Journal
3RD INTERNATIONAL CONFERENCE ON INNOVATION IN ARTIFICIAL INTELLIGENCE (ICIAI 2019)
Volume -, Issue -, Pages 248-252Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.1145/3319921.3319962
Keywords
fire detection; substation; smoke detection; color characteristics
Categories
Funding
- technology project of State Grid Corporation of China
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In this paper, a fire detection method based on color features, wavelet analysis, and convolution neural network is proposed. Firstly, the candidate region of flame is extracted by color segmentation method, and then the candidate region of smoke is generated by the background fuzzy model based on wavelet analysis. Then the candidate region is filtered by the trained CNN model, and the position of flame and smoke in a picture is located. Finally, a large number of fire pictures in different scenes are used to test the algorithm. The results show that this method can detect the location of flame and smoke accurately and quickly from images or videos, and can be applied to fire detection tasks in substation scenarios.
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