An early fire smoke detection method based on multi-features  fusion

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Journal of Dalian Maritime University ›› 2014, Vol. 40 ›› Issue (1) : 97-100.

An early fire smoke detection method based on multi-features fusion

WANG Lin, LI Ai-guo, WANG Xin-nian, YU Yan-feng

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Abstract

An early fire smoke detection method combined of color, background blurring and contour disorder features was proposed. A mixed Gaussian model of the background was established in RGB space, while the suspicious region was extracted by comparing the current frame with its background reference model. According to color model of early smoke in RGB and HIS space, the color feature of suspicious region was obtained. The background blurring feature was obtained by two-dimension discrete wavelet transformation, the disorder feature was computed by calculating ratio of pixels in suspicious region to the area of minimum bounding rectangle. The features extracted above were used to determine whether the suspicious region was smoky according to a joint judging rule. Experimental results on public test videos show that the proposed method can improve the accuracy of smoke detection and can be used in outdoor environment.

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early fire smoke detection / multi-features fusion / mixed Gaussian model

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WANG Lin, LI Ai-guo, WANG Xin-nian, YU Yan-feng. An early fire smoke detection method based on multi-features fusion[J]. Journal of Dalian Maritime University. 2014, 40(1): 97-100

References

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