376 research outputs found
General Framework of Reversible Watermarking Based on Asymmetric Histogram Shifting of Prediction Error
This paper presents a general framework for the reversible watermarking based on asymmetric histogram shifting of prediction error, which is inspired by reversible watermarking of prediction error. Different from the conventional algorithms using single-prediction scheme to create symmetric histogram, the proposed method employs a multi-prediction scheme, which calculates multiple prediction values for the pixels. Then, the suitable value would be selected by two dual asymmetric selection functions to construct two asymmetric error histograms. Finally, the watermark is embedded in the two error histograms separately utilizing a complementary embedding strategy. The proposed framework provides a new perspective for the research of reversible watermarking, which brings about many benefits for the information security
Prediction-error of Prediction Error (PPE)-based Reversible Data Hiding
This paper presents a novel reversible data hiding (RDH) algorithm for
gray-scaled images, in which the prediction-error of prediction error (PPE) of
a pixel is used to carry the secret data. In the proposed method, the pixels to
be embedded are firstly predicted with their neighboring pixels to obtain the
corresponding prediction errors (PEs). Then, by exploiting the PEs of the
neighboring pixels, the prediction of the PEs of the pixels can be determined.
And, a sorting technique based on the local complexity of a pixel is used to
collect the PPEs to generate an ordered PPE sequence so that, smaller PPEs will
be processed first for data embedding. By reversibly shifting the PPE histogram
(PPEH) with optimized parameters, the pixels corresponding to the altered PPEH
bins can be finally modified to carry the secret data. Experimental results
have implied that the proposed method can benefit from the prediction procedure
of the PEs, sorting technique as well as parameters selection, and therefore
outperform some state-of-the-art works in terms of payload-distortion
performance when applied to different images.Comment: There has no technical difference to previous versions, but rather
some minor word corrections. A 2-page summary of this paper was accepted by
ACM IH&MMSec'16 "Ongoing work session". My homepage: hzwu.github.i
Steganalytic Methods for the Detection of Histogram Shifting Data Hiding Schemes
Peer-reviewedIn this paper, several steganalytic techniques designed to detect the existence of hidden messages using histogram shifting schemes are presented. Firstly, three techniques to identify specific histogram shifting data hiding schemes, based on detectable visible alterations on the histogram or abnormal statistical distributions, are suggested. Afterwards, a general technique capable of detecting all the analyzed histogram shifting data hiding methods is suggested. This technique is based on the effect of histogram shifting methods on the ¿volatility¿ of the histogram of the difference image. The different behavior of volatility whenever new data are hidden makes it possible to identify stego and cover images
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