Mehdi Fallahpour

Reversible image data hiding based on gradient adjusted prediction

The present study illustrates a new lossless data hiding method for digital images using image prediction technique. In the proposed method which is based on gradient-adjusted prediction (GAP), first prediction errors are computed and then the error values are slightly modified through shifting the prediction errors. The modified errors are used for embedding the data. Experimental results of present research have demonstrated that the proposed method called shifted gradient-adjusted prediction error (SGAPE) is capable of hiding more secret data with absolutely high PSNR.

Efficient self-synchronised blind audio watermarking system based on time domain and FFT amplitude modification

Many audio watermarking schemes divide the audio signal into several blocks such that part of the watermark is embedded into each of them. One of the key issues in these block-oriented watermarking schemes is to preserve the synchronisation, i.e. to recover the exact position of each block in the mark recovery process. In this paper, a novel time domain synchronisation technique is presented together with a new blind watermarking scheme which works in the discrete Fourier transform (DFT or FFT) domain. The combined scheme provides excellent imperceptibility results whilst achieving robustness against typical attacks. Furthermore, the execution of the scheme is fast enough to be used in real-time applications. The excellent transparency of the embedding algorithm makes it particularly useful for professional applications, such as the embedding of monitoring information in broadcast signals. The scheme is also compared with some recent results of the literature.

High capacity audio watermarking using FFT amplitude interpolation

An audio watermarking technique in the frequency domain which takes advantage of interpolation is proposed. Interpolated FFT samples are used to generate imperceptible marks. The experimental results show that the suggested method has very high capacity (about 3kbps), without significant perceptual distortion (ODG about -0.5) and provides robustness against common audio signal processing such as echo, add noise, filtering, resampling and MPEG compression (MP3). Depending on the specific application, the tuning parameters could be selected adaptively to achieve even more capacity and better transparency.

Subjectively adapted high capacity lossless image data hiding based on prediction errors

This article reports on a lossless data hiding scheme for digital images where the data hiding capacity is either determined by minimum acceptable subjective quality or by the demanded capacity. In the proposed method data is hidden within the image prediction errors, where the most well-known prediction algorithms such as the median edge detector (MED), gradient adjacent prediction (GAP) and Jiang prediction are tested for this purpose. In this method, first the histogram of the prediction errors of images are computed and then based on the required capacity or desired image quality, the prediction error values of frequencies larger than this capacity are shifted. The empty space created by such a shift is used for embedding the data. Experimental results show distinct superiority of the image prediction error histogram over the conventional image histogram itself, due to much narrower spectrum of the former over the latter. We have also devised an adaptive method for hiding data, where subjective quality is traded for data hiding capacity. Here the positive and negative error values are chosen such that the sum of their frequencies on the histogram is just above the given capacity or above a certain quality.

High capacity, reversible data hiding in medical images

In this paper we introduce a highly efficient reversible data hiding technique. It is based on dividing the image into tiles and shifting the histograms of each image tile between its minimum and maximum frequency. Data are then inserted at the pixel level with the largest frequency to maximize data hiding capacity. It exploits the special properties of medical images, where the histogram of their non-overlapping image tiles mostly peak around some gray values and the rest of the spectrum is mainly empty. The zeros (or minima) and peaks (maxima) of the histograms of the image tiles are then relocated to embed the data. The grey values of some pixels are therefore modified. High capacity, high fidelity, reversibility and multiple data insertions are the key requirements of data hiding in medical images. We show how histograms of image tiles of medical images can be exploited to achieve these requirements. Compared with data hiding method in the whole image, our scheme can result in 30%–200% capacity improvement with still better image quality, depending on the medical image content.

High Capacity Method for Real-Time Audio Data Hiding Using the FFT Transform

This paper presents a very efficient method for audio data hiding which is suitable for real-time applications. The FFT magnitudes which are in a band of frequencies between 5 and 15 kHz are modified slightly and the frequencies which have a magnitude less than a threshold are used for embedding. Its low complexity is one of the most important properties of this method making it appropriate for real-time applications. In addition, the suggested scheme is blind, since it does not need the original signal for extracting the hidden bits. The Experimental results show that it has a very good capacity (5 kbps), without significant perceptual distortion and provides robustness against MPEG compression (MP3).

Reversible Data Hiding Based On H.264/AVC Intra Prediction

This paper proposes a novel high capacity reversible image data hiding scheme using a prediction technique which is effective for error resilience in H.264/AVC. In the proposed method, which is based on H.264/AVC intra prediction, firstly the prediction error blocks are computed and then the error values are slightly modified through shifting the prediction errors. The modified errors are used for embedding the secret data. The experimental results show that the proposed method, called shifted intra prediction error (SIPE), is able of hiding more secret data while the PSNR of the marked image is about 48 dB.

High capacity FFT-based audio watermarking

This paper proposes a novel high capacity audio watermarking algorithm to embed data and extract it in a bit-exact manner based on changing the magnitudes of the FFT spectrum. The key idea is to divide the FFT spectrum into short frames and change the magnitude value of the FFT samples based on the average of the samples of each frame. Using the average of FFT magnitudes makes it possible to improve the robustness, since the average is more stable against changes compared with single samples. In addition to good capacity, transparency and robustness, this scheme has three parameters which facilitate the regulation of these properties. Considering the embedding domain, audio watermarking techniques can be classified into time domain and frequency domain methods. In frequency domain watermarking [1-7], after taking one of the usual transforms such as the Discrete/Fast Fourier Transform (DFT/FFT) [4-6], the Modified Discrete Cosine Transform (MDCT) or the Wavelet Transform (WT) from the signal [7], the hidden bits are embedded into the resulting transform coefficients. In [4-6], which were proposed by the authors of this paper, the FFT domain is selected to embed watermarks for making use of the translation-invariant property of the FFT coefficients to resist small distortions in the time domain. In fact, using methods based on transforms provides better perceptual quality and robustness against common attacks at the price of increasing the computational complexity.

Lossless Image Data Embedding in Plain Areas

This letter presents a lossless data hiding scheme for digital images which uses an edge detector to locate plain areas for embedding. The proposed method takes advantage of the well-known gradient adjacent prediction utilized in image coding. In the suggested scheme, prediction errors and edge values are first computed and then, excluding the edge pixels, prediction error values are slightly modified through shifting the prediction errors to embed data. The aim of proposed scheme is to decrease the amount of modified pixels to improve transparency by keeping edge pixel values of the image. The experimental results have demonstrated that the proposed method is capable of hiding more secret data than the known techniques at the same PSNR, thus proving that using edge detector to locate plain areas for lossless data embedding can enhance the performance in terms of data embedding rate versus the PSNR of marked images with respect to original image.

Improving reversible histogram based data hiding schemes with an image preprocessing method

This paper presents two edge detectors and a preprocessing algorithm for histogram based data hiding schemes. The proposed technique takes advantage of the edge detectors to segment the image into plain and textured areas. The plain areas are selected for embedding where a histogram based scheme is used to embed information in these areas. Since in the plain areas, pixel intensities are close to each other, with the proposed preprocessing algorithm the number of shifted pixels for the same amount of hidden data capacity are decreased which results in a better transparency. To validate the efficiency of the technique two of the best known histogram based schemes which use prediction and interpolation are implemented and results are compared with and without the preprocessing scheme. The experimental results show that the histogram based methods with preprocessing algorithm, under the same capacity, have better transparency than the schemes without preprocessing. This scheme improves capacity, even by 200%, at equal distortion, or about 4 dB improvement in PSNR, at the same hiding capacity.