Classification of butterfly images with multi-scale local binary patterns

Basit Öğe Kaydı
dc.contributor.authorKaya, Yilmaz
dc.contributor.authorKayci, Lokman
dc.contributor.authorSezgin, Necmettin
dc.date.accessioned2024-12-24T19:23:55Z
dc.date.available2024-12-24T19:23:55Z
dc.date.issued2013
dc.departmentSiirt Üniversitesi
dc.description21st Signal Processing and Communications Applications Conference (SIU) -- APR 24-26, 2013 -- CYPRUS
dc.description.abstractButterflies are classified first according to their outer morphological qualities. It is required to analyze their genital characters when classification according to their outer morphological qualities is not possible. The genital characters of butterflies can be obtained using various chemical substances and methods; however, these processes can only be carried out with some certain expenses. Furthermore, the preparation of genital slides is time-consuming since it requires specific processes. In this study, a computer vision system based on local binary patterns was proposed to alternative conventional diagnostic methods for the diagnosis of butterfly species. 140 images of 14 butterfly species belonging to the family of Styridae are used. The butterfly diagnostic process was carried out by using LBPP, R attributes as inputs for the ANN, SVM and LR classification methods. 100% classification was achieved with macro and micro patterns obtained with LBPP, R for different values of parameter R. As a result, it was seen butterfly wings have different types of micro and macro properties, and LBP has a major advantage in identification of butterfly species.
dc.identifier.isbn978-1-4673-5563-6
dc.identifier.isbn978-1-4673-5562-9
dc.identifier.issn2165-0608
dc.identifier.scopus2-s2.0-84880908248
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://hdl.handle.net/20.500.12604/5749
dc.identifier.wosWOS:000325005300124
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherIEEE
dc.relation.ispartof2013 21st Signal Processing and Communications Applications Conference (Siu)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241222
dc.subjectbutterfly identification
dc.subjectlocal binary Pattern
dc.subjectcomputer vision
dc.subjectpattern recognition
dc.titleClassification of butterfly images with multi-scale local binary patterns
dc.title.alternativeÇok ölçekli yerel ikili örüntüler ile kelebek görüntülerin siniflandirilmasi
dc.typeConference Object

Dosyalar

Koleksiyon

WOS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu