Efficient digital image watermarking for mobile applications by optimising the spread spectrum technique

In recent years, there has been considerable interest in the development of audio watermarking techniques. To clarify the essential principles underlying a diversity of sophisticated algorithms, this chapter gives an overview of basic methods for audio watermarking, such as least significant bit (LSB) modification, phase coding, spread spectrum watermarking, cepstrum domain watermarking, wavelet domain watermarking, echo hiding, and histogram-based watermarking.

In the current digital era, patient data in the form of digital medical images in several hospitals are widely used. There are two important thin to use of digital medical images namely the ownership authority (integrity control) and the authenticity of the image (authentication), because digital medical images are very easily manipulated. To maintain the authority of ownership, it needs robust watermarking techniques in which the embedded data is not easily damaged if the image has been manipulated. Meanwhile, to detect the authenticity of the image, it needs fragile watermarking technique in which the embedded data is easily damaged if the image has been manipulated. In this paper, we implement Reed-Solomon code for robust watermark in wavelet domain and SHA-256 for fragile watermark in Hash Block Chaining. The proposed multiple watermarks can be implemented simultaneously on an image so that the integrity control and authenticity of the image detection can be applied at once.

This paper studied the characteristics of time and energy consumption of gear hobbing in batch production of small modulus gear. A method of integrating design of experiment, response surface method and multi-objective salp swarm algorithm (DOE/RSM/MMSA) is proposed for the complex optimization of machining parameters (namely hob rotation speed, cutting feed and depth of cut) in gear hobbing process. This paper uses three-level factorial design method to design gear hobbing experiments, and carries out mathematical and statistical analysis on the experimental results. It is found that cutting feed is the most significant machining parameter followed by hob rotation speed and depth of cut to reduce processing time and energy consumption. The prediction model of processing time and energy consumption in gear hobbing process is obtained through response surface methodology. The relative error rates of the predicted value and the actual value of the processing time and energy consumption are 0.11% and 0.09% respectively, indicating the validity of the model. Multi-objective salp swarm algorithm is used to optimize the machining parameters to minimizing processing time and energy consumption. Finally, through the comparison with the existing research results, it is concluded that the optimized machining parameters have better processing effect to achieve minimized processing time and energy consumption, which shows the effectiveness and rationality of the method proposed, and provides references for the decision-making of machining parameters in workshop.

In this paper, we propose a complete architecture based on digital watermarking techniques to solve the issue of copyright protection and authentication for digital contents. We apply invisible watermarking to establish the copyright protection. Host and watermark images in the discrete wavelet transform (DWT) domain is considered with Human Vision System (HVS) models. In Images, the colored images (24 bits/pixel) that consist of RGB values of colors are a better environment for embedding data than the grey scaled images (8 bits/pixel), and usually data are hidden in the redundant bits which are usually the least significant bits(blue color) of the image since their change won't be noticeable by the human eye system. The simulation results show that the proposed method provides better performance under most attacks including JPEG compression. (6 pages)

Spread spectrum systems are being widely deployed today and are becoming more prevalent as most next-generation wireless systems are adopting it for their common air interface. These systems include the digital cellular IS-95 A/B/C, IEEE 802.11 wireless local area networks, as well as third-generation wideband code-division multiple access systems. In spread-spectrum systems, the receiver must synchronize on to the transmitted pseudo-noise (PN) code to obtain the improvement performance achieved through spreading. Since PN acquisition must process the spread-spectrum signal at a speed much faster than the transmitted data rate, its energy consumption can become significant and should be minimized for portable applications. Typically, either matched filters or serial correlators are used to acquire the PN code timing. This paper describes a hybrid PN acquisition architecture which employs both matched filters and serial correlators to achieve a lower energy consumption and fast acquisition time as compared to the traditional approaches of using either matched filters or serial correlators alone. The hybrid architecture has been implemented in RTL VHDL and synthesized down to gate level in a 0.5 micron CMOS library. Synthesis results show a factor of four reduction in energy for the hybrid scheme as compared to the matched filters architecture and a factor of two reduction in energy as compared to the serial architecture.

