Open AccessEarly forest fire smoke detection based on aerial video
Author(s) -
Cang Nai-meng,
Wei Yu
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1684/1/012095
Subject(s) - smoke , fire detection , energy (signal processing) , artificial intelligence , environmental science , wavelet transform , computer science , remote sensing , computer vision , wavelet , geography , mathematics , engineering , statistics , meteorology , architectural engineering
The early detection of forest fire smoke has more research value than the detection of forest fire flames. This article mainly introduces the content of early forest fire smoke detection based on background blur model and aerial video. First, the background image of the video is extracted by establishing a background model. Then, through wavelet transform, the energy value of the background composite image is compared with the energy value of the target composite image when smoke appears, and the presence of smoke is detected by threshold processing. Experimental results show that the average recognition rate of smoke is as high as 96.94%.