Journal
OPTICS AND LASER TECHNOLOGY
Volume 47, Issue -, Pages 283-291Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.optlastec.2012.08.040
Keywords
Video fire detection; Generic color model; Cumulative geometrical independent; component analysis
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Funding
- Key Program of National Natural Science Foundation of China [51036007]
- Research Fund for the Doctoral Program of Higher Education of China [20103402110009]
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To improve the video fire detection rate, a robust fire detection algorithm based on the color, motion and pattern characteristics of fire targets was proposed, which proved a satisfactory fire detection rate for different fire scenes. In this fire detection algorithm: (a) a rule-based generic color model was developed based on analysis on a large quantity of flame pixels; (b) from the traditional GICA (Geometrical Independent Component Analysis) model, a Cumulative Geometrical Independent Component Analysis (C-GICA) model was developed for motion detection without static background and (c) a BP neural network fire recognition model based on multi-features of the fire pattern was developed. Fire detection tests on benchmark fire video clips of different scenes have shown the robustness, accuracy and fast-response of the algorithm. (C) 2012 Elsevier Ltd. All rights reserved.
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