An efficient hybrid algorithm for fire flame detection

Seyed Amin Khatami, S. Mirghasemi, A. Khosravi, S. Nahavandi
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引用次数: 10

Abstract

Proposing efficient methods for fire protection is becoming more and more important, because a small flame of fire may cause huge problems in social safety. In this paper, an effective fire flame detection method is investigated. This fire detection method includes four main stages: in the first step, a linear transformation is applied to convert red, green, and blue (RGB) color space through a 3*3 matrix to a new color space. In the next step, fuzzy c-mean clustering method (FCM) is used to distinguish between fire flame and non-fire flame pixels. Particle Swarm Optimization algorithm (PSO) is also utilized in the last step to decrease the error value measured by FCM after conversion. Finally, we apply Otsu threshold method to the new converted images to make a binary picture. Empirical results show the strength, accuracy and fast-response of the proposed algorithm in detecting fire flames in color images.
一种有效的火焰检测混合算法
提出有效的消防方法变得越来越重要,因为一个小小的火焰可能会造成巨大的社会安全问题。本文研究了一种有效的火灾火焰检测方法。该火灾检测方法包括四个主要阶段:第一步,通过3*3矩阵,应用线性变换将红、绿、蓝(RGB)颜色空间转换为新的颜色空间。下一步,使用模糊c均值聚类方法(FCM)区分火焰和非火焰像素。最后一步采用粒子群优化算法(Particle Swarm Optimization algorithm, PSO)减小FCM变换后测量的误差值。最后,利用Otsu阈值法对转换后的图像进行二值化处理。实验结果表明,该算法在彩色图像火焰检测中具有较强的准确性和快速响应能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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