The key problem of fire detection is the recognition and classification for fire flame and interference. Support vector machine (SVM) is a potential data classification tool developed from statistical theory. Aiming at the shortcomings of traditional fire detection, An image fire detection algorithm based on support vector machine is presented. The algorithm overcomes the disadvantages of neural network such as over learning, trapping in local minimum easily etc., and overcomes the complexity of doing a lot of experiments and statistical analysis to obtain recognition threshold. The experiment results show that the image fire detection algorithm based on SVM has high accuracy and notable effect on solving the recognition problem of small samples and nonlinear problem.
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