Smoke regions extraction based on two steps segmentation and motion detection in early fire

Wenlin Jian; Kaizhi Wu; Zirong Yu; Lijuan Chen

doi:10.1117/12.2285697

8 March 2018 Smoke regions extraction based on two steps segmentation and motion detection in early fire

Wenlin Jian, Kaizhi Wu, Zirong Yu, Lijuan Chen

Proceedings Volume 10609, MIPPR 2017: Pattern Recognition and Computer Vision; 1060919 (2018) https://doi.org/10.1117/12.2285697
Event: Tenth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2017), 2017, Xiangyang, China

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.

Citation Download Citation

Wenlin Jian, Kaizhi Wu, Zirong Yu, and Lijuan Chen "Smoke regions extraction based on two steps segmentation and motion detection in early fire", Proc. SPIE 10609, MIPPR 2017: Pattern Recognition and Computer Vision, 1060919 (8 March 2018); https://doi.org/10.1117/12.2285697

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