Early Smoke Detection in Outdoor Space by Spatio-Temporal Clustering Using a Single Video Camera

Chapter
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 234)

Abstract

Video surveillance systems are increasingly being used to monitor urban areas and the landscape. Cameras have been proven near buildings, on bridges, ships, into tunnels. One important application of video surveillance system is the early smoke detection in the outdoor space for alarm generation. A novel video-based method of smoke detection by spatio-temporal clustering involves three developing stages. The first stage connects with any motion detection within a scene. The second stage is based on a color-texture analysis of moving regions to find smoke-like regions. Considering the complex nature of smoke (semi-transparency, spectrum overlapping, randomly motion changes) these two stages are not enough for decision making about early alarm generation. The third stage is enhanced by a spatio-temporal clustering of moving regions with a turbulence parameter connecting with fractal properties of smoke. A spatio-temporal data permit to track effectively a smoke propagation in the outdoor space by using the designed real-time software. Experimental results show that the proposed set of spatial and temporal features well discriminates smoke and non-smoke regions in outdoor scenes with a complex background.

Keywords

Smoke detection Surveillance Turbulence Video Sequences  

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Siberian State Aerospace UniversityKrasnoyarskRussian Federation
  2. 2.Siberian State Aerospace University KonstantinRussia

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