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Forest Fire Detection using Machine Learning


R. Munieswari, K. Meenatchi


In this project, image processing based forest fire detection using YCbCr colour model is proposed. The proposed method adopts rule based colour model due to its less complexity and effectiveness. YCbCr colour space effectively separates luminance from chrominance compared to other colour spaces like RGB and rgb (normalized RGB). The proposed method not only separates fire flame pixels but also separates high temperature fire centre pixels by taking into account of statistical parameters of fire image in YCbCr colour space like mean and standard deviation. In this method, four rules are formed to separate the true fire region. Two rules are used for segmenting the fire region and other two rules are used for segmenting the high temperature fire centre region. The results obtained are compared with the other methods in the literature and shows higher true fire detection rate and less false detection rate. The proposed method can be used for real time forest fire detection with moving camera.



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Forest Fire Detection using Machine Learning. R. Munieswari, K. Meenatchi. 2024. IJIRCT, Volume 10, Issue 1. Pages 1-3.

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