Publication
Non-cooperative iris recognition
| dc.contributor.advisor | Proença, Hugo Pedro Martins Carriço | |
| dc.contributor.author | Santos, Gil Melfe Mateus | |
| dc.date.accessioned | 2015-07-23T09:35:02Z | |
| dc.date.available | 2015-07-23T09:35:02Z | |
| dc.date.issued | 2009 | |
| dc.date.submitted | 2009-08 | |
| dc.description.abstract | The dramatic growth in practical applications for iris biometrics has been accompanied by relevant developments in the underlying algorithms and techniques. Along with the research focused on near-infrared images captured with subject cooperation, e orts are being made to minimize the trade-o between the quality of the captured data and the recognition accuracy on less constrained environments, where images are obtained at the visible wavelength, at increased distances, over simpli ed acquisition protocols and adverse lightning conditions. At a rst stage, interpolation e ects on normalization process are addressed, pointing the outcomes in the overall recognition error rates. Secondly, a couple of post-processing steps to the Daugman's approach are performed, attempting to increase its performance in the particular unconstrained environments this thesis assumes. Analysis on both frequency and spatial domains and nally pattern recognition methods are applied in such e orts. This thesis embodies the study on how subject recognition can be achieved, without his cooperation, making use of iris data captured at-a-distance, on-the-move and at visible wavelength conditions. Widely used methods designed for constrained scenarios are analyzed. | |
| dc.description.sponsorship | Fundação para a Ciência e a Tecnologia (FCT) | por |
| dc.identifier.uri | http://hdl.handle.net/10400.6/3761 | |
| dc.language.iso | por | por |
| dc.relation | BioRec - Non-Cooperative Multimodal Biometric Recognition | |
| dc.title | Non-cooperative iris recognition | por |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | BioRec - Non-Cooperative Multimodal Biometric Recognition | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/5876-PPCDTI/PTDC%2FEIA%2F69106%2F2006/PT | |
| oaire.fundingStream | 5876-PPCDTI | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| rcaap.rights | openAccess | por |
| rcaap.type | masterThesis | por |
| relation.isProjectOfPublication | 256ed824-fca0-4cfe-9b7e-30fd12be7742 | |
| relation.isProjectOfPublication.latestForDiscovery | 256ed824-fca0-4cfe-9b7e-30fd12be7742 | |
| thesis.degree.discipline | Engenharia Informática | por |
| thesis.degree.level | Mestre | por |
| thesis.degree.name | Dissertação apresentada à Universidade da Beira Interior para a obtenção do grau de mestre em Engenharia Informática | por |