Early smoke detection in video using swaying and diffusion feature

Authors:
Shidong Wang;Yaping He;Ju Jia Zou;Dechuang Zhou;Jian Wang
Affiliations:
State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei, PR China and Information Network Center, Anhui University of Architecture, Hefei, PR China;School of Computing Engineering and Mathematics, University of Western Sydney, Australia;School of Computing Engineering and Mathematics, University of Western Sydney, Australia;State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei, PR China;State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei, PR China
Venue:
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Year:
2014

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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 320 × 240 pixels.