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Volume 13
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10.3390/f13101719
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Article

Investigation of Recognition and Classification of Forest Fires Based on Fusion Color and Textural Features of Images

by
Cong Li
*,
Qiang Liu
,
Binrui Li
and
Luying Liu
School of Emergency Management and Safety Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China
*
Author to whom correspondence should be addressed.
Forests 2022, 13(10), 1719; https://doi.org/10.3390/f13101719
Submission received: 31 August 2022 / Revised: 11 October 2022 / Accepted: 17 October 2022 / Published: 18 October 2022
(This article belongs to the Section Natural Hazards and Risk Management)
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Abstract

An image recognition and classification method based on fusion color and textural features was studied. Firstly, the suspected forest fire region was segmented via the fusion RGB-YCbCr color spaces. Then, 10 kinds of textural features were extracted by a local binary pattern (LBP) algorithm and 4 kinds of textural features were extracted by a gray-level co-occurrence matrix (GLCM) algorithm from the suspected fire region. In terms of its application, a database of the forest fire textural feature vector of three scenes was constructed, including forest images without fire, forest images with fire, and forest images with fire-like interference. The existence of forest fires can be recognized based on the database via a support vector machine (SVM). The results showed that the method’s recognition rate for forest fires reached 93.15% and that it had a strong robustness with respect to distinguishing fire-like interference, which provides a more effective scheme for forest fire recognition.
Keywords: forest fire; Image recognition; color features; texture feature; gray level co-occurrence matrix forest fire; Image recognition; color features; texture feature; gray level co-occurrence matrix

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MDPI and ACS Style

Li, C.; Liu, Q.; Li, B.; Liu, L. Investigation of Recognition and Classification of Forest Fires Based on Fusion Color and Textural Features of Images. Forests 2022, 13, 1719. https://doi.org/10.3390/f13101719

AMA Style

Li C, Liu Q, Li B, Liu L. Investigation of Recognition and Classification of Forest Fires Based on Fusion Color and Textural Features of Images. Forests. 2022; 13(10):1719. https://doi.org/10.3390/f13101719

Chicago/Turabian Style

Li, Cong, Qiang Liu, Binrui Li, and Luying Liu. 2022. "Investigation of Recognition and Classification of Forest Fires Based on Fusion Color and Textural Features of Images" Forests 13, no. 10: 1719. https://doi.org/10.3390/f13101719

APA Style

Li, C., Liu, Q., Li, B., & Liu, L. (2022). Investigation of Recognition and Classification of Forest Fires Based on Fusion Color and Textural Features of Images. Forests, 13(10), 1719. https://doi.org/10.3390/f13101719

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