Forest fire detection and identification using image processing and SVM


Mubarak Adam Ishag Mahmoud, Honge Ren, Journal of Information Processing Systems Vol. 15, No. 1, pp. 159-168, Feb. 2019  

https://doi.org/10.3745/JIPS.01.0038
Keywords: Background subtraction, CIE L?a?b? Color Space, Forest Fire, SVM, wavelet
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Abstract

Accurate forest fires detection algorithms remain a challenging issue, because, some of the objects have the same features with fire, which may result in high false alarms rate. This paper presents a new video-based, image processing forest fires detection method, which consists of four stages. First, a background-subtraction algorithm is applied to detect moving regions. Secondly, candidate fire regions are determined using CIE L?a?b? color space. Thirdly, special wavelet analysis is used to differentiate between actual fire and fire-like objects, because candidate regions may contain moving fire-like objects. Finally, support vector machine is used to classify the region of interest to either real fire or non-fire. The final experimental results verify that the proposed method effectively identifies the forest fires.


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Cite this article
[APA Style]
Mahmoud, M. & Ren, H. (2019). Forest fire detection and identification using image processing and SVM. Journal of Information Processing Systems, 15(1), 159-168. DOI: 10.3745/JIPS.01.0038.

[IEEE Style]
M. A. I. Mahmoud and H. Ren, "Forest fire detection and identification using image processing and SVM," Journal of Information Processing Systems, vol. 15, no. 1, pp. 159-168, 2019. DOI: 10.3745/JIPS.01.0038.

[ACM Style]
Mubarak Adam Ishag Mahmoud and Honge Ren. 2019. Forest fire detection and identification using image processing and SVM. Journal of Information Processing Systems, 15, 1, (2019), 159-168. DOI: 10.3745/JIPS.01.0038.