Open AccessA Flame Detection Method Based on Fusion Feature and SVM for Substation Inspection
Author(s) -
Jiankang Deng,
Chao Wei,
Guang Chen,
Xu Liang,
Bo Zhu
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 - 10.1088/1742-6596/1607/1/012021
Subject(s) - support vector machine , artificial intelligence , flicker , feature (linguistics) , pattern recognition (psychology) , computer science , fusion , feature extraction , computer vision , philosophy , linguistics , operating system
For the safety inspection of substation, this paper proposes a flame image detection method based on the combination of fusion feature and support vector machine (SVM). Firstly, the suspected flame area is detected by motion detection and flame color model. Then, four features of B-channel color variation coefficient, roughness, flicker frequency and flame area change rate are extracted. Finally, four features are sent to SVM to learn the flame classifier and used in video flame detection. The experimental results show that the proposed method can effectively identify the flame.