Abstract
In order to improve the effectiveness of flame image feature extraction, we propose a M-DTCWT (multidirectional dual-tree complex wavelet transform) complex frequency domain feature extraction method, combined with multi-feature fusion to achieve flame recognition in multiple scenes.First, the suspected flame region is detected by the RGB-HSI mixed color space. Secondly, Combining the filter bank in the M-DTCWT with the hourglass filter bank to construct more M-DTCWT in the diagonal direction, M-DTCWT decomposition on the suspected flame region image, and extracting the improved LBP (Local Binary Patterns)texture feature and circularity feature in the low frequency coefficients.Finally, through feature fusion, the SVM(Support Vector Machine) using the cross grid search method identifies the flame.A large number of experimental results verify the effectiveness of the algorithm.
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