An image information hiding algorithm based on grey system theory

SUMMARY On the basis of grey system theory, an image information hiding algorithm is proposed in this paper. First, to choose the blocks of rich texture, a method based on two-dimensional grey relational analysis is designed; making use of the improved GM(1,1) prediction model, the secret image is compressed losslessly, and then scrambled by means of time-division multiplexing method in communication theory. Block discrete cosine transform is applied to the chosen blocks, and coefficients of mid frequencies are chosen as the embedded data, whereas the embedding intensity is determined on the basis of human visual system, and the embedding capacity of sub-blocks can be controlled by its two-dimensional grey relational grade adaptively. The experiment results show that the algorithm cannot only achieve satisfactory invisibility and robustness, but also improve the payload of the cover image, and meanwhile solve the problem that the small capacity of traditional algorithms in transform domain efficiently. Copyright © 2013 John Wiley & Sons, Ltd.

[1]  Liu Yi,et al.  Grey Distance Information Approach for Parameter Estimation of Small Samples , 2008, IEEE Transactions on Instrumentation and Measurement.

[2]  Morteza Khademi,et al.  An adaptive scheme for compressed video steganography using temporal and spatial features of the video signal , 2009 .

[3]  Liang Zhang,et al.  A High-Capacity Steganography Scheme for JPEG2000 Baseline System , 2009, IEEE Transactions on Image Processing.

[4]  H. B. Kekre,et al.  Performance comparison of DCT and Walsh transform for steganography , 2010, ICWET.

[5]  Jiwu Huang,et al.  Edge Adaptive Image Steganography Based on LSB Matching Revisited , 2010, IEEE Transactions on Information Forensics and Security.

[6]  Chin-Chen Chang,et al.  Lossless Data Embedding With High Embedding Capacity Based on Declustering for VQ-Compressed Codes , 2007, IEEE Transactions on Information Forensics and Security.

[7]  Min Wu,et al.  Data hiding in image and video .II. Designs and applications , 2003, IEEE Trans. Image Process..

[8]  Chia-Chen Lin,et al.  DCT-based Reversible Data Hiding Scheme , 2010 .

[9]  Sheng Zhong,et al.  An efficient identity‐based protocol for private matching , 2011, Int. J. Commun. Syst..

[10]  Pradeep M. Patil,et al.  Robust and secured image-adaptive data hiding , 2012, Digit. Signal Process..

[11]  Jung-Shian Li,et al.  A hidden mutual authentication protocol for low-cost RFID tags , 2011, Int. J. Commun. Syst..

[12]  Xin-ping Xiao,et al.  A novel algorithm of image denoising based on the grey absolute relational analysis , 2009, 2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009).

[13]  Wei Su,et al.  Robust Lossless Image Data Hiding Designed for Semi-Fragile Image Authentication , 2008, IEEE Transactions on Circuits and Systems for Video Technology.

[14]  Min Wu,et al.  Data hiding in image and video .I. Fundamental issues and solutions , 2003, IEEE Trans. Image Process..

[15]  Keith Harrow The Bounded Arithmetic Hierarchy , 1978, Inf. Control..