A wireless underwater acoustic communication system based on the combination of chirp modulation and direct-sequence spread-spectrum signaling is presented. The use of chirp signals takes advantage of the low Doppler sensitivity in the matched filter operation whereas the choice of pseudo noise (PN) sequences allows one to reduce narrowband interference arising from other users and self-interference due to multipath propagation. The system here described is made of a transmitter encoding the bits with linear chirps multiplied by PN sequences, and a rake receiver that allows one to positively exploit the energy present in the most significant propagation paths. Moreover a tracking procedure that allows an adaptation to the instantaneous Doppler shift has been devised and tested. Results, obtained on real data over a long-range shallow-water channel with a moving transmitting platform, are presented and discussed.

When a binary fingerprinting codeword is embedded into multimedia content by using a spread-spectrum (SS) watermarking scheme, it is difficult for colluders to perform a symbol-wise attack using their codewords. As discussed in regard to SS fingerprinting schemes, averaging their copies is a cost-effective attack from the signal processing point of view. If the number of colluders is known, an optimal detector can be used against an averaging attack with added white Gaussian noise. The detector first estimates the variance of additive noise, and then calculates correlation scores using a log-likelihood-based approach. However, the number of colluders is not usually known in a real situation. In this paper, we simplify the optimal detector by making statistical approximations and using the characteristics of the parameters for generating codewords. After that, we propose an orthogonal frequency division multiplexing-based SS watermarking scheme to embed the fingerprinting codeword into multimedia content. In a realistic situation, the signal embedded as a fingerprint is in principle attenuated by lossy compression. Because the signal amplitude in a pirated codeword is attenuated, we should adaptively estimate the parameters before calculating the scores. Different from the optimal detector, the simplified detector can easily accommodate changes in signal amplitude by examining the distorted codeword extracted from a pirated copy. We evaluate the performance of the simplified detector through simulation using digital images as well as codewords.

In order to more effectively monitor and interfere with enemy signals, it is particularly important to accurately and efficiently identify the intercepted signals and estimate their parameters in the increasingly complex electromagnetic environment. Therefore, in non-cooperative situations, it is of great practical significance to study how to accurately detect direct sequence spread spectrum (DSSS) signals in real time and estimate their parameters. The traditional time-delay correlation algorithm encounters the challenges such as peak energy leakage and false peak interference. As an alternative, this paper introduces a Pseudo-Noise (PN) code period estimation method utilizing a one-dimensional (1D) convolutional neural network based on the residual network (CNN-ResNet). This method transforms the problem of spread spectrum code period estimation into a multi-classification problem of spread spectrum code length estimation. Firstly, the In-phase/Quadrature(I/Q) two-way of the received DSSS signals is directly input into the CNN-ResNet model, which will automatically learn the characteristics of the DSSS signal with different PN code lengths and then estimate the PN code length. Simulation experiments are conducted using a data set with DSSS signals ranging from -20 to 10 dB in terms of signal-to-noise ratios (SNRs). Upon training and verifying the model using BPSK modulation, it is then put to the test with QPSK-modulated signals, and the estimation performance was analyzed through metrics such as loss function, accuracy rate, recall rate, and confusion matrix. The results demonstrate that the 1D CNN-ResNet proposed in this paper is capable of effectively estimating the PN code period of the non-cooperative DSSS signal, exhibiting robust generalization abilities.

According to the demand of spread spectrum signal processing in lower SNR conditions, a novel blind estimation algorithm of the pseudo-noise (PN) sequence for the direct sequence spread spectrum (DSSS) signal is proposed based on the similarities among the DSSS signals and the eigenanalysis technique. At first, through segmentation processing and average cross-correlation calculation, the starting symbol of PN sequence is determined. Next, by utilizing the eigenanalysis technique PN sequence can be estimated accurately without any information of the DSSS signal. Simulation results show that compared with the existing algorithms under the same condition, the proposed algorithm not only overcomes the partial-encode problem, but also improves estimation performance by 2dB. Therefore, the proposed algorithm achieves an accurate estimation of PN sequence in lower SNR conditions.

