Difference between revisions of "Publications:Quality Factors Affecting Iris Segmentation and Matching"
From ISLAB/CAISR
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{{PublicationSetupTemplate|Author=Fernando Alonso-Fernandez, Josef Bigun | {{PublicationSetupTemplate|Author=Fernando Alonso-Fernandez, Josef Bigun | ||
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| − | |Name=Alonso-Fernandez, Fernando | + | |Name=Alonso-Fernandez, Fernando (feralo) (0000-0002-1400-346X) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), CAISR Centrum för tillämpade intelligenta system (IS-lab) (13650));Bigun, Josef (josef) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), CAISR Centrum för tillämpade intelligenta system (IS-lab) (13650)) |
|Title=Quality Factors Affecting Iris Segmentation and Matching | |Title=Quality Factors Affecting Iris Segmentation and Matching | ||
|PublicationType=Conference Paper | |PublicationType=Conference Paper | ||
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|Volume= | |Volume= | ||
|Issue= | |Issue= | ||
| − | |HostPublication=Proceedings 2013 International Conference on Biometrics | + | |HostPublication=Proceedings – 2013 International Conference on Biometrics, ICB 2013 |
| − | |Conference=ICB-2013, The 6th IAPR International Conference on Biometrics June 4 - 7, 2013 | + | |Conference=ICB-2013, The 6th IAPR International Conference on Biometrics, Madrid, Spain, June 4-7, 2013 |
| − | |StartPage= | + | |StartPage=Article number 6613016 |
| − | |EndPage= | + | |EndPage= |
|Year=2013 | |Year=2013 | ||
|Edition= | |Edition= | ||
|Pages= | |Pages= | ||
| − | |City=Piscataway | + | |City=Piscataway, N.J. |
|Publisher=IEEE conference proceedings | |Publisher=IEEE conference proceedings | ||
|Series= | |Series= | ||
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|ISRN= | |ISRN= | ||
|DOI=http://dx.doi.org/10.1109/ICB.2013.6613016 | |DOI=http://dx.doi.org/10.1109/ICB.2013.6613016 | ||
| − | |ISI= | + | |ISI=000334288200065 |
|PMID= | |PMID= | ||
| − | |ScopusId= | + | |ScopusId=2-s2.0-84887495558 |
|NBN=urn:nbn:se:hh:diva-21554 | |NBN=urn:nbn:se:hh:diva-21554 | ||
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|Notes=<p>IEEE Catalog Number: CFP1392R-ART</p> | |Notes=<p>IEEE Catalog Number: CFP1392R-ART</p> | ||
| − | |Abstract=<p>Image degradations can affect the different processing steps of iris recognition systems. With several quality factors proposed for iris images, its specific effect in the segmentation accuracy is often obviated, with most of the efforts focused on its impact in the recognition accuracy. Accordingly, we evaluate the impact of 8 quality measures in the performance of iris segmentation. We use a database acquired with a close-up iris sensor and built-in quality checking process. Despite the latter, we report differences in behavior, with some measures clearly predicting the segmentation performance, while others giving inconclusive results. Recognition experiments with two matchers also show that segmentation and matching performance are not necessarily affected by the same factors. The resilience of one matcher to segmentation inaccuracies also suggest that segmentation errors due to low image quality are not necessarily revealed by the matcher, pointing out the importance of separate evaluation of the segmentation accuracy.</p> | + | |Abstract=<p>Image degradations can affect the different processing steps of iris recognition systems. With several quality factors proposed for iris images, its specific effect in the segmentation accuracy is often obviated, with most of the efforts focused on its impact in the recognition accuracy. Accordingly, we evaluate the impact of 8 quality measures in the performance of iris segmentation. We use a database acquired with a close-up iris sensor and built-in quality checking process. Despite the latter, we report differences in behavior, with some measures clearly predicting the segmentation performance, while others giving inconclusive results. Recognition experiments with two matchers also show that segmentation and matching performance are not necessarily affected by the same factors. The resilience of one matcher to segmentation inaccuracies also suggest that segmentation errors due to low image quality are not necessarily revealed by the matcher, pointing out the importance of separate evaluation of the segmentation accuracy. © 2013 IEEE.</p> |
|Opponents= | |Opponents= | ||
|Supervisors= | |Supervisors= | ||
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|CreatedDate=2013-02-22 | |CreatedDate=2013-02-22 | ||
|PublicationDate=2013-02-22 | |PublicationDate=2013-02-22 | ||
| − | |LastUpdated= | + | |LastUpdated=2015-09-29 |
|diva=http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:607425}} | |diva=http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:607425}} | ||
<div style='display: none'> | <div style='display: none'> | ||
Latest revision as of 21:41, 30 September 2016
| Title | Quality Factors Affecting Iris Segmentation and Matching |
|---|---|
| Author | Fernando Alonso-Fernandez and Josef Bigun |
| Year | 2013 |
| PublicationType | Conference Paper |
| Journal | |
| HostPublication | Proceedings – 2013 International Conference on Biometrics, ICB 2013 |
| Conference | ICB-2013, The 6th IAPR International Conference on Biometrics, Madrid, Spain, June 4-7, 2013 |
| DOI | http://dx.doi.org/10.1109/ICB.2013.6613016 |
| Diva url | http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:607425 |
| Abstract | Image degradations can affect the different processing steps of iris recognition systems. With several quality factors proposed for iris images, its specific effect in the segmentation accuracy is often obviated, with most of the efforts focused on its impact in the recognition accuracy. Accordingly, we evaluate the impact of 8 quality measures in the performance of iris segmentation. We use a database acquired with a close-up iris sensor and built-in quality checking process. Despite the latter, we report differences in behavior, with some measures clearly predicting the segmentation performance, while others giving inconclusive results. Recognition experiments with two matchers also show that segmentation and matching performance are not necessarily affected by the same factors. The resilience of one matcher to segmentation inaccuracies also suggest that segmentation errors due to low image quality are not necessarily revealed by the matcher, pointing out the importance of separate evaluation of the segmentation accuracy. © 2013 IEEE. |
