Entropy-functional-based online adaptive decision fusion framework with application to wildfire detection in video

Osman Gunay; Behçet Ugur Toreyin; Kivanc Kose; A. Enis Cetin

doi:10.1109/TIP.2012.2183141

Entropy-functional-based online adaptive decision fusion framework with application to wildfire detection in video

Osman Gunay^*, Behçet Ugur Toreyin, Kivanc Kose, A. Enis Cetin

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

78 Citations (Scopus)

Abstract

In this paper, an entropy-functional-based online adaptive decision fusion (EADF) framework is developed for image analysis and computer vision applications. In this framework, it is assumed that the compound algorithm consists of several subalgorithms, each of which yields its own decision as a real number centered around zero, representing the confidence level of that particular subalgorithm. Decision values are linearly combined with weights that are updated online according to an active fusion method based on performing entropic projections onto convex sets describing subalgorithms. It is assumed that there is an oracle, who is usually a human operator, providing feedback to the decision fusion method. A video-based wildfire detection system was developed to evaluate the performance of the decision fusion algorithm. In this case, image data arrive sequentially, and the oracle is the security guard of the forest lookout tower, verifying the decision of the combined algorithm. The simulation results are presented.

Original language	English
Article number	6126027
Pages (from-to)	2853-2865
Number of pages	13
Journal	IEEE Transactions on Image Processing
Volume	21
Issue number	5
DOIs	https://doi.org/10.1109/TIP.2012.2183141
Publication status	Published - May 2012
Externally published	Yes

Funding

Manuscript received January 23, 2011; revised May 06, 2011 and November 12, 2011; accepted December 14, 2011. Date of publication January 09, 2012; date of current version April 18, 2012. This work was supported in part by the Scientific and Technical Research Council of Turkey (TUBITAK) under Grant 111E057 and Grant 105E191, by the European Commission 7th Framework Program under Grant FP7-ENV-2009-1244088 FIRESENSE (Fire Detection and Management through a Multi-Sensor Network for the Protection of Cultural Heritage Areas from the Risk of Fire and Extreme Weather Conditions). The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Arun A. Ross.

Funders	Funder number
European Commission 7th Framework Program	FP7-ENV-2009-1244088 FIRESENSE
TUBITAK	105E191, 111E057
Seventh Framework Programme	244088
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu

Keywords

Active learning
decision fusion
entropy maximization
online learning
projections onto convex sets
wildfire detection using video

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10.1109/TIP.2012.2183141

Cite this

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Entropy-functional-based online adaptive decision fusion framework with application to wildfire detection in video

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Keywords

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