This scheme describes a procedure that uses the motion characteristics of the videos to calculate the embedding tolerance for imperceptible video watermarking in wavelet domain. This procedure exploits the perceptual properties of HVS and motion content of video sequence adoptively calculating the embedding tolerance of watermark in order to improve the imperceptibility of watermarking according to the content of video. The experiment results indicate that this method can effectively reduce the degradation in the video quality.

Image watermarking in wavelet domain has been emerged as an interesting area of research. However, classical wavelet transform, like DWT, lacks in providing directional information and is shift sensitive. These limitations can be overcome with the use of NSCT (Nonsubsampled contourlet transform), which is shift invariant and provides rich directional information. Therefore, in this work, we propose NSCT based image watermarking using MSVD (Multiresolution singular value decomposition). High directionality of NSCT provides better reconstruction of watermarked images, whereas MSVD provides invariance against geometrical attacks. Experiments have been performed over benchmark datasets. Qualitative and quantitative analysis in terms of PSNR (Peak signal to noise ratio) and CC (Correlation coefficients) shows the effectiveness of the proposed approach.

An SVD-based image watermarking in wavelet domain using SVR and PSO

The massive spreading of broadband networks and new developments in digital technology has made ownership protection and authorisation of digital multimedia a very important issue. The reason is the availability of powerful tools for editing, lossless copying and transmission of digital multimedia such as images. Image watermarking is now an effective solution for the problem of authentication and protection of copyrighted image content. In this paper, discrete wavelet transform DWT-based watermarking technique is proposed in which mean energy of the each of 32 × 32 block in the CH and CV subbands is calculated and range of coefficients that exceed the mean energy of the block are selected for watermark embedding. Watson perceptual distortion control model is considered to keep the perceptual quality of the image and genetic programming GP is used to provide optimum watermarking level for the selected coefficients. The results show that there is almost no difference between original and watermarked image demonstrating key feature of imperceptibility. The technique has been tested and proves to be effective against a set of malicious attacks.

Spread spectrum watermarking (SSW) is one of the most widespread watermarking methods. In this paper, the characterization of the SSW from the information theoretic point of view is performed. Previous works on channel capacity analysis of watermarking systems are reviewed. Since SSW method is designed so that the host signal is unknown to the embedding encoder, Costa's results for capacity analysis of watermarking systems are not directly applicable. In this paper, watermarking embedding and detection is modeled as a channel that transmits information in the presence of noise of host and channel capacity analysis of that model is derived and the most reliable transmission rate of hidden information obtained. In addition, channel capacity for the case of presence of additive noise in the watermark channel is derived and robustness of the SSW against additive noise examined

At present, the spread spectrum (SS) sequences used in watermark include i.i.d. random sequences and the sequences used in SS communications. They appear earlier than digital watermark. Almost no researchers pay attention to whether they are really fit for watermark. In this paper, we compare the SS watermark channel and the traditional SS communication channel. We find out that their correlation property is different. Considering cropping and translation attacks, we define watermark auto- and cross-correlation and propose Loose Autocorrelation and Tight Cross-Correlation (LAC&TCC) properties for SS watermark. The LAC&TCC properties are that, whether or not synchronized, the autocorrelation is equal or close to 1 and the cross-correlation is equal or close to 0. Accordingly, the peak correlation is divided into the peak autocorrelation Ra(l) and the peak cross-correlation Rc(l). We establish the lower bound of Rc(l) and the higher bound of Ra(l), respectively. The two bounds indicate that, no matter how small the cover is reserved, the extractor can always find a threshold to distinguish auto- and cross-correlation in theory.