Journal article

Smoke detection in video using wavelets and support vector machines

Jayavardhana Gubbi, Slaven Marusic, Marimuthu Palaniswami

FIRE SAFETY JOURNAL | ELSEVIER SCI LTD | Published : 2009

Abstract

Early warning systems are critical in providing emergency response in the event of unexpected hazards. Cheap cameras and improvements in memory and computing power have enabled the design of fire detectors using video surveillance systems. This is critical in scenarios where traditional smoke detectors cannot be installed. In such scenarios, it has been observed that the smoke is visible well before flames can be sighted. A novel method for smoke characterization using wavelets and support vector machines is proposed in this paper. Forest fire, tunnel fire and news channel videos have been used for testing the proposed method. The results are impressive with limited false alarms. The propose..

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Grants

Awarded by iOmniscient Ply Ltd, Sydney, Australia


Funding Acknowledgements

The authors acknowledge Dr. Rustom Kanga, iOmniscient Ply Ltd for data and feedback he provided during this work. This work was carried out under the DEST-ISL Project on Distributed Sensor Networks (CG080110) in collaboration with iOmniscient Ply Ltd, Sydney, Australia.