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Improving GFR steganalysis features by using Gabor symmetry and weighted histograms (IH & MMSec 2017)

02/08/2018 - Image Steganology

C. Xia, Q. X. Guan, X. F. Zhao, Z. J. Xu, Y. Ma                                          

ABSTRACT

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.

Cite the paper as:

[1] C. Xia, Q. X. Guan, X. F. Zhao, Z. J. Xu, Y. Ma. Improving GFR steganalysis features by using Gabor symmetry and weighted histograms. In Proc. 5th ACM Workshop on Information Hiding and Multimedia Security (IH & MMSec 2017), Philadelphia, PA, USA, June 20-22, 2017, pp. 55-66 

IH 2017 Paper

code_IH17.rar