An Intelligent Fire-Detection Method Based on Image Processing

Abstract:

How to explore higher efficient and more credible fire-detection system by rapid development of computer and image processing techniques has aroused public’s extensive attention. To achieve fully automatic surveillance of fires, an intelligent fire detection method based on a multi-stage decision strategy of image processing is proposed. Both static and dynamic characteristics of the fire images sequence are considered. First of all time difference is used to process the gray-scale image to obtain the moving region in the scene, secondly apply color segmentation to get the ROI of fire region, thirdly shape features such as randomness of area size, edge likelihood are calculated to avoid some interference, at last the polygonal and irregular characters of flame like sharp corners and circularity are used to identified the fire. Experimental result shows the Fire-detection method presented in this paper could detect fire in the image sequence effectively, and it is capable of distinguishing Environmental light changes, background color interference and light false identification. Multi-stage decision strategy can improve the algorithm performance and reduce false-alarm rate. The proposed method has broad application prospects in the important military, social security, forest-fire alarm, commercial applications, and so on.

• Periodical: Advanced Engineering Forum (Volumes 2-3)
• Pages: 172-175
• DOI: https://doi.org/10.4028/www.scientific.net/AEF.2-3.172
• Online since: December 2011
• Authors: Ming Xiu Lin, Wen Lin Chen, Bao Song Liu, Li Na Hao
• Keywords: Color Model, Fire-Detection, Image Sequence, Shape Features, Time Difference

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