Efficient Forest Fire Detection using Rule-Based Multi-color Space and Correlation Coefficient for Application in Unmanned Aerial Vehicles

• Nguyen Duc Anh,
• Pham Van Thanh,
• Doan Tu Lap,
• Nguyen Tuan Khai,
• Tran Van An,
• Tran Duc Tan,
• Nguyen Huu An,
• Dang Nhu Dinh,

Vol. 16, No. 2, February 28, 2022
10.3837/tiis.2022.02.002, Download Paper (Free):

• Forest Fire Detection
• rule-based
• RGB
• YCbCr
• Correlation Coefficient

Abstract

Forest fires inflict great losses of human lives and serious damages to ecological systems. Hence, numerous fire detection methods have been proposed, one of which is fire detection based on sensors. However, these methods reveal several limitations when applied in large spaces like forests such as high cost, high level of false alarm, limited battery capacity, and other problems. In this research, we propose a novel forest fire detection method based on image processing and correlation coefficient. Firstly, two fire detection conditions are applied in RGB color space to distinguish between fire pixels and the background. Secondly, the image is converted from RGB to YCbCr color space with two fire detection conditions being applied in this color space. Finally, the correlation coefficient is used to distinguish between fires and objects with fire-like colors. Our proposed algorithm is tested and evaluated on eleven fire and non-fire videos collected from the internet and achieves up to 95.87% and 97.89% of F-score and accuracy respectively in performance evaluation.

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