Difference between revisions of "Publications:Experimental Analysis Regarding the Influence of Iris Segmentation on the Recognition Rate"
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{{PublicationSetupTemplate|Author=Heinz Hofbauer, Fernando Alonso-Fernandez, Josef Bigun, Andreas Uhl | {{PublicationSetupTemplate|Author=Heinz Hofbauer, Fernando Alonso-Fernandez, Josef Bigun, Andreas Uhl | ||
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| − | |Name=Hofbauer, Heinz (University of Salzburg, Salzburg, Austria);Alonso-Fernandez, Fernando | + | |Name=Hofbauer, Heinz (University of Salzburg, Salzburg, Austria);Alonso-Fernandez, Fernando (feralo) (0000-0002-1400-346X) (Högskolan i Halmstad (2804), Akademin för informationsteknologi (16904), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), CAISR Centrum för tillämpade intelligenta system (IS-lab) (13650));Bigun, Josef (josef) (Högskolan i Halmstad (2804), Akademin för informationsteknologi (16904), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), CAISR Centrum för tillämpade intelligenta system (IS-lab) (13650));Uhl, Andreas (University of Salzburg, Salzburg, Austria) |
|Title=Experimental Analysis Regarding the Influence of Iris Segmentation on the Recognition Rate | |Title=Experimental Analysis Regarding the Influence of Iris Segmentation on the Recognition Rate | ||
|PublicationType=Journal Paper | |PublicationType=Journal Paper | ||
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|Journal=IET Biometrics | |Journal=IET Biometrics | ||
|JournalISSN=2047-4938 | |JournalISSN=2047-4938 | ||
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| − | |StartPage= | + | |StartPage=200 |
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|Year=2016 | |Year=2016 | ||
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| − | |DOI= | + | |DOI=http://dx.doi.org/10.1049/iet-bmt.2015.0069 |
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| − | |Keywords= | + | |Keywords=image segmentation;iris recognition |
|Categories=Signalbehandling (20205) | |Categories=Signalbehandling (20205) | ||
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| − | |Abstract= | + | |Abstract=<p>In this study the authors will look at the detection and segmentation of the iris and its influence on the overall performance of the iris-biometric tool chain. The authors will examine whether the segmentation accuracy, based on conformance with a ground truth, can serve as a predictor for the overall performance of the iris-biometric tool chain. That is: If the segmentation accuracy is improved will this always improve the overall performance? Furthermore, the authors will systematically evaluate the influence of segmentation parameters, pupillary and limbic boundary and normalisation centre (based on Daugman's rubbersheet model), on the rest of the iris-biometric tool chain. The authors will investigate if accurately finding these parameters is important and how consistency, that is, extracting the same exact region of the iris during segmenting, influences the overall performance. © The Institution of Engineering and Technology 2016</p> |
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|CreatedDate=2015-11-24 | |CreatedDate=2015-11-24 | ||
|PublicationDate=2015-11-24 | |PublicationDate=2015-11-24 | ||
| − | |LastUpdated=2016- | + | |LastUpdated=2016-08-16 |
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Latest revision as of 22:39, 30 September 2016
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| Title | Experimental Analysis Regarding the Influence of Iris Segmentation on the Recognition Rate |
|---|---|
| Author | |
| Year | 2016 |
| PublicationType | Journal Paper |
| Journal | IET Biometrics |
| HostPublication | |
| Conference | |
| DOI | http://dx.doi.org/10.1049/iet-bmt.2015.0069 |
| Diva url | http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:873744 |
| Abstract | In this study the authors will look at the detection and segmentation of the iris and its influence on the overall performance of the iris-biometric tool chain. The authors will examine whether the segmentation accuracy, based on conformance with a ground truth, can serve as a predictor for the overall performance of the iris-biometric tool chain. That is: If the segmentation accuracy is improved will this always improve the overall performance? Furthermore, the authors will systematically evaluate the influence of segmentation parameters, pupillary and limbic boundary and normalisation centre (based on Daugman's rubbersheet model), on the rest of the iris-biometric tool chain. The authors will investigate if accurately finding these parameters is important and how consistency, that is, extracting the same exact region of the iris during segmenting, influences the overall performance. © The Institution of Engineering and Technology 2016 |
