3 research outputs found

    Reversible Data Hiding Scheme with High Embedding Capacity Using Semi-Indicator-Free Strategy

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    A novel reversible data-hiding scheme is proposed to embed secret data into a side-matched-vector-quantization- (SMVQ-) compressed image and achieve lossless reconstruction of a vector-quantization- (VQ-) compressed image. The rather random distributed histogram of a VQ-compressed image can be relocated to locations close to zero by SMVQ prediction. With this strategy, fewer bits can be utilized to encode SMVQ indices with very small values. Moreover, no indicator is required to encode these indices, which yields extrahiding space to hide secret data. Hence, high embedding capacity and low bit rate scenarios are deposited. More specifically, in terms of the embedding rate, the bit rate, and the embedding capacity, experimental results show that the performance of the proposed scheme is superior to those of the former data hiding schemes for VQ-based, VQ/SMVQ-based, and search-order-coding- (SOC-) based compressed images

    A Survey on Data Hiding and Compression Schemes

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    ABSTRACT: Data hiding has a vital role to play in information security. Using a data hiding technique, secret information is hidden into cover digital content. Compression techniques and data hiding techniques received much less attention from the research community and from industry than cryptography. In past research many data hiding and image compression techniques has been developed, it works independent module in both sender and server side. These method cause low efficiency, less security and also the low bit rate scheme requires more time to encode. Both image compression and data hiding (EJDHC) using residual codebooks with side match vector quantization (SMVQ). In this survey is to discuss on data hiding schemas and compression techniques such as JPEG, JPEG 2000, vector quantization, VQ compression and SMVQ. KEYWORDS: Data hiding, image compression, side match vector quantization I.INTRODUCTION Data hiding is a process to hide data into cover media. The data hiding process links two sets of data and a set of the embedded data and another set of the cover media data. The relationship between these two sets of data characterizes different applications. In authentication phase embedded data are closely related to the cover media. High Data hiding in images [1] 8-bit grayscale images are selected as the cover media called as cover images. Cover images with the secret messages embedded in the images. For data hiding methods, the image quality refers to the quality of the images. Most of the hiding techniques is based on manipulating the least-signi7cant-bit (LSB) planes by directly replacing the LSBs of the cover image with the message bits. LSB methods typically achieve high capacity. Another technique introduced in Data hiding [6] also can be classified into three domains, namely, spatial, transformative, and compression. In the spatial domain each pixel in the cover image is modified to hide the secret information. In the transformative domain the cover image is transformed into coefficients using well-known transform techniques the integer wavelet transform and the integer discrete cosine transform. Then to embed the secret information, these coefficients are altered. In the compression domain, the cover image is compressed to save the storage and the bandwidth space of the embedded image. Then, the image-compressed codes are processed to hide the secret information. Many image-compressed data hiding schemes have been noted in the literature because the sizes of the compressed images will be much smaller than those of the original images before and after data hiding. Various compression techniques JPEG block truncatio

    Data Hiding and Its Applications

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    Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others
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