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

Very High Embedding Capacity Algorithm for Reversible Image Watermarking

Reversible image watermarking enables the embedding of copyright or useful information in a host image without any loss of information. Here a novel technique to improve the embedding capacity i.e. reversible watermarking using an adaptive prediction error expansion & pixel selection is proposed. This work is an improvement in conventional Prediction Error Expansion by adding two new techniques adaptive embedding & pixel selection. Instead of uniform embedding, here one or two bits of watermark are adaptively embed into the expandable pixels as per the regional complexity. Adaptive Prediction Error Expansion can obtain the embedded rate upto 1.3 bits per pixel as compared to the 1 BPP of conventional Prediction Error Expansion. Also an intermediate step of prediction error expansion is proposed to select relatively smooth pixels and ignore the rough ones. In other words, the rough pixels may remain unchanged, and only smooth pixels are expanded or shifted. Therefore compared with conventional Prediction Error Expansion, a more sharply distributed prediction error histogram is obtained i.e. , and a larger proportion of prediction-errors in the histogram are expanded to carry hidden data. So the amount of shifted pixels is diminished, which leads to a better image quality. With these improvements, this method performs better than conventional Prediction Error Expansion. It can embed larger payloads with less distortion (almost 30% greater than the conventional method). DOI: 10.17762/ijritcc2321-8169.150510

An Efficient Data Security System Using Reserve Room Approach on Digital Images for Secret Sharing

This paper presents enhancement of d ata protection system for secret communication through common network based on reversible data concealment in encrypted images with reserve room approach. In this paper was implemented for true color RGB image and reserve room approach under multi scale decomposition. The Blue plane will be chosen for hiding the secret text data. Then image is then separated into number of blocks locally and lifting wavelet will be used to detect approximation and detailed coefficients. Then approximation part is encrypted using chaos encryption method. The proposed encryption technique uses the key to encrypt an image and not only enhances the safety of secret carrier informa tion by making the information inaccessible to any intruder having a random method. After image encryption, the data hide r will conceal the secret data into the detailed coefficients which are reserved before encryption. Although encryption achieves certain security effects, they make the secret messages unreadable and unnatural or meaningless. This system is still enhanced with encrypt messages using a symmetric key method. This is the reason a new security approach called reversible data hiding arises. It is the art of hiding the existence of data in another transmission medium to achieve secret communication. The data hidi ng technique uses the adaptive LSB replacement algorithm for concealing the secret message bits into the encrypted image. In the data extraction module, the secret data will be extracted by using relevant key for choosing the encrypted pixe ls to extract th e data. By using the decryption keys, the image and extracted text data will be extracted from encryption to get the original informatio n. Finally the performance of this proposal in encryption and data hiding will be analyzed based on image and data recovery

A Review on Image mosaicing for secure Transmission of University Exam Question Paper

The rapid spread of the digital world nowadays which is powered by ever faster system demands greater speed and security. Real time to secure an image is a challenging task due to the processing time and computational requirement for RGB image. So, to cope with these concerns, many innovative techniques of image processing for data hiding are required. In this paper new data hiding scheme is proposed which is known as image mosaicing. Image mosaicing is the process of merging split images to produce a single and complete image of the document. For this technique two input images are required one is secret image and second is target image, by merging these two a new image is made called as a mosaic image. So, the creation of mosaic image and lossless recovery of secret input image for question paper security is presented in this paper

Reversible Data Hiding using Visual Cryptography: A Review

ABSTRACT: Data security and data integrity are the two challenging areas for research. There are so many research is progressing on the field like internet security, steganography, cryptography. Data hiding are a group of techniques used to put a secure data in a host media with small deterioration in host and the means to extract the secure data afterwards. Reversible data hiding is a technique to embed additional message into some distortion-unacceptable cover media, such as military or medical images, with a reversible manner so that the original cover content can be perfectly restored after extraction of the hidden message. The reversibility means not only embedding data but also original image can be precisely recovered in the extracting stage. Most hiding techniques perform data embedding by altering the contents of a host media. These types of data hiding techniques are thus irreversible. However in a number of domains such as military, legal and medical imaging although some embedding distortion is admissible, permanent loss of signal fidelity is undesirable. This highlights the need for Reversible (Lossless) data embedding techniques. This paper gives a review on various reversible data hiding techniques and also proposes a novel approach for reversible data hiding using visual cryptography. This involves no use of keys thus keeping the computation cost for encryption/decryption low. This scheme applies a method of vacating the room for data prior to the image encryption used to hide the secret data. By reversing the order of encryption and data hiding we overcome the difficulty of finding the room for data from already encrypted image

Protection of medical images and patient related information in healthcare: Using an intelligent and reversible watermarking technique

This work presents an intelligent technique based on reversible watermarking for protecting patient and medical related information. In the proposed technique ‘IRW-Med’, the concept of companding function is exploited for reducing embedding distortion, while Integer Wavelet Transform (IWT) is used as an embedding domain for achieving reversibility. Histogram processing is employed to avoid underflow/overflow. In addition, the learning capabilities of Genetic Programming (GP) are exploited for intelligent wavelet coefficient selection. In this context, GP is used to evolve models that not only make an optimal tradeoff between imperceptibility and capacity of the watermark, but also exploit the wavelet coefficient hidden dependencies and information related to the type of sub band. The novelty of the proposed IRW-Med technique lies in its ability to generate a model that can find optimal wavelet coefficients for embedding, and also acts as a companding factor for watermark embedding. The proposed IRW-Med is thus able to embed watermark with low distortion, take out the hidden information, and also recovers the original image. The proposed IRW-Med technique is effective with respect to capacity and imperceptibility and effectiveness is demonstrated through experimental comparisons with existing techniques using standard images as well as a publically available medical image dataset