Open AccessA Model‐Based Image Steganography Method Using Watson's Visual Model
Author(s) -
Fakhredanesh Mohammad,
Safabakhsh Reza,
Rahmati Mohammad
Publication year - 2014
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.14.0113.0171
Subject(s) - steganography , steganalysis , computer science , histogram , artificial intelligence , pattern recognition (psychology) , perception , similarity (geometry) , embedding , cosine similarity , image (mathematics) , discrete cosine transform , computer vision , neuroscience , biology
This paper presents a model‐based image steganography method based on Watson's visual model. Model‐based steganography assumes a model for cover image statistics. This approach, however, has some weaknesses, including perceptual detectability. We propose to use Watson's visual model to improve perceptual undetectability of model‐based steganography. The proposed method prevents visually perceptible changes during embedding. First, the maximum acceptable change in each discrete cosine transform coefficient is extracted based on Watson's visual model. Then, a model is fitted to a low‐precision histogram of such coefficients and the message bits are encoded to this model. Finally, the encoded message bits are embedded in those coefficients whose maximum possible changes are visually imperceptible. Experimental results show that changes resulting from the proposed method are perceptually undetectable, whereas model‐based steganography retains perceptually detectable changes. This perceptual undetectability is achieved while the perceptual quality — based on the structural similarity measure — and the security — based on two steganalysis methods — do not show any significant changes.