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An Adaptive Image Calibration Algorithm for Steganalysis

Xuyu Xiang1, Jiaohua Qin1, *, Junshan Tan1, Neal N. Xiong1

1 College of Computer Science and Information Technology, Central South University of Forestry & Technology, Changsha, 410114, China.
2 Department of Mathematics and Computer Science, Northeastern State University, OK, 74464, USA.

* Corresponding Author: Jiaohua Qin. Email: .

Computers, Materials & Continua 2020, 62(2), 963-976.


In this paper, a new adaptive calibration algorithm for image steganalysis is proposed. Steganography disturbs the dependence between neighboring pixels and decreases the neighborhood node degree. Firstly, we analyzed the effect of steganography on the neighborhood node degree of cover images. Then, the calibratable pixels are marked by the analysis of neighborhood node degree. Finally, the strong correlation calibration image is constructed by revising the calibratable pixels. Experimental results reveal that compared with secondary steganography the image calibration method significantly increased the detection accuracy for LSB matching steganography on low embedding ratio. The proposed method also has a better performance against spatial steganography.


Cite This Article

X. Xiang, J. Qin, J. Tan and N. N. Xiong, "An adaptive image calibration algorithm for steganalysis," Computers, Materials & Continua, vol. 62, no.2, pp. 963–976, 2020.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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