Forest Fire Detection System
D. Sathya, Assistant Professor II, Department of CSE, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
Manuscript received on 28 September 2019 | Revised Manuscript received on 10 November 2019 | Manuscript Published on 22 November 2019 | PP: 1138-1142 | Volume-8 Issue-6S3 September 2019 | Retrieval Number: F11890986S319/19©BEIESP | DOI: 10.35940/ijeat.F1189.0986S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The forest is one of the most important wealth of every country. The forest fires destroys the wildlife habitat, damages the environment, affects the climate, spoils the biological properties of the soil, etc. So the forest fire detection is a major issue in the present decade. At the same time the forest fire have to be detected as fast as possible. In the proposed method, a color spatial segmentation, temporal segmentation, global motion compensation, Support Vector Machine (SVM) classifications are used to detect the fire and to segment the fire from the video sequence. The method is implemented over the two real time data sets. The proposed method is most suitable for segmenting fire events over unconstrained videos in real time.
Keywords: Fire-like Pixel Detector, Regions of Interest, Support Vector Machine, Temporal Segmentation.
Scope of the Article: System Integration