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Color Models Aware Dynamic Feature Extraction for Forest Fire Detection Using Machine Learning Classifiers

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Abstract

The earth’s ecology is well balanced and protected by forests. On the other hand, forest fires affect forest resources, thus causing both economical and ecological losses. Hence, preserving forest resources from fires is very essential to reduce environmental disasters. Controlling forest fire at an early stage is necessary to control their spread. This requirement enforces the necessity of fast and reliable fire detection algorithms. In this paper, a color models aware dynamic feature extraction for forest fire detection using machine learning classifiers is proposed to achieve early detection of fire and reduced false alarm rate. The proposed algorithm extracts fire detection index, wavelet energy, and gray level co-occurrence matrix features from RGB, L*a*b*, and YCbCr color models respectively to train the machine learning classifiers. The performance of the proposed model is analysed using various machine learning algorithms and the standard classification metrics. The proposed color-aware feature extraction gives precision, recall, F1-score, and accuracy of 99, 95, 94, and 97% respectively for the K-nearest neighbourhood model. The support vector machine model delivers 98, 95, 93, and 96.5% respectively. The accuracy of the proposed model is improved by a minimum of 3%, and a maximum of 11% than other color models. Similarly, the false rate reduction is a minimum of 5% and a maximum of 17% than other models.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, St. Joseph’s College of Engineering, Chennai, India

    R. Avudaiammal

  2. Centre for Healthcare Advancement, Innovation and Research, SENSE, Vellore Institute of Technology, Chennai, India

    Vijayarajan Rajangam

  3. Department of Computer Science and Engineering, St. Joseph’s College of Engineering, Chennai, India

    Durai Raji V.

  4. Department of Electronics and Communication Engineering, Er. Perumal Manimekalai College of Engineering, Hosur, India

    Senthil Kumar S.

Authors
  1. R. Avudaiammal
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  2. Vijayarajan Rajangam
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  3. Durai Raji V.
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  4. Senthil Kumar S.
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Correspondence to Vijayarajan Rajangam.

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Avudaiammal, R., Rajangam, V., Durai Raji V. et al. Color Models Aware Dynamic Feature Extraction for Forest Fire Detection Using Machine Learning Classifiers. Aut. Control Comp. Sci. 57, 627–637 (2023). https://doi.org/10.3103/S0146411623060020

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