Please use this identifier to cite or link to this item:
Title: Fast and efficient method for fire detection using image processing
Authors: Celik, T. 
Keywords: Color modeling
Fire detection
Image processing
Image segmentation
Motion detection
Video processing
Issue Date: Dec-2010
Citation: Celik, T. (2010-12). Fast and efficient method for fire detection using image processing. ETRI Journal 32 (6) : 881-890. ScholarBank@NUS Repository.
Abstract: Conventional fire detection systems use physical sensors to detect fire. Chemical properties of particles in the air are acquired by sensors and are used by conventional fire detection systems to raise an alarm. However, this can also cause false alarms; for example, a person smoking in a room may trigger a typical fire alarm system. In order to manage false alarms of conventional fire detection systems, a computer vision-based fire detection algorithm is proposed in this paper. The proposed fire detection algorithm consists of two main parts: fire color modeling and motion detection. The algorithm can be used in parallel with conventional fire detection systems to reduce false alarms. It can also be deployed as a stand-alone system to detect fire by using video frames acquired through a video acquisition device. A novel fire color model is developed in CIE L*a*b* color space to identify fire pixels. The proposed fire color model is tested with ten diverse video sequences including different types of fire. The experimental results are quite encouraging in terms of correctly classifying fire pixels according to color information only. The overall fire detection system's performance is tested over a benchmark fire video database, and its performance is compared with the stateof- the-art fire detection method. © 2010 ETRI.
Source Title: ETRI Journal
ISSN: 12256463
DOI: 10.4218/etrij.10.0109.0695
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.


checked on Mar 23, 2019


checked on Mar 13, 2019

Page view(s)

checked on Mar 16, 2019

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.