Feb 17, 2010 · The proposed steganalyzer models linear dependencies of image rows/columns in local neighborhoods using singular value decomposition transform ...
Experimental results show that the novel method has superior performance when compared with its counterparts in terms of spatial domain steganography.
The basic idea behind the proposed method is twofold: The first is the capability of modeling linear dependencies of image rows/columns in local neighborhoods ...
The proposed steganalyzer models linear dependencies of image rows/columns in local neighborhoods using singular value decomposition transform and employs ...
The proposed steganalyzer models linear dependencies of image rows/columns in local neighborhoods using singular value decomposition transform and employs ...
This paper is concerned with the universal (blind) image steganalysis problem and introduces a novel method to detect especially spatial domain ...
The idea of using SVD is that it provides modeling absolute and relative linear dependencies among image rows and columns. Thus any image which do not exhibit ...
SVD-Based Universal Spatial Domain Image Steganalysis | CoLab
colab.ws › articles › tifs.2010.2041826
This paper is concerned with the universal (blind) image steganalysis problem and introduces a novel method to detect especially spatial domain steganographic
Abstract—We propose a novel image steganalysis method, based on singular value decomposition and noise estimation, for the spatial domain LSB embedding ...
Steganalysis is the counterpart of steganography, as its goal is to detect the presence of hidden data. Steganography is the art of stealth communication.