1 Ocak 2009 Dergi makalesi Açık Erişim

Gunay, Osman; Tasdemir, Kasim; Toreyin, B. Ugur; Cetin, A. Enis

Dublin Core

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  <dc:creator>Gunay, Osman</dc:creator>
  <dc:creator>Tasdemir, Kasim</dc:creator>
  <dc:creator>Toreyin, B. Ugur</dc:creator>
  <dc:creator>Cetin, A. Enis</dc:creator>
  <dc:date>2009-01-01</dc:date>
  <dc:description>There has been an increasing interest in the study of video based fire detection algorithms as video based surveillance systems become widely available for indoor and outdoor monitoring applications. A novel method explicitly developed for video based detection of wildfires at night (in the dark) is presented in this paper. The method comprises four sub-algorithms: (i) slow moving video object detection, (ii) bright region detection, (iii) detection of objects exhibiting periodic motion, and (iv) a sub-algorithm interpreting the motion of moving regions in video. Each of these sub-algorithms characterizes an aspect of fire captured at night by a visible range M camera. Individual decisions of the sub-algorithms are combined together using a least-mean-square (LMS) based decision fusion approach, and fire/nofire decision is reached by an active learning method. (C) 2009 Elsevier Ltd. All rights reserved.</dc:description>
  <dc:identifier>https://aperta.ulakbim.gov.trrecord/42017</dc:identifier>
  <dc:identifier>oai:zenodo.org:42017</dc:identifier>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>http://www.opendefinition.org/licenses/cc-by</dc:rights>
  <dc:source>FIRE SAFETY JOURNAL 44(6) 860-868</dc:source>
  <dc:title>Video based wildfire detection at night</dc:title>
  <dc:type>info:eu-repo/semantics/article</dc:type>
  <dc:type>publication-article</dc:type>
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