A Novel Fuzzy-Based Smoke Detection System Using Dynamic and Static Smoke Features
Paper i proceeding, 2015

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.

motion block

fuzzy inference system

smoke detection

smoke features

Författare

Yashar Deldjoo

Chalmers, Signaler och system

F. Nazary

A. M. Fotouhi

2015 23rd Iranian Conference on Electrical Engineering

2164-7054 (ISSN)

Vol. 10 729-733

Ämneskategorier

Elektroteknik och elektronik

DOI

10.1109/IranianCEE.2015.7146309

ISBN

978-1-4799-1971-0

Mer information

Skapat

2017-10-07