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dc.contributor.convenorhttp://www.mirlabs.net/isda13/proceedings/
dc.contributor.authorDas, Abhijit
dc.contributor.authorBlumenstein, Michael
dc.contributor.authorPal, Umapada
dc.contributor.authorFerrer Ballester, Miguel Angel
dc.contributor.editorAjith Abraham
dc.date.accessioned2017-07-27T01:31:07Z
dc.date.available2017-07-27T01:31:07Z
dc.date.issued2014
dc.identifier.refurihttp://www.mirlabs.net/isda13/proceedings/
dc.identifier.urihttp://hdl.handle.net/10072/61112
dc.description.abstractIn this paper we propose a biometric sclera recognition and validation system. Here the sclera segmentation is performed by a time-adaptive active contour-based region growing technique. The sclera vessels are not prominent so image enhancement is required and hence a bank of 2D decomposition Haar wavelet multi-resolution filters is used to enhance the vessels pattern for better accuracy. For feature extraction, Dense Scale Invariant Feature Transform (D-SIFT) is used. D-SIFT patch descriptors of each training image are used to form bag of features by using k-means clustering and a spatial pyramid model, which is used to produce the training model. Support Vector Machines (SVMs) are used for classification. The UBIRIS version 1 dataset is used here for experimentation. An encouraging Equal Error Rate (EER) of 0.66% is attained in the experiments presented. Keywords: Biometric; Sclera vessel patterns; D-SIFT; SVM; Bag of features, k-means, Bank of 2D decomposition Haar multi- resolution filters wavelet. .
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.language.isoeng
dc.publisherIEEE
dc.publisher.placeUnited States
dc.publisher.urihttp://www.mirlabs.net/isda13/
dc.relation.ispartof39728
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofconferencenameISDA 2013
dc.relation.ispartofconferencetitle2013 International Conference on Intelligent Systems Design and Applications (ISDA 2013)
dc.relation.ispartofdatefrom2013-12-08
dc.relation.ispartofdateto2013-12-10
dc.relation.ispartoflocationMalaysia
dc.rights.retentionY
dc.subject.fieldofresearchComputer Vision
dc.subject.fieldofresearchcode080104
dc.titleSclera Recognition Using Dense-SIFT
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.date.issued2015-05-25T05:16:45Z
gro.hasfulltextNo Full Text
gro.griffith.authorBlumenstein, Michael M.
gro.griffith.authorDas, Abhijit


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