Title: Early video-based smoke detection in outdoor spaces by spatio-temporal clustering

Authors: Margarita N. Favorskaya; Konstantin E. Levtin

Addresses: Department of Informatics and Computer Techniques, Siberian State Aerospace University, Krasnoyarsky Rabochy av., 31, Krasnoyarsk, 660014, Russian Federation ' Department of Informatics and Computer Techniques, Siberian State Aerospace University, Krasnoyarsky Rabochy av., 31, Krasnoyarsk, 660014, Russian Federation

Abstract: The early smoke detection in outdoor spaces concerns to people's life and safety tasks. Such technique is necessary in video surveillance systems near building, on bridges, ships, into tunnels, in landscape monitoring systems, etc. We have suggested a novel video-based method of smoke detection by spatio-temporal clustering which involves three developing stages. The first stage connects with motion detection, the second stage is based on a colour and texture analysis of moving regions and the third stage is enhanced by a spatio-temporal clustering of moving regions with a turbulence parameter. A spatio-temporal volume data permits effectively dynamic track of smoke propagation in outdoor spaces using the designed real-time software. Experimental results show that the proposed set of spatial and temporal features always permits to detect the smoke and non-smoke moving objects in outdoor scenes with a complex background; the percent of true detected smoke elements in test video sequences is up to 89%.

Keywords: smoke detection; video surveillance; morphological processing; turbulence; fractal dimension; cluster analysis; video sequences; early detection; outdoor spaces; spatio-temporal clustering; motion detection; colour analysis; texture analysis; moving regions; dynamic tracking; smoke propagation; safety.

DOI: 10.1504/IJRIS.2013.057275

International Journal of Reasoning-based Intelligent Systems, 2013 Vol.5 No.2, pp.133 - 144

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 20 Oct 2013 *

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