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|Title:||Fire detection in different color models||Authors:||Burak, Çelen V.
Muhammed, Fatih Demirci
|Keywords:||Fire and smoke detection
|Issue Date:||2012||Source:||2012 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2012, 16 July 2012 through 19 July 2012, Las Vegas, NV, 95339||Abstract:||Detecting forest fire is a highly active research area in the field of pattern recognition and computer vision as a number of existing methods available in the literature. The purpose of the proposed study is to select the most suitable color space, features and classifiers for the fire classification. Our approach begins by finding the likelihood of every pixel value. The fire is then defined by multiplying pixel channel value's likelihood. By using a simple thresholding schema, the fire pixel classification process is performed. Our experimental study demonstrates which color space, features and classifiers are most suitable for fire detection.||URI:||https://hdl.handle.net/20.500.11851/5741||ISBN:||9781601322258|
|Appears in Collections:||Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering|
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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