Robust localization and identification of African clawed frogs in digital images

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dc.authorid0000-0002-8649-6013
dc.authorid0000-0001-7550-8579
dc.authorid0000-0002-7117-3174
dc.contributor.authorTek, Faik Borayen_US
dc.contributor.authorCannavo, Flavioen_US
dc.contributor.authorNunnari, Giuseppeen_US
dc.contributor.authorKale, İzzeten_US
dc.date.accessioned2015-01-15T23:02:50Z
dc.date.available2015-01-15T23:02:50Z
dc.date.issued2014-09
dc.departmentIşık Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.departmentIşık University, Faculty of Engineering, Department of Computer Engineeringen_US
dc.description.abstractWe study the automatic localization and identification of African clawed frogs (Xenopus laevis sp.) in digital images taken in a laboratory environment. We propose a novel and stable frog body localization and skin pattern window extraction algorithm. We show that it compensates scale and rotation changes very well. Moreover, it is able to localize and extract highly overlapping regions (pattern windows) even in the cases of intense affine transformations, blurring, Gaussian noise, and intensity transformations. The frog skin pattern (i.e. texture) provides a unique feature for the identification of individual frogs. We investigate the suitability of five different feature descriptors (Gabor filters, area granulometry, HoG,(1) dense SIFT,(2) and raw pixel values) to represent frog skin patterns. We compare the robustness of the features based on their identification performance using a nearest neighbor classifier. Our experiments show that among five features that we tested, the best performing feature against rotation, scale, and blurring modifications was the raw pixel feature, whereas the SIFT feature was the best performing one against affine and intensity modifications.en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationTek, F. B., Cannavo, F., Nunnari, G. & Kale, İ. (2014). Robust localization and identification of african clawed frogs in digital images. Ecological Informatics, 23, 3-12. doi:10.1016/j.ecoinf.2013.09.005en_US
dc.identifier.doi10.1016/j.ecoinf.2013.09.005
dc.identifier.endpage12
dc.identifier.issn1574-9541
dc.identifier.issn1878-0512
dc.identifier.issueSI
dc.identifier.scopus2-s2.0-84905096672
dc.identifier.scopusqualityQ1
dc.identifier.startpage3
dc.identifier.urihttps://hdl.handle.net/11729/518
dc.identifier.urihttp://dx.doi.org/10.1016/j.ecoinf.2013.09.005
dc.identifier.volume23
dc.identifier.wosWOS:000340851600002
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakScience Citation Index Expanded (SCI-EXPANDED)en_US
dc.institutionauthorTek, Faik Borayen_US
dc.institutionauthorid0000-0002-8649-6013
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherElsevier Science BVen_US
dc.relation.ispartofEcological Informaticsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectXenopus laevisen_US
dc.subjectAutomated frog identificationen_US
dc.subjectSkin pattern recognitionen_US
dc.subjectArea granulometryen_US
dc.subjectSiften_US
dc.subjectHoGen_US
dc.subjectTexture analysisen_US
dc.subjectClassificationen_US
dc.subjectSimilarityen_US
dc.subjectRetrievalen_US
dc.subjectFeaturesen_US
dc.titleRobust localization and identification of African clawed frogs in digital imagesen_US
dc.typeArticleen_US
dspace.entity.typePublication

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