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<item>
  <id>05935959</id>
  <dt>a</dt>
  <an>05935959</an>
  <augroup>
    <au>Chora\'s, Micha{\l}</au>
    <au>Kozik, Rafa{\l}</au>
  </augroup>
  <ti>Knuckle recognition for human identification.</ti>
  <so>Burduk, Robert (ed.) et al., Computer recognition systems 4. Berlin: Springer (ISBN 978-3-642-20319-0/pbk; 978-3-642-20320-6/ebook). Advances in Intelligent and Soft Computing 95, 61-70 (2011).</so>
  <py>2011</py>
  <pu>Berlin: Springer</pu>
  <lagroup>
    <la>EN</la>
  </lagroup>
  <ccgroup>
  </ccgroup>
  <utgroup>
  </utgroup>
  <cigroup>
  </cigroup>
  <ligroup>
    <li>doi:10.1007/978-3-642-20320-6_7</li>
  </ligroup>
  <abgroup>
    <ab>Summary: This paper is the continuation of our previous work - hereby we report new results proving the effectiveness of our knuckle recognition method based on texture features. We use Probabilistic Hough Transform and SURF features as well as the 3-step classification methodology. Hereby we present promising results achieved for recently published PolyU knuckle database.</ab>
    <rv></rv>
  </abgroup>
</item>