Abstract:
Fire detection system in the surveillance system
monitors the indoor environment and issues alarm as part of the
early warning mechanism with ultimate goal to provide an alarm
at early stage before the fire become uncontrollable.
Conventional fire detection systems suffer from the transparent
delay from the fire to the sensor which is looking at a point. The
reliability of the fire detection system mainly depends on the
positional distribution of the sensors. This paper proposes novel
method of fire detection by processing image sequence acquired
from a video. The proposed video based fire-detection system
uses adaptive background subtraction to detect foreground
moving object and then verified by the rule based fire color
model to determine whether the detected foreground object is a
fire or not. YCbCr color space is used to model the fire pixel
classification. In addition to the motion and color the detected
fire candidate regions are analyzed in temporal domain to detect
the fire flicker. Some Morphological operations are used to
enhance the features of detected fire candidate region. All of the
above clues are combining to form the fire detection system. The
performance of the proposed algorithm is tested on two sets of
videos comprising the fire, fire colored object and non-fire. The
experimental results show that the proposed system is very
successful in detecting fire and /or flames.
Citation:
A. E. Gunawaardena, R. M. M. Ruwanthika and A. G. B. P. Jayasekara, "Computer vision based fire alarming system," 2016 Moratuwa Engineering Research Conference (MERCon), 2016, pp. 325-330, doi: 10.1109/MERCon.2016.7480162.