Secure Binary Image Steganography Based on Minimizing the Distortion on the Texture
Abstract— Most state-of-the-art binary image steganographic techniques only consider the ﬂipping distortion according to the human visual system, which will be not secure when they are attacked by steganalyzers. In this paper, a binary image steganographic scheme that aims to minimize the embedding distortion on the texture is presented. We extract the complement, rotation, and mirroring-invariant local texture patterns < Final Year Projects 2016 > from the binary image ﬁrst. The weighted sum of crmiLTPs changes when ﬂipping one pixel is then employed to measure the ﬂipping distortion corresponding to that pixel. By testing on both simple binary images and the constructed image data set, we show that the proposed measurement can well describe the distortions on both visual quality and statistics.