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Video fire detection based on Gaussian Mixture Model and multi-color features

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Abstract

This paper proposes a new approach to detect fire from a video stream. It takes full advantage of the motion feature and color information of fire. Firstly, motion detection using Gaussian Mixture Model-based background subtraction is applied to extract moving objects from a video stream. Then, multi-color-based detection combining the RGB, HSI and YUV color space is employed to obtain possible fire regions. Finally, the results of the above two steps are combined to identify the accurate fire areas. The experimental results obtained by applying this method on different fire videos show that the proposed method can achieve better effectiveness, adaptability and robustness.

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Authors and Affiliations

  1. Tianjin University, Tianjin, 300072, China

    Xian-Feng Han, Jesse S. Jin, Ming-Jie Wang & Wei Jiang

  2. National Key Laboratory of Science and Technology on Aerospace Intelligent Control, Beijing, 100085, China

    Lei Gao & Li-Ping Xiao

Authors
  1. Xian-Feng Han
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  2. Jesse S. Jin
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  3. Ming-Jie Wang
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  4. Wei Jiang
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  5. Lei Gao
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  6. Li-Ping Xiao
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Correspondence to Xian-Feng Han.

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Han, XF., Jin, J.S., Wang, MJ. et al. Video fire detection based on Gaussian Mixture Model and multi-color features. SIViP 11, 1419–1425 (2017). https://doi.org/10.1007/s11760-017-1102-y

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  • DOI: https://doi.org/10.1007/s11760-017-1102-y

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