Adaptive estimation of visual smoke detection parameters based on spatial data and fire risk index
Computer Vision and Image Understanding
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A smoke detection algorithm based on Discrete Wavelet Transform and Correlation Analysis is presented to distinguish smoke and other smoke-like objects, especially cloud. Firstly, based on Gaussian mixture model, the target region of image is picked up. Secondly, we use Discrete Wavelet Transform to discriminate low frequency content and high frequency content of the images. At last, the high frequency information is analyzed by correlation. According to this algorithm, the motion region is smoke or not can be distinguished effectively and reliably. Experimental results show that the proposed method can improve the accuracy of smoke detection and reduce the false alarm.