Affiliations: [a] Information Network Center, Anhui Jianzhu University, Hefei, PR China | [b] School of Computing Engineering and Mathematics, Western Sydney University, Australia
| [c] School of Computer and Information, Hefei University of Technology, Hefei, PR China | [d]
Anhui Institute of Scientific and Technical Information, Hefei, PR China | [e] School of Electronic and Information Engineering, Anhui Jianzhu University, Hefei, PR China | [f] State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei, PR China
Correspondence:
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Corresponding author. Shidong Wang, Information Network Center, Anhui Jianzhu University, Hefei, PR China. E-mail: wsd@ahjzu.edu.cn and Jian Wang, State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei, PR China. E-mail: wangj@ustc.edu.cn.
Abstract: Video smoke detection benefits life safety and environment protection. A method of video smoke detection using shape, color and dynamic texture features is presented in this paper. Firstly, an algorithm identifying cone geometry feature is used to distinguish conical region from dynamic regions. Secondly, conical regions are filtered by a color filtering algorithm to further test the candidate smoke region. Finally, a texture filtering algorithm is used to differentiate true smoke from candidate smoke regions. Experiments show that the proposed method is effective and it results in earlier and more reliable detection than the other two methods reported in the literature. The processing rate of the smoke detection method achieves 25 frames per second with an image size of 320×240 pixels.
