Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)

Image-Based Fire Detection Using Neural Networks

Authors
Wen-Bing Horng 0, Jian-Wen Peng
Corresponding Author
Wen-Bing Horng
0Tamkang University
Available Online October 2006.
DOI
https://doi.org/10.2991/jcis.2006.301How to use a DOI?
Keywords
burning degree estimation, color masking, fire flame detection, neural network
Abstract
An image-based fire detection method using neural networks is proposed in this paper. First, flame color features, based on the HSI color model, are trained by a backpropagation neural network for flame recognition. Then, based on the learned flame color features, regions with fire-like colors are roughly separated from an image. Besides segmenting flame regions, background objects with similar fire colors or resulted from the reflection of fire flames are also separated from the image. In order to get rid of these spurious fire-like regions, the image difference method and the invented color masking technique are applied. Finally, a compact method is devised to estimate the burning degree of fire flames so that users could be informed with a proper warning alarm. The proposed system can achieve 96.47% fire detection rate on average.
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Proceedings
9th Joint International Conference on Information Sciences (JCIS-06)
Part of series
Advances in Intelligent Systems Research
Publication Date
October 2006
ISBN
978-90-78677-01-7
ISSN
1951-6851
DOI
https://doi.org/10.2991/jcis.2006.301How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Wen-Bing Horng
AU  - Jian-Wen Peng
PY  - 2006/10
DA  - 2006/10
TI  - Image-Based Fire Detection Using Neural Networks
BT  - 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.301
DO  - https://doi.org/10.2991/jcis.2006.301
ID  - Horng2006/10
ER  -