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dc.contributor.authorDas, Abhijit
dc.contributor.authorPal, Umapada
dc.contributor.authorFerrer Ballester, Miguel Angel
dc.contributor.authorBlumenstein, Michael
dc.contributor.editorJ. Fierrez, S. Z. Li, A. Ross, R. Veldhuis, F. Alonso-Fernandez, J. Bigun
dc.date.accessioned2018-06-01T01:00:19Z
dc.date.available2018-06-01T01:00:19Z
dc.date.issued2016
dc.identifier.doi10.1109/ICB.2016.7550069
dc.identifier.urihttp://hdl.handle.net/10072/123942
dc.description.abstractAbstract: This article reports and summarizes the results of a competition on sclera segmentation and recognition benchmarking, called Sclera Segmentation and Recognition Benchmarking Competition 2016 (SSRBC 2016). It was organized in the context of the 9th IAPR International Conference on Biometrics (ICB 2016). The goal of this competition was to record the recent developments in sclera segmentation and recognition, and also to gain the attention of researchers on this subject of biometrics. In this regard, we have used a multi-angle sclera dataset (MASD version 1). It is comprised of 2624 images taken from both the eyes of 82 identities. Therefore, it consists of images of 164 (82*2) different eyes. We have prepared a manual segmentation mask of these images to create the baseline for both tasks. We have, furthermore, adopted precision and recall based statistical measures to evaluate the effectiveness of the segmentation and the ranks of the competing algorithms. The recognition accuracy measure has been employed to measure the recognition task. To summarize, twelve participants registered for the competition, and among them, three participants submitted their algorithms/ systems for the segmentation task and two their recognition algorithm. The results produced by these algorithms reflect developments in the literature of sclera segmentation and recognition, employing cutting edge segmentation techniques. Along with the algorithms of three competing teams and their results, the MASD version 1 dataset will also be freely available for research purposes from the organizer's website. The competition also demonstrates the recent interests of researchers from academia as well as industry on this subject of biometrics.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.publisher.placeUnited States
dc.relation.ispartofconferencenameICB 2016
dc.relation.ispartofconferencetitle2016 International Conference on Biometrics (ICB): Proceedings
dc.relation.ispartofdatefrom2016-06-13
dc.relation.ispartofdateto2016-06-16
dc.relation.ispartoflocationHalmstad, Sweden
dc.subject.fieldofresearchArtificial intelligence not elsewhere classified
dc.subject.fieldofresearchcode460299
dc.titleSSRBC 2016: Sclera Segmentation and Recognition Benchmarking Competition
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.hasfulltextNo Full Text
gro.griffith.authorBlumenstein, Michael M.
gro.griffith.authorDas, Abhijit


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