Fire-Flame Detection Based on Fuzzy Finite Automation

This paper proposes a new fire-flame detection method using probabilistic membership function of visual features and Fuzzy Finite Automata (FFA). First, moving regions are detected by analyzing the background subtraction and candidate flame regions then identified by applying flame color models. Sin...

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Bibliographic Details
Main Authors: SunJae Ham, ByoungChul Ko, JaeYeal Nam
Format: Conference Proceeding
Language:English
Subjects:
Automata
background subtraction
Feature extraction
FFA
Fire-flame
Fires
Fuzzy logic
Mathematical model
Motion pictures
probabilistic membership function
Videos
Online Access:Request full text
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Description
Summary:This paper proposes a new fire-flame detection method using probabilistic membership function of visual features and Fuzzy Finite Automata (FFA). First, moving regions are detected by analyzing the background subtraction and candidate flame regions then identified by applying flame color models. Since flame regions generally have an irregular pattern continuously, membership functions of variance of intensity, wavelet energy and motion orientation are generate and applied to FFA. Since FFA combines the capabilities of automata with fuzzy logic, it not only provides a systemic approach to handle uncertainty in computational systems, but also can handle continuous spaces. The proposed algorithm is successfully applied to various fire videos and shows a better detection performance when compared with other methods.
ISSN:1051-4651
2831-7475
DOI:10.1109/ICPR.2010.953