[1]HE Shizhao,YANG Xuanfang,CHEN Xiaojuan.Comparisons between a support vector machine and BP neural network for video image fire detection[J].CAAI Transactions on Intelligent Systems,2011,6(4):339-343.
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Comparisons between a support vector machine and  BP neural network for video image fire detection

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 6 Number of periods: 2011 4 Page number: 339-343 Column: 学术论文—机器感知与模式识别 Public date: 2011-08-25
Title:
Comparisons between a support vector machine and  BP neural network for video image fire detection
Author(s):
HE Shizhao;  YANG Xuanfang;  CHEN Xiaojuan
College of Electrical and Information Engineering, Naval University of Engineering, Wuhan 430033, China
Keywords:
fire detection;  shape features;  SVM;  BP neural network
CLC:
TP18
DOI:
-
Abstract:
According to the theoretical differences between a back propagation (BP) network and support vector machine (SVM) in relation to fire detection, two kinds of video image fire detection methods based on a BP network and SVM, respectively, were constructed. Judging from color distribution of the flames, the objective regions were separated in both methods, and their shape features along with the changes in shape features were extracted as criteria. The performance of each method was compared and analyzed after conducting many experiments. The experimental results show that the SVM had a high convergence rate and needed fewer training samples. At the same time, fewer misjudgments of testing samples confirmed that the BP network was more suitable for solving complex internal mechanism problems due to its good mapping capability. 
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