NDLI: Improving GFR Steganalysis Features by Using Gabor Symmetry and Weighted Histograms

Content Provider	ACM Digital Library
Author	Zhao, Xianfeng Xu, Zhoujun Guan, Qingxiao Ma, Yi Xia, Chao
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.
Starting Page	55
Ending Page	66
Page Count	12
File Format	PDF
ISBN	9781450350617
DOI	10.1145/3082031.3083243
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2017-06-20
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Steganalysis Weighted histograms Adaptive steganography Jpeg Gabor filters
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Improving GFR Steganalysis Features by Using Gabor Symmetry and Weighted Histograms