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On approach to vision based fire detection based on type-2 fuzzy clustering

Duong, H.D. and Nguyen, D.D. and Ngo, L.T. and Tinh, D.T. (2011) On approach to vision based fire detection based on type-2 fuzzy clustering. In: 2011 International Conference of Soft Computing and Pattern Recognition, SoCPaR 2011, 14 October 2011 through 16 October 2011, Dalian.

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Abstract

During the last ten years computer vision techniques have shown a great potential in solving the problem of automatic fire detection. Vision-based fire detection offers many advantages over the conventional methods that use smoke and heat detectors. This paper presents a novel approach for fire detection by modeling the structure of spatial of fire, this structure is considered in terms of the color intensity of fire pixels. Furthers the type-2 fuzzy clustering technique is applied to separate fire-color pixels into some clusters, then these clusters are used to model structure of fire. Experimental results show that our method is capable of detecting fire in early state of fire and weak light-intensity environment; and this method uses only information on a single image so it can be integrated into the surveillance system that used dynamic camera. © 2011 IEEE.

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculties > Faculty of Information Technology
Identification Number: 10.1109/SoCPaR.2011.6089094
Uncontrolled Keywords: Color intensity; Computer vision techniques; Conventional methods; Dynamic camera; Fire detection; Fuzzy clustering techniques; Single images; Surveillance systems; Type-2 fuzzy set; Vision based; Vision based fire detection; Computer vision; Fire detectors; Fuzzy clustering; Pixels; Security systems; Soft computing; Fires
Additional Information: Conference code: 87832. Language of original document: English.
URI: http://eprints.lqdtu.edu.vn/id/eprint/10132

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