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A Novel Fuzzy-Based Smoke Detection System Using Dynamic and Static Smoke Features

Yashar Deldjoo (Institutionen för signaler och system) ; F. Nazary ; A. M. Fotouhi
2015 23rd Iranian Conference on Electrical Engineering (2164-7054). Vol. 10 (2015), p. 729-733.
[Konferensbidrag, refereegranskat]

Automatic fire surveillance is an important task for providing emergency response in the event of unexpected fire hazards. Early detection of fire can substantially mitigate the ecological or economical costs associated with a fire disaster. In this regard, as smoke usually always precedes fire, an intelligent smoke detection system is proposed that exploits a Fuzzy Inference System (FIS) in order to aggregate the features of smoke. In addition, robust smoke feature detection algorithms are implemented that take into account both dynamic and static characteristics of smoke. The smoke features include motion, motion orientation (estimated by using the accumulation of motion) for the former and texture for the latter. Experimental results on different video frames show that the proposed smoke detection system has robust performance on detecting the existence of smoke which shows the effectiveness of the proposed smoke detection system.

Nyckelord: smoke detection, smoke features, fuzzy inference system, motion block

Denna post skapades 2016-09-29. Senast ändrad 2017-09-28.
CPL Pubid: 242615


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Institutioner (Chalmers)

Institutionen för signaler och system (1900-2017)


Elektroteknik och elektronik

Chalmers infrastruktur