Dergi makalesi Açık Erişim
Gunay, Osman; Tasdemir, Kasim; Toreyin, B. Ugur; Cetin, A. Enis
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.
Dosya adı | Boyutu | |
---|---|---|
bib-41fd6876-f09b-43d4-a5f8-03ea8258266d.txt
md5:1942a41def5d44aaf5cab79e4501540e |
134 Bytes | İndir |
Görüntülenme | 63 |
İndirme | 10 |
Veri hacmi | 1.3 kB |
Tekil görüntülenme | 59 |
Tekil indirme | 10 |