Journal
FIRE SAFETY JOURNAL
Volume 57, Issue -, Pages 44-57Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.firesaf.2012.07.005
Keywords
Video fire detection; Time-of-flight imaging; Multi-modal video analysis; Flame detection; Smoke detection; Video surveillance
Funding
- Ghent University
- Interdisciplinary Institute for Broadband Technology (IBBT)
- University College West Flanders
- Warrington Fire Ghent
- Car Park Fire Safety project
- Bilkent University (Department of Electrical and Electronics Engineering)
- Institute for the Promotion of Innovation by Science and Technology in Flanders (IWT)
- Fund for Scientific Research-Flanders (FWO-Flanders G.0060.09)
- Belgian Federal Science Policy Office (BFSPO)
- European Union
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In this paper a novel multi-modal flame and smoke detector is proposed for the detection of fire in large open spaces such as car parks. The flame detector is based on the visual and amplitude image of a time-of-flight camera. Using this multi-modal information, flames can be detected very accurately by visual flame feature analysis and amplitude disorder detection. In order to detect the low-cost flame related features, moving objects in visual images are analyzed over time. If an object possesses high probability for each of the flame characteristics, it is labeled as candidate flame region. Simultaneously, the amplitude disorder is also investigated. Also labeled as candidate flame regions are regions with high accumulative amplitude differences and high values in all detail images of the amplitude image's discrete wavelet transform. Finally, when there is overlap of at least one of the visual and amplitude candidate flame regions, fire alarm is raised. The smoke detector, on the other hand, focuses on global changes in the depth images of the time-of-flight camera, which do not have significant impact on the amplitude images. It was found that this behavior is unique for smoke. Experiments show that the proposed detectors improve the accuracy of fire detection in car parks. The flame detector has an average flame detection rate of 93%, with hardly any false positive detection, and the smoke detection rate of the TOF based smoke detector is 88%. (C) 2012 Elsevier Ltd. All rights reserved.
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