Journal
FIRE SAFETY JOURNAL
Volume 44, Issue 3, Pages 322-329Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.firesaf.2008.07.006
Keywords
Fire detection; Vision sensor; Wavelet transform; Support vector machine; Luminance map
Funding
- Ministry of Commerce Industry and Energy of the Korean Government
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This paper proposes a new vision sensor-based fire-detection method for an early-warning fire-monitoring system. First, candidate fire regions are detected using modified versions of previous related methods, such as the detection of moving regions and fire-colored pixels. Next, since fire regions generally have a higher luminance contrast than neighboring regions, a luminance map is made and used to remove non-fire pixels. Thereafter, a temporal fire model with wavelet coefficients is created and applied to a two-class support vector machines (SVM) classifier with a radial basis function (RBF) kernel. The SVM classifier is then used for the final fire-pixel verification. Experimental results showed that the proposed approach was more robust to noise, such as smoke, and subtle differences between consecutive frames when compared with the other method. Crown Copyright (c) 2008 Published by Elsevier Ltd. All rights reserved.
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