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Unsupervised detection of non-iris occlusions

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F15%3A00444723" target="_blank" >RIV/67985556:_____/15:00444723 - isvavai.cz</a>

  • Alternative codes found

    RIV/68407700:21240/15:00240483

  • Result on the web

    <a href="http://dx.doi.org/10.1016/j.patrec.2015.02.012" target="_blank" >http://dx.doi.org/10.1016/j.patrec.2015.02.012</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.patrec.2015.02.012" target="_blank" >10.1016/j.patrec.2015.02.012</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Unsupervised detection of non-iris occlusions

  • Original language description

    This paper presents a fast precise unsupervised iris defects detection method based on the underlying multispectral spatial probabilistic iris textural model and adaptive thresholding applied to demanding high resolution mobile device measurements. The accurate detection of iris eyelids and reflections is the prerequisite for the accurate iris recognition, both in near-infrared or visible spectrum measurements. The model adaptively learns its parameters on the iris texture part and subsequently checks for iris reflections using the recursive prediction analysis. The method is developed for color eye images from unconstrained mobile devices but it was also successfully tested on the UBIRIS v2 eye database. Our method ranked first from the 97+1 recent Noisy Iris Challenge Evaluation contest alternative methods on this large color iris database using the exact contest data and methodology.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    BD - Information theory

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GA14-10911S" target="_blank" >GA14-10911S: Mathematical modeling of surface material appearance</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2015

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Pattern Recognition Letters

  • ISSN

    0167-8655

  • e-ISSN

  • Volume of the periodical

    57

  • Issue of the periodical within the volume

    5

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    6

  • Pages from-to

    60-65

  • UT code for WoS article

    000353350200008

  • EID of the result in the Scopus database

    2-s2.0-84939997157