Dimension and color classification of olive fruit with image processing techniques

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dc.authorid0000-0002-3942-6442
dc.authorid0000-0002-2433-246X
dc.authorid0000-0002-5715-1040
dc.contributor.authorİnce, Fatma Betül Kınacı
dc.contributor.authorTaşdemir, Şakir
dc.contributor.authorÖzkan, İlker Ali
dc.date.accessioned2025-02-12T12:05:14Z
dc.date.available2025-02-12T12:05:14Z
dc.date.issued2020
dc.departmentSelçuk Üniversitesi, Teknoloji Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractThe development of image processing technology appears in agriculture as well as in many other fields. Various classifications are carried out for fruits and vegetables. These are processes such as determining the harvest time according to their degree of maturity, deciding the way of collection and performing packaging operations according to their dimension. This study aims to classify the fruit according to its intended use in order to benefit more from the olive fruit that is important in industrial terms. In this study, olive fruit is classified as big, medium, and small according to its dimensions. Also classified as black and green according to their colors. This classification process was made in MATLAB environment and the KNN algorithm and decision trees was used. The results are obtained with Euclid and Manhattan methods used with the KNN algorithm and are given comparatively. According to the application results, 100% success was achieved in both methods in color classification. In dimension classification, 89.2% classification success was achieved in KNN algorithm and 86.7% in decision tree method.
dc.identifier.citationİnce, F. B. K., Taşdemir, Ş., Özkan, İ. A. (2020). Dimension and color classification of olive fruit with image processing techniques. Selçuk-Teknik Dergisi, (Özel Sayı), 156-167.
dc.identifier.issn1302-6178
dc.identifier.issueÖzel Sayı
dc.identifier.urihttps://hdl.handle.net/20.500.12395/54367
dc.institutionauthorTaşdemir, Şakir
dc.institutionauthorÖzkan, İlker Ali
dc.institutionauthorid0000-0002-2433-246X
dc.institutionauthorid0000-0002-5715-1040
dc.language.isoen
dc.publisherSelçuk Üniversitesi
dc.relation.ispartofSelçuk-Teknik Dergisi
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Başka Kurum Yazarı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectImage Processing
dc.subjectOlive Classification
dc.subjectKNN Classification Algorithm
dc.subjectDecision Tree
dc.subjectGörüntü İşleme
dc.subjectOlive Sınıflandırma
dc.subjectKNN Sınıflandırma Algoritması
dc.subjectKarar Ağacı
dc.titleDimension and color classification of olive fruit with image processing techniques
dc.typeArticle

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