WSEAS Transactions on Environment and Development

Print ISSN: 1790-5079
E-ISSN: 2224-3496

Volume 13, 2017

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.

Volume 13, 2017

Real-Time Fire Detection in Camera Stream Using Statistical Analysis

AUTHORS: Kare Koplík, Peter Janků, Olga Vozniuk, Tomáš Dulík, Petr Snopek

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ABSTRACT: The paper describes a new algorithm designed to be fast and efficient for detecting fire. It is based on finding and investigating suspicious regions in each frame of video stream. The investigation consists of tracking regions across frames and performing statistical analysis on their trajectory. If the trajectory has characteristic similar to fire, a test on persistence is performed. If the fire-like characteristics persists, the alarm is triggered. This criterion enables to eliminate a large proportion of false alarms. Given it’s simplicity, the algorithm can be used separately in some environments and can improve existing algorithms as well.

KEYWORDS: Fire detection. Statistical analysis. Digital signal processing


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[8] A. E. Gunawaardena, R. M. M. Ruwanthika, A. G. B. P. Jayasekara, 'Computer Vision Based Fire Alarming System', in Proceedings of the 2nd International Moratuwa Engineering Research Conference (MERCon), pp. 325-330, Moratuwa, Sri Lanka, April 2016.

WSEAS Transactions on Environment and Development, ISSN / E-ISSN: 1790-5079 / 2224-3496, Volume 13, 2017, Art. #40, pp. 387-393

Copyright © 2017 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0

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