507 research outputs found

    Reversible Data Hiding Based on Improved Multilevel Histogram Modification of Pixel Differences

    Get PDF
    [[abstract]]The technique of reversible data hiding recovers the original image without distortion from a stego-image after the hidden data have been extracted. In this paper, we modify Zhao et al.’s method to propose a reversible data hiding algorithm based on improved histogram modification of pixel differences. Experimental results show that our proposed scheme uses improved multilevel histogram modification of pixel differences to achieve large hiding capacity and keep distortion low. We also adopt a histogram shifting technique to prevent overflow and underflow. Performance comparisons with other existing schemes are provided to demonstrate the superiority of the proposed scheme.[[notice]]補正完

    Steganalytic Methods for the Detection of Histogram Shifting Data Hiding Schemes

    Get PDF
    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

    Prediction-error of Prediction Error (PPE)-based Reversible Data Hiding

    Full text link
    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

    A Brief Review of RIDH

    Get PDF
    The Reversible image data hiding (RIDH) is one of the novel approaches in the security field. In the highly sensitive domains like Medical, Military, Research labs, it is important to recover the cover image successfully, Hence, without applying the normal steganography, we can use RIDH to get the better result. Reversible data hiding has a advantage over image data hiding that it can give you double security surely
    corecore