| Paper Details: | Downloads: 370 |
| Serial Number: | P1151052917
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| Title: | Multi-Sensor Fire Detection by Fusing Visual and LWIR Flame Features
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| Authors: | S. Verstockt and C. Hollemeersch and C. Poppe and P. Lambert and R. Van de Walle
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| Abstract: | This paper proposes a feature-based multi-sensor fi re detector operating on ordinary video and long wave infrared (LWIR) thermal images. The detector automatically extracts hot objects from the thermal images by dynamic background subtraction and histogram-based segmentation. Analogously, moving objects are extracted from the ordinary video by intensity-based dynamic background subtraction. These hot and moving objects are then further analyzed using a set of ame features which focus on the distinctive geometric, temporal and spatial disorder characteristics of ame regions. By combining the probabilities of these fast retrievable visual and
thermal features, we are able to detect the re at anearly stage. Experiments with video and LWIR sequences of re and non- re real case scenarios show good results and indicate that multi-sensor re analysis is very promising
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| Keywords: | fi re detection, multi-sensor, LWIR, moving object detection, disorder analysis, histogram-based segmentetion, ame features
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| Journal/Conference: | International Journal of Graphics, Vision and Image Processing
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| Volume: | 10
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| Issue: | 6
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| Submission Date: | 9/1/2010 12:00:00 AM
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| Review Date: | 10/1/2010 12:00:00 AM
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| Publishing Date: | 12/31/2010 12:00:00 AM
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| Article Downloads: | 370
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