Real-Time implementation of a blind authentication method using self-synchronous speech watermarking

A blind speech watermarking scheme that meets hard real-time deadlines is presented and implemented. In addition, one of the key issues in these block-oriented watermarking techniques is to preserve the synchronization. Namely, to recover the exact position of each block in the mark extract process. In fact, the presented scheme can be split up into two distinguished parts, the synchronization and the information mark methods. The former is embedded into the time domain and it is fast enough to be run meeting real-time requirements. The latter contains the authentication information and it is embedded into the wavelet domain. The synchronization and information mark techniques are both tunable in order to allow a con gurable method. Thus, capacity, transparency and robustness can be con gured depending on the needs. It makes the scheme useful for professional applications, such telephony authentication or even sending information throw radio applications.

An empirical study of machine learning techniques applied to image watermarking

A study of how the machine learning technique, known as gentleboost, could improve different digital watermarking methods such as LSB, DWT, DCT2 and Histogram shifting.

High capacity audio watermarking using the high frequency band of the wavelet domain

This paper proposes a novel high capacity robust audio watermarking algorithm by using the high frequency band of the wavelet decomposition at which the human auditory system (HAS) is not very sensitive to alteration. The main idea is to divide the high frequency band into frames and, for embedding, to change the wavelet samples depending on the average of relevant frame¿s samples. The experimental results show that the method has a very high capacity (about 11,000 bps), without significant perceptual distortion (ODG in [¿1 ,0] and SNR about 30dB), and provides robustness against common audio signal processing such as additive noise, filtering, echo and MPEG compression (MP3).

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.

A novel semi-fragile forensic watermarking scheme for remote sensing images

Peer-reviewed

High capacity FFT-based audio watermarking

Peer-reviewed

High capacity robust audio watermarking scheme based on FFT and linear regression

Peer-reviewed

A robust audio watermarking scheme based on MPEG 1 Layer 3 Compression

This paper describes an audio watermarking scheme based on lossy compression. The main idea is taken from an image watermarking approach where the JPEG compression algorithm is used to determine where and how the mark should be placed. Similarly, in the audio scheme suggested in this paper, an MPEG 1 Layer 3 algorithm is chosen for compression to determine the position of the mark bits and, thus, the psychoacoustic masking of the MPEG 1 Layer 3compression is implicitly used. This methodology provides with a high robustness degree against compression attacks. The suggested scheme is also shown to succeed against most of the StirMark benchmark attacks for audio.

Robust watermarking scheme based on the JPEG2000 standard

Peer reviewed

Secure logarithmic audio watermarking scheme based on the human auditory system

Peer-reviewed

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.

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.