnitude was calculated with horizontal and vertical gradient information. Gray-level co-occurrence matrix was obtained using gradient magnitude. The meaningful features of the images were calculated by performing 4 different statistical calculations. Results on our SAR database reveal the proposed model's superior classification performance.
dc.identifier.citationHANBAY, K., ÖZDEMIR, T. B. (2024). Ship Classification Based On Co-Occurrence Matrix and Support Vector Machines. Electrica, 24(3),812-817. doi.org/10.5152/electrica.2024.24110
dc.identifier.endpage817
dc.identifier.issue3
dc.identifier.startpage812
dc.identifier.urihttps://hdl.handle.net/11616/106350
dc.identifier.volume24
dc.language.isoen
dc.publisherİnönü Üniversitesi
dc.relation.ispartofElectrica
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectImage processing
dc.subjectGradient
dc.subjectship classification
dc.titleShip Classification Based On Co-Occurrence Matrix and Support Vector Machines
dc.typeArticle

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