Publikation:

Realtime Quality Assessment of Iris Biometrics under Visible Light

Vorschaubild

Dateien

Jenadeleh_2-1db8odgkzm0gn5.pdf
Jenadeleh_2-1db8odgkzm0gn5.pdfGröße: 1.03 MBDownloads: 556

Datum

2018

Autor:innen

Pedersen, Marius

Herausgeber:innen

Kontakt

ISSN der Zeitschrift

Electronic ISSN

ISBN

Bibliografische Daten

Verlag

Schriftenreihe

Auflagebezeichnung

URI (zitierfähiger Link)
http://nbn-resolving.de/urn:nbn:de:bsz:352-2-1db8odgkzm0gn5
DOI (zitierfähiger Link)
https://doi.org/10.1109/CVPRW.2018.00085
ArXiv-ID

Internationale Patentnummer

Link zur Lizenz
Urheberrechtlich geschützt

Angaben zur Forschungsförderung

Projekt

Open Access-Veröffentlichung
Open Access Green

Sammlungen

Informatik und Informationswissenschaft: Publikationen
Core Facility der Universität Konstanz

Gesperrt bis

Titel in einer weiteren Sprache

Publikationstyp
Beitrag zu einem Konferenzband
Publikationsstatus
Published

Erschienen in

The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. Computer Vision Foundation, 2018, pp. 556-565. Available under: doi: 10.1109/CVPRW.2018.00085

Zusammenfassung

Ensuring sufficient quality of iris images acquired by handheld imaging devices in visible light poses many challenges to iris recognition systems. Many distortions affect the input iris images, and the source and types of these distortions are unknown in uncontrolled environments. We propose a fast no-reference image quality assessment measure for predicting iris image quality to handle severely degraded iris images. The proposed differential sign-magnitude statistics index (DSMI) is based on statistical features of the local difference sign-magnitude transform, which are computed by comparing the local mean with the central pixel of the patch and considering the noticeable variations. The experiments, conducted with a reference iris recognition system and three visible light datasets, showed that the quality of iris images strongly affects the recognition performance. Using the proposed method as a quality filtering step improved the performance of the iris recognition system by rejecting poor quality iris samples.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
004 Informatik

Schlagwörter

Konferenz

CVPR 2018 : IEEE/CVF Conference on Computer Vision and Pattern Recognition, 18. Juni 2018 - 22. Juni 2018, Salt Lake City, Utah, USA
Rezension
undefined / . - undefined, undefined

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Zugehörige Datensätze in KOPS

Zitieren

ISO 690JENADELEH, Mohsen, Marius PEDERSEN, Dietmar SAUPE, 2018. Realtime Quality Assessment of Iris Biometrics under Visible Light. CVPR 2018 : IEEE/CVF Conference on Computer Vision and Pattern Recognition. Salt Lake City, Utah, USA, 18. Juni 2018 - 22. Juni 2018. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. Computer Vision Foundation, 2018, pp. 556-565. Available under: doi: 10.1109/CVPRW.2018.00085
BibTex
@inproceedings{Jenadeleh2018Realt-42587,
  year={2018},
  doi={10.1109/CVPRW.2018.00085},
  title={Realtime Quality Assessment of Iris Biometrics under Visible Light},
  url={http://openaccess.thecvf.com/content_CVPR_2018/papers/w11/Jenadeleh_Realtime_Quality_Assessment_CVPR_2018_paper.pdf},
  publisher={Computer Vision Foundation},
  booktitle={The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
  pages={556--565},
  author={Jenadeleh, Mohsen and Pedersen, Marius and Saupe, Dietmar}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/42587">
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:creator>Saupe, Dietmar</dc:creator>
    <dc:contributor>Jenadeleh, Mohsen</dc:contributor>
    <dc:language>eng</dc:language>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/42587/3/Jenadeleh_2-1db8odgkzm0gn5.pdf"/>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2018-06-14T12:59:46Z</dcterms:available>
    <dc:creator>Pedersen, Marius</dc:creator>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/42587"/>
    <dc:rights>terms-of-use</dc:rights>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2018-06-14T12:59:46Z</dc:date>
    <dc:contributor>Pedersen, Marius</dc:contributor>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dcterms:title>Realtime Quality Assessment of Iris Biometrics under Visible Light</dcterms:title>
    <dc:contributor>Saupe, Dietmar</dc:contributor>
    <dcterms:abstract xml:lang="eng">Ensuring sufficient quality of iris images acquired by handheld imaging devices in visible light poses many challenges to iris recognition systems. Many distortions affect the input iris images, and the source and types of these distortions are unknown in uncontrolled environments. We propose a fast no-reference image quality assessment measure for predicting iris image quality to handle severely degraded iris images. The proposed differential sign-magnitude statistics index (DSMI) is based on statistical features of the local difference sign-magnitude transform, which are computed by comparing the local mean with the central pixel of the patch and considering the noticeable variations. The experiments, conducted with a reference iris recognition system and three visible light datasets, showed that the quality of iris images strongly affects the recognition performance. Using the proposed method as a quality filtering step improved the performance of the iris recognition system by rejecting poor quality iris samples.</dcterms:abstract>
    <dc:creator>Jenadeleh, Mohsen</dc:creator>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/42587/3/Jenadeleh_2-1db8odgkzm0gn5.pdf"/>
    <dcterms:issued>2018</dcterms:issued>
  </rdf:Description>
</rdf:RDF>

Interner Vermerk

xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter

Kontakt
URL der Originalveröffentl.
http://openaccess.thecvf.com/content_CVPR_2018/papers/w11/Jenadeleh_Realtime_Quality_Assessment_CVPR_2018_paper.pdf

Prüfdatum der URL

2018-06-14

Prüfungsdatum der Dissertation

Finanzierungsart

Kommentar zur Publikation

Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Ja
Begutachtet
Diese Publikation teilen