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Title: Experimental study of video fire detection and its applications
Authors: Wong AKK 
Fong, NK 
Keywords: Recognition
Video fire detection
Issue Date: 2014
Publisher: Elsevier
Source: Procedia engineering, 2014, v. 71, p. 316-327 How to cite?
Journal: Procedia engineering 
Abstract: Video fire detection makes a significant contribution to the effectiveness of fire detection systems, particularly as regards fire in large spaces such as Atria, Tunnels, Hangers, Warehouses and E&M Plant rooms, as traditional fire detection systems have been shown to be ineffective in large spaces. For the development of video fire detection systems, spatial, spectral and temporal indicators are important in the identification of a fire source. In the development of video fire detection systems, flame image segmentation, recognition, tracking and predication are important areas of investigation. The multi - threshold algorithm of Otsu's method and the Rayleigh distribution analysis method (modified segmentation algorithm) can be used in the segmentation of flame images. The modified segmentation algorithm, however, can be strengthen to extract the pool fire images making use of the optimum threshold values. Following such segmentation the pool fire images centroid analysis technique can be used to recognize pool fire images by means of the Nearest Neighbor (NN) algorithm. The objective of this paper is to examine the modified segmentation and the NN algorithms.
Description: 2013 International Conference on Performance-Based Fire and Fire Protection Engineering, ICPFFPE 2013, Wuhan, 16-17 November 2013
EISSN: 1877-7058
DOI: 10.1016/j.proeng.2014.04.046
Rights: © 2014 The Authors. Published by Elsevier Ltd. Open access under CC BY-NC-ND license (
Peer-review under responsibility of School of Engineering of Sun Yat-Sun University
The following publication Wong, A. K. K., & Fong, N. K. (2014). Experimental study of video fire detection and its applications. Procedia engineering, 2014, 71, 316-327 is available at
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