Publication
IRINA: Iris Recognition (even) in Inacurately Segmented Data
| dc.contributor.author | Proença, H. | |
| dc.contributor.author | Neves, João | |
| dc.date.accessioned | 2020-02-10T14:35:50Z | |
| dc.date.available | 2020-02-10T14:35:50Z | |
| dc.date.issued | 2017 | |
| dc.description.abstract | The effectiveness of current iris recognition systems de-pends on the accurate segmentation and parameterisationof the iris boundaries, as failures at this point misalignthe coefficients of the biometric signatures. This paper de-scribesIRINA, an algorithm forIrisRecognition that is ro-bust againstINAccurately segmented samples, which makesit a good candidate to work in poor-quality data. The pro-cess is based in the concept of ”corresponding” patch be-tween pairs of images, that is used to estimate the posteriorprobabilities that patches regard the same biological region,even in case of segmentation errors and non-linear texturedeformations. Such information enables to infer a free-formdeformation field (2D registration vectors) between images,whose first and second-order statistics provide effective bio-metric discriminating power. Extensive experiments werecarried out in four datasets (CASIA-IrisV3-Lamp, CASIA-IrisV4-Lamp, CASIA-IrisV4-Thousand and WVU) and showthat IRINA not only achieves state-of-the-art performancein good quality data, but also handles effectively severe seg-mentation errors and large differences in pupillary dilation/ constriction. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.6/9174 | |
| dc.language.iso | eng | pt_PT |
| dc.subject | Iris recognition | pt_PT |
| dc.title | IRINA: Iris Recognition (even) in Inacurately Segmented Data | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/5876/UID%2FEEA%2F50008%2F2013/PT | |
| oaire.fundingStream | 5876 | |
| person.familyName | Proença | |
| person.givenName | Hugo | |
| person.identifier | 1153590 | |
| person.identifier.ciencia-id | ED16-81E7-0319 | |
| person.identifier.orcid | 0000-0003-2551-8570 | |
| person.identifier.rid | F-9499-2010 | |
| person.identifier.scopus-author-id | 14016540600 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
| relation.isAuthorOfPublication | 16ca2fc4-5379-43a6-8867-ba63bd9289e0 | |
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