1 December 2010 Nonparametric membership functions and fuzzy logic for vision sensor-based flame detection
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This paper proposes an advanced fire-flame detection algorithm using camera images for a better performance than conventional sensor-based systems that are limited to a small area. First, candidate flame regions are detected from the captured images using a background model and flame-color model. After forming probability density functions for the intensity variation, wavelet energy, and motion orientation on a time axis, these probability density functions are changed into membership functions for fuzzy logic. Finally, the result function is made by defuzzification, and the probability value of a fire flame is estimated. The proposed algorithm is successfully applied to various fire videos, including indoor and outdoor fires, and shows a better detection performance when compared with other methods.
© (2010) Society of Photo-Optical Instrumentation Engineers (SPIE)
Byoung Chul Ko, Byoung Chul Ko, Hyun-Jae Hwang, Hyun-Jae Hwang, Jae-Yeal Nam, Jae-Yeal Nam, } "Nonparametric membership functions and fuzzy logic for vision sensor-based flame detection," Optical Engineering 49(12), 127202 (1 December 2010). https://doi.org/10.1117/1.3520069 . Submission:

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