—As well-known, it is hard to detect LSB matching steganography when cover images are scans of photographs, which usually have high-frequency noise. This paper proposes a novel steganalysis method for this issue by making use of the following two facts: One is the local maxima of an image histogram decrease and the local minima increase after LSB matching steganography. As a result, the area between upper envelope and lower envelope of the histogram of a stego image will be smaller than that of a cover image. The other is LSB matching embedding in the spatial domain of an image corresponds to low-pass filtering of the histogram. So, there are some differences in the high order statistical moments of high frequencies of the histogram. Based on these facts, this paper constructs a novel feature vector to distinguish between stego and cover images. Experimental results show the proposed scheme has better performance than some state-of-the-art steganalyzers in the literature.
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