关键词: 隐马尔科夫模型, 支持向量机, 火焰识别, 匹配值

Abstract: In view of the high false alarm rate of image fire detection based on only Hidden Markov Model, a flame recognition algorithm based on Hidden Markov Model and Support Vector Machines is proposed. Flame candidate regions of captured image are detected with the motion detection and color analysis. Then after matching the candidate regions and flame models, HMM?is?used?to?calculate?the?similarity?values between?them. The matching values are input into SVM for second recognition. The experimental results show that compared with HMM, the HMM-SVM hybrid model can effectively reduce the rate of false positives, and improve the flame recognition accuracy.

Key words: Hidden Markov Model（HMM）, Support Vector Machines（SVM）, flame recognition, matching values