Recognition of plant leaves: An approach with hybrid features produced by dividing leaf images into two and four parts

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dc.authoridHanbay, Davut/0000-0003-2271-7865
dc.authorwosidHanbay, Davut/AAG-8511-2019
dc.contributor.authorTurkoglu, Muammer
dc.contributor.authorHanbay, Davut
dc.date.accessioned2024-08-04T20:45:42Z
dc.date.available2024-08-04T20:45:42Z
dc.date.issued2019
dc.departmentİnönü Üniversitesien_US
dc.description.abstractPlants play a crucial role in the lives of all living things. A risk of extinction exists for many plants, hence many botanists and scientists are working in order to protect plants and plant diversity. Plant identification is the most important part of studies carried out for this purpose. In order to identify plants more accurately, different approaches have been used in the studies to date. One of these approaches is plant identification through leaf recognition, and is the basis of many conducted studies. It can be used for automatic plant recognition in the area of botany, the food sector, industry, medicine, and in many more areas too. In this study, image processing based on feature extraction methods such as color features, vein features, Fourier Descriptors (FD), and Gray-Level Co-occurrence Matrix (GLCM) methods are used. This study suggests the use of features extracted from leaves divided into two or four parts, instead of extracting for the whole leaf. Both the individual and combined performances of each feature extraction method are calculated by Extreme Learning Machines (ELM) classifier. The suggested approach has been applied to the Flavia leaf dataset. 10-fold cross-validation was used to evaluate the accuracy of the proposed method, which was then compared and tabulated with methods from other studies. The evaluated accuracy of the proposed method on the Flavia leaf dataset was calculated as 99.10%. (C) 2019 Elsevier Inc. All rights reserved.en_US
dc.identifier.doi10.1016/j.amc.2019.01.054
dc.identifier.endpage14en_US
dc.identifier.issn0096-3003
dc.identifier.issn1873-5649
dc.identifier.scopus2-s2.0-85060939399en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage1en_US
dc.identifier.urihttps://doi.org/10.1016/j.amc.2019.01.054
dc.identifier.urihttps://hdl.handle.net/11616/98634
dc.identifier.volume352en_US
dc.identifier.wosWOS:000459775000001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier Science Incen_US
dc.relation.ispartofApplied Mathematics and Computationen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectLeaf recognitionen_US
dc.subjectImage processingen_US
dc.subjectSection processen_US
dc.subjectHybrid featuresen_US
dc.subjectELMen_US
dc.titleRecognition of plant leaves: An approach with hybrid features produced by dividing leaf images into two and four partsen_US
dc.typeArticleen_US

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