Algorithm for Detection of Fire Smoke in a Video Based on Wavelet Energy Slope Fitting


Yi Zhang, Haifeng Wang, Xin Fan, Journal of Information Processing Systems Vol. 16, No. 3, pp. 557-571, Jun. 2020  

https://doi.org/10.3745/JIPS.01.0054
Keywords: Background Estimation Method, least square method, Low-Frequency Wavelet Energy, Slope Fitting, Smoke detection
Fulltext:

Abstract

The existing methods for detection of fire smoke in a video easily lead to misjudgment of cloud, fog and moving distractors, such as a moving person, a moving vehicle and other non-smoke moving objects. Therefore, an algorithm for detection of fire smoke in a video based on wavelet energy slope fitting is proposed in this paper. The change in wavelet energy of the moving target foreground is used as the basis, and a time window of 40 continuous frames is set to fit the wavelet energy slope of the suspected area in every 20 frames, thus establishing a wavelet-energy-based smoke judgment criterion. The experimental data show that the algorithm described in this paper not only can detect smoke more quickly and more accurately, but also can effectively avoid the distraction of cloud, fog and moving object and prevent false alarm.


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Cite this article
[APA Style]
Zhang, Y., Wang, H., & Fan, X. (2020). Algorithm for Detection of Fire Smoke in a Video Based on Wavelet Energy Slope Fitting. Journal of Information Processing Systems, 16(3), 557-571. DOI: 10.3745/JIPS.01.0054.

[IEEE Style]
Y. Zhang, H. Wang, X. Fan, "Algorithm for Detection of Fire Smoke in a Video Based on Wavelet Energy Slope Fitting," Journal of Information Processing Systems, vol. 16, no. 3, pp. 557-571, 2020. DOI: 10.3745/JIPS.01.0054.

[ACM Style]
Yi Zhang, Haifeng Wang, and Xin Fan. 2020. Algorithm for Detection of Fire Smoke in a Video Based on Wavelet Energy Slope Fitting. Journal of Information Processing Systems, 16, 3, (2020), 557-571. DOI: 10.3745/JIPS.01.0054.