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Optical Engineering

Nonparametric membership functions and fuzzy logic for vision sensor-based flame detection
Author(s): Byoung Chul Ko; Hyun-Jae Hwang; Jae-Yeal Nam
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Paper Abstract

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.

Paper Details

Date Published: 1 December 2010
PDF: 11 pages
Opt. Eng. 49(12) 127202 doi: 10.1117/1.3520069
Published in: Optical Engineering Volume 49, Issue 12
Show Author Affiliations
Byoung Chul Ko, Keimyung Univ. (Korea, Republic of)
Hyun-Jae Hwang, Keimyung Univ. (Korea, Republic of)
Jae-Yeal Nam, Keimyung Univ. (Korea, Republic of)


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