Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A Ground Truth for Iris Segmentation
Department of Computer Sciences, University of Salzburg, Salzburg, Austria. (Multimedia Signal Processing and Security Lab)
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0002-1400-346X
Department of Computer Sciences, University of Salzburg, Salzburg, Austria. (Multimedia Signal Processing and Security Lab)
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0002-4929-1262
Show others and affiliations
2014 (English)In: 2014 22nd International Conference on Pattern Recognition (ICPR) / [ed] Lisa O’Conner, Los Alamitos: IEEE Computer Society, 2014, 527-532 p.Conference paper, Published paper (Refereed)
Abstract [en]

Classical iris biometric systems assume ideal environmental conditions and cooperative users for image acquisition. When conditions are less ideal or users are uncooperative or unaware of their biometrics being taken the image acquisition quality suffers. This makes it harder for iris localization and segmentation algorithms to properly segment the acquired image into iris and non-iris parts. Segmentation is a critical part in iris recognition systems, since errors in this initial stage are propagated to subsequent processing stages. Therefore, the performance of iris segmentation algorithms is paramount to the performance of the overall system. In order to properly evaluate and develop iris segmentation algorithm, especially under difficult conditions like off angle and significant occlusions or bad lighting, it is beneficial to directly assess the segmentation algorithm. Currently, when evaluating the performance of iris segmentation algorithms this is mostly done by utilizing the recognition rate, and consequently the overall performance of the biometric system. In order to streamline the development and assessment of iris segmentation algorithms with the dependence on the whole biometric system we have generated a iris segmentation ground truth database. We will show a method for evaluating iris segmentation performance base on this ground truth database and give examples of how to identify problematic cases in order to further analyse the segmentation algorithms. ©2014 IEEE.

Place, publisher, year, edition, pages
Los Alamitos: IEEE Computer Society, 2014. 527-532 p.
Series
International Conference on Pattern Recognition, ISSN 1051-4651
Keyword [en]
Iris recognition, Image segmentation, Iris, Algorithm design and analysis, Image databases, Biomedical imaging
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:hh:diva-24992DOI: 10.1109/ICPR.2014.101ISI: 000359818000089Scopus ID: 2-s2.0-84919897814ISBN: 978-1-4799-5208-3 (print)OAI: oai:DiVA.org:hh-24992DiVA: diva2:710627
Conference
22nd International Conference on Pattern Recognition, ICPR, Stockholm, Sweden, August 24-28, 2014
Funder
Swedish Research Council, 2012-4313
Available from: 2014-04-07 Created: 2014-04-07 Last updated: 2017-09-27Bibliographically approved

Open Access in DiVA

fulltext(3567 kB)389 downloads
File information
File name FULLTEXT01.pdfFile size 3567 kBChecksum SHA-512
d4e65b22dd4d54db7271bc70480cbfcc142bca078e5b6cb57e0480b19e59d88e1c09fe52d3bc4603fb86c5157564bcdd8e8ee280cefe62f671916871b3802d71
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Alonso-Fernandez, FernandoBigun, Josef
By organisation
CAISR - Center for Applied Intelligent Systems Research
Signal Processing

Search outside of DiVA

GoogleGoogle Scholar
Total: 389 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 540 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf