Effect of eyelid and eyelash occlusions on iris images using subpattern-based approaches

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dc.contributor.authorEskandari, Maryam
dc.contributor.authorToygar, Önsen
dc.date.accessioned2026-02-06T17:54:40Z
dc.date.issued2009
dc.departmentDoğu Akdeniz Üniversitesi
dc.description5th International Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control, ICSCCW 2009 --
dc.description.abstractThe effect of eyelid and eyelash occlusions on iris images is investigated in this study using subpattern-based approaches. Principal Component Analysis (PCA), subpattern-based PCA (spPCA) and modular PCA (mPCA) methods are used as feature extractors to recognize occluded iris images. In order to eliminate the effect of illumination changes, histogram equalization and mean-and-variance normalization techniques are used. Various experiments are carried out on UBIRIS, CASIA and MMU iris databases to demonstrate the effect of eyelid and eyelash occlusions on iris images. The results of the experiments are consistent with the results of other biometrics systems using PCA, spPCA and mPCA approaches. ©2009 IEEE.
dc.identifier.doi10.1109/ICSCCW.2009.5379468
dc.identifier.isbn9781424434282
dc.identifier.scopus2-s2.0-77950504831
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/ICSCCW.2009.5379468
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/
dc.identifier.urihttps://hdl.handle.net/11129/7528
dc.indekslendigikaynakScopus
dc.language.isoen
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20260204
dc.subjectIris recognition
dc.subjectOcclusion
dc.subjectPCA
dc.subjectSubpattern-based approaches
dc.titleEffect of eyelid and eyelash occlusions on iris images using subpattern-based approaches
dc.typeConference Object

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