JPEG隐写分析中GFR特征的进一步研究
Further Study on GFR Features for JPEG Steganalysis
摘要：
GFR（Gabor滤波器残差）特征，构建为直方图的量化残差得到的2D Gabor滤波器，可以实现竞争的检测性能对自适应JPEG隐写。在本文中，提出了一种改进的版本的GFR。首先，根据不同Gabor滤波器之间的对称性，提出了一种新的直方图合并方法，从而使特征更加紧凑和鲁棒。其次，提出了一种新的加权直方图方法，通过考虑残差值在量化区间中的位置，使特征对残差值的微小变化更加敏感。最后通过实验验证了所提方法的有效性。最后，我们设计了一个CNN来复制具有改进的GFR特征和集成分类器的检测器，从而优化了用于在JPEG相位感知特征中形成残差的滤波器的设计。
英文摘要：
The GFR (Gabor Filter Residual) features, built as histograms of quantized residuals obtained with 2D Gabor filters, can achieve competitive detection performance against adaptive JPEG steganography. In this paper, an improved version of the GFR is proposed. First, a novel histogram merging method is proposed according to the symmetries between different Gabor filters, thus making the features more compact and robust. Second, a new weighted histogram method is proposed by considering the position of the residual value in a quantization interval, making the features more sensitive to the slight changes in residual values. The experiments are given to demonstrate the effectiveness of our proposed methods. Finally, we design a CNN to duplicate the detector with the improved GFR features and the ensemble classifier, thus optimizing the design of the filters used to form residuals in JPEG-phase-aware features.
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