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Diyala Journal for Pure Science

Scientific Refereed Journal Published By College of Science - University of Diyala


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Diyala Journal for Pure Science DJPS


P- ISSN:2222-8373, E-ISSN:2518-9255

Volume 15, Issue 3 , July . 2019





Satellite Images Scene Classification Based Support Vector Machines and K-Nearest Neighbor


Ghaidaa Waleed Naji  , Jamal Mustafa Al -Tuwaijari


Year: 2019, Volume: 15, Issue: 3


Pages: 70-87 , DOI: https://dx.doi.org/10.24237/djps.15.03.486B


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Satellite image classification is a valuable technique for producing worthy information. This paper deal with high-resolution satellite for scene classification. In this research presents three algorithms were used to extract the features which are local binary patterns, gray level co-occurrence matrix, and color histogram features. The classification process included the use of two types of data mining techniques belongs to supervisor classification which are support vector machines, and k-nearest neighbor. Test results explain that the proposed classification method obtains a very auspicious performance.


Keywords: Supervised Classification, Satellite Images, Feature Extraction, GLCM, LBP, SVM, KNN.

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