Hybrid fire detection using hidden Markov model and luminance map

被引:16
作者
Wang, Liqiang [1 ]
Ye, Mao [2 ]
Ding, Jian
Zhu, Yuanxiang
机构
[1] Univ Elect Sci & Technol China, Sch Engn & Comp Sci, Chengdu 611731, Peoples R China
[2] Univ Elect Sci & Technol China, CVLab, Chengdu 611731, Peoples R China
基金
中国国家自然科学基金;
关键词
FLAME DETECTION;
D O I
10.1016/j.compeleceng.2011.09.011
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Recently, fire detection is a hot research topic. Although many detection methods have been proposed, there exist high false alarms because of the interference of fire-colored moving object in the complex environments. In this paper, a hybrid method is proposed. First, we get the set of candidate fire regions. Then these candidate fire regions are analyzed to exclude the fire-colored moving object. Our contributions are using the hidden Markov model (HMM) based on spatio-temporal feature and the variance of luminance map motivated by visual attention, and combining both for fire detection. The wrong detection can be reduced greatly. Experiment results show our proposed method has a good performance and it is robust to be used in complex environment compared with previous algorithms. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:905 / 915
页数:11
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