Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/21021
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dc.contributor.authorLameski, Petreen_US
dc.contributor.authorZdravevski, Eftimen_US
dc.contributor.authorKulakov, Andreaen_US
dc.contributor.authorGjorgjevikj, Dejanen_US
dc.date.accessioned2022-07-18T09:59:19Z-
dc.date.available2022-07-18T09:59:19Z-
dc.date.issued2015-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/21021-
dc.description.abstractIn this paper we compare two shape-based descriptors for plant leaf image classification. The leaves in the dataset are already segmented from the background only the contour detection algorithm is applied to extract the contour points and generate the shape-based descriptors. We propose a reduced size descriptor based on the angles between three points of the leaf contour and compare this descriptor with other similar descriptors based on their classification quality. The classification quality is measured both with 1-nearest neighbor comparison and with RBF-SVM model trained on the generated descriptors.en_US
dc.publisherFaculty of Computer Science and Engineering, Ss. Cyril and Methodius University in Skopje, Macedoniaen_US
dc.subjectimage processing; leaf image classification; machine learningen_US
dc.titlePlant images classification based on the angles between the leaf shape-contour pointsen_US
dc.typeProceedingsen_US
dc.relation.conferenceCIIT 2015en_US
item.fulltextWith Fulltext-
item.grantfulltextopen-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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