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Smoke regions extraction based on two steps segmentation and motion detection in early fire
Author(s): Wenlin Jian; Kaizhi Wu; Zirong Yu; Lijuan Chen
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Paper Abstract

Aiming at the early problems of video-based smoke detection in fire video, this paper proposes a method to extract smoke suspected regions by combining two steps segmentation and motion characteristics. Early smoldering smoke can be seen as gray or gray-white regions. In the first stage, regions of interests (ROIs) with smoke are obtained by using two step segmentation methods. Then, suspected smoke regions are detected by combining the two step segmentation and motion detection. Finally, morphological processing is used for smoke regions extracting. The Otsu algorithm is used as segmentation method and the ViBe algorithm is used to detect the motion of smoke. The proposed method was tested on 6 test videos with smoke. The experimental results show the effectiveness of our proposed method over visual observation.

Paper Details

Date Published: 8 March 2018
PDF: 8 pages
Proc. SPIE 10609, MIPPR 2017: Pattern Recognition and Computer Vision, 1060919 (8 March 2018); doi: 10.1117/12.2285697
Show Author Affiliations
Wenlin Jian, Nanchang Hangkong Univ. (China)
Kaizhi Wu, Nanchang Hangkong Univ. (China)
Zirong Yu, Nanchang Hangkong Univ. (China)
Lijuan Chen, Nanchang Hangkong Univ. (China)


Published in SPIE Proceedings Vol. 10609:
MIPPR 2017: Pattern Recognition and Computer Vision
Zhiguo Cao; Yuehuang Wang; Chao Cai, Editor(s)

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