@article{ref1,
title="Fire detection using multi color space and background modeling",
journal="Fire technology",
year="2021",
author="Khalil, Adnan and Rahman, Sami Ur and Alam, Fakhre and Ahmad, Iftikhar and Khalil, Irshad",
volume="57",
number="3",
pages="1221-1239",
abstract="Emergency incidents and events of fires can be dangerous and required quick and accurate decision-making need quick and correct decision-making. The use of computer vision for fire detection can provide a efficient solution to deal with these situations. These systems handle the usual data, provide an automated solution, and discard non-relevant information without discarding relevant content. Researchers developed many techniques for fire detection in videos and still images by using different color-based models. However, for videos, these methods are unsuitable because of high false-positive results. These methods use few parameters with little physical meaning, which makes fire detection more difficult. To deal with this, we have proposed a novel fire detection method based on Red Green Blue and CIE $$L * a * b$$color models, by combining motion detection with tracking fire objects. We have eliminated the moving region and calculate the growth rate of the fire to reduce false-alarm and calculate the risk. The proposed method operates on a reduced number of parameters compared to the existing methods. Experimental results demonstrate the effectiveness of our method of reducing false positives while keeping their precision compatible with the existing methods.<p /> <p>Language: en</p>",
language="en",
issn="0015-2684",
doi="10.1007/s10694-020-01030-9",
url="http://dx.doi.org/10.1007/s10694-020-01030-9"
}