Improve Watermark Security Via Wavelet Transfrom And Cdma Techniques

This paper presents a new robust hybrid multiple watermarking technique using fusion of discrete wavelet transforms (DWT), discrete cosine transforms (DCT), and singular value decomposition (SVD) instead of applying DWT, DCT and SVD individually or combination of DWT-SVD / DCT-SVD. For identity authentication purposes, multiple watermarks are embedded into the same medical image / multimedia objects simultaneously, which provides extra level of security with acceptable performance in terms of robustness and imperceptibility. In the embedding process, the cover image is decomposed into first level discrete wavelet transforms where the A (approximation/lower frequency sub-band) is transformed by DCT and SVD. The watermark image is also transformed by DWT, DCT and SVD. The S vector of watermark information is embedded in the S component of the cover image. The watermarked image is generated by inverse SVD on modified S vector and original U, V vectors followed by inverse DCT and inverse DWT. The watermark is extracted using an extraction algorithm. Furthermore, the text watermark is embedding at the second level of the D (diagonal sub-band) of the cover image. The security of the text watermark considered as EPR (Electronic Patient Record) data is enhanced by using encryption method before embedding into the cover. The results are obtained by varying the gain factor, size of the text watermark, and cover medical images. The method has been extensively tested and analyzed against known attacks and is found to be giving superior performance for robustness, capacity and reduced storage and bandwidth requirements compared to reported techniques suggested by other authors.

This paper presents a new technique for copyright protection and content authentication of satellite images. The novelty in the presented approach consists in designing a hybrid Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and hash function based digital image watermarking. In this study, two watermarks are embedded in the cover image called robust copyright watermark and fragile authentication watermark. The robust watermark is embedded in hybrid frequency and wavelet domain by applying DWT and DCT respectively. Such two steps embedding allows the proposed approach to provide better imperceptibility in harmony with the human visual system and offers higher robustness against signal processing attacks. Subsequently, the fragile watermark is embedded in a spatial domain using the hash function approach. The proposed hybrid watermarking technique has been tested on DubaiSat-2 images with 1 meter resolution. The experimental results show that the proposed method is robust against JPEG compression, rotation and resizing attacks. In addition, the multi-watermarked image has a good transparency and the fragile watermark is sensitive to any tampering.

Protection of copyright is a crucial issue in the data transmission and distribution. Considering the fact that there are different types of information available for misuse and manipulation by all the internet users it is necessary to establish the rules for copyright protection of a certain content. In this paper, special attention is given to the technical aspects of copyright protection. We took a digital image and a digital watermark into consideration. The original image has undergone a discrete wavelet transformation. Then, spread spectrum techniques were applied to the watermark. Digital watermark is then embedded into the original image. The aim of the paper is to present the comparison of results obtained using two different spread spectrum techniques in image watermarking.

In the current scenario, information transmission through digitize way is becoming a fast variant. But security between information transmissions is a measure concern. So digital watermarking technology provides a way for prevention of unauthorized access, distinguish information against illegal exploitations and allocations and copyright protection of the digitize data. Digital watermarking method should be robust, so it would be recoverable even if a part of this is altered. For embedding and extracting the watermark from the original image many different methods are provided. In this research paper watermarking is done by the combining the features of DWT (Discrete wavelet transformation) and