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Coverless Image Steganography Method Based on Feature Selection

Anqi Qiu1,2, Xianyi Chen1,2, Xingming Sun1,2,*, Shuai Wang3, Guo Wei4

School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
Jiangsu Engineering Centre of Network Monitoring, Nanjing, 210044, China.
Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina, 27599, USA.
Mathematics and Computer Science, University of North Carolina at Pembroke, North Carolina, 28372, USA.

*Corresponding Author: Xingming Sun. Email: email.

Journal of Information Hiding and Privacy Protection 2019, 1(2), 49-60.


A new information hiding technology named coverless information hiding is proposed. It uses original natural images as stego images to represent secret information. The focus of coverless image steganography method is how to represent image features and establish a map relationship between image feature and the secret information. In this paper, we use three kinds of features which are Local Binary Pattern (LBP), the mean value of pixels and the variance value of pixels. On this basis, we realize the transmission of secret information. Firstly, the hash sequence of the original cover image is obtained according to the description of the feature, and then the sequence of the secret information and the hash sequence of the original cover image are matched one by one. If the values are not the same, the image blocks of the original cover image are replaced according to the secret information to get the stego image. This paper explores the effect of three features on the visual quality of stego image. Experimental results show that the feature LBP is the best.


Cite This Article

A. Qiu, X. Chen, X. Sun, S. Wang and G. Wei, "Coverless image steganography method based on feature selection," Journal of Information Hiding and Privacy Protection, vol. 1, no.2, pp. 49–60, 2019.


cc 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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