Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/5741
Title: Fire detection in different color models
Authors: Burak, Çelen V.
Muhammed, Fatih Demirci
Keywords: Fire and smoke detection
Pattern recognition
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

Show full item record

CORE Recommender

Page view(s)

6
checked on Dec 26, 2022

Google ScholarTM

Check

Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.