Steganalysis Feature Subspace Selection Based on Fisher Criterion
Chunfang Yang, Yi Zhang, Ping Wang, Xiangyang Luo, Fenlin Liu, Jicang Lu · 2017
With the dimension of steganalysis feature increases rapidly, ensemble steganalysis has become the trend, and its performance is greatly influenced by the selection of feature subspaces. In order to select feature subspaces more effectively to improve the performance of ensemble steganalysis, a feature subspace selection algorithm based on Fisher criterion is proposed. The proposed selection algorithm computes weight for each feature component according to its Fisher criterion value and a base probability value, then selects the feature components with the probabilities in proportion to their weights. When it is used to improve the ensemble steganalysis, the appropriate base probability value is searched by steps. Experimental results show that for J-UNIWARD (JPEG UNIversal WAvelet Relative Distortion) steganography, the proposed feature subspace selection algorithm can select more effective feature subspaces, and enhance the detection performance of GFR (Gabor Filter Residual) feature.