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Fire-Flame Detection using Fuzzy Finite Automata  

Ham, Sun-Jae (계명대학교 컴퓨터공학과)
Ko, Byoung-Chul (계명대학교 컴퓨터공학과)
Publication Information
Journal of KIISE:Software and Applications / v.37, no.9, 2010 , pp. 712-721 More about this Journal
Abstract
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 continuous and an irregular pattern continuously, membership functions of variance of intensity, wavelet energy and motion orientation are generated 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.
Keywords
Fire-Flame detection; Fuzzy Finite Automata; Membership Function; Wavelet Transform; Motion vector; Skewness;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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