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S. D. Wang, Y. P. He, J. J. Zou, D. C. Zhou and J. Wang (2014) Journal Of Intelligent & Fuzzy Systems 26 267-275.
文章来源:SKLFS    作者:SKLFS    发布时间:2015-03-25

S. D. Wang, Y. P. He, J. J. Zou, D. C. Zhou and J. Wang (2014) Early smoke detection in video using swaying and diffusion feature. Journal/Journal Of Intelligent & Fuzzy Systems 26 267-275. [In English]
Web link: http://dx.doi.org/10.3233/ifs-120735
Keywords: Smoke detection; choquet fuzzy integral; centroid; gray Level; Co-occurrence Matrix; MOTION; IMAGE

Abstract: A method of early smoke detection in video using swaying and diffusion feature is presented in this paper. Firstly, in view of early smoke's swaying feature, choquet fuzzy integral was adopted to extract dynamic regions from video frames, and then, a swaying identification algorithm based on centroid calculation was used to distinguish candidate smoke region from other dynamic regions. Secondly, smoke diffusion makes different textures between the bottom region and the top region of smoke. This unique feature was used to differentiate smoke from other candidate smoke regions by Gray Level Co-occurrence Matrix. Experiments show that the proposed method is effective, robust, and has a performance of earlier smoke alarm. The processing rate of the smoke detection method achieves 25 frames per second with an image size of 320x240 pixels.

 
 
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S. D. Wang, Y. P. He, J. J. Zou, D. C. Zhou and J. Wang (2014) Journal Of Intelligent & Fuzzy Systems 26 267-275.
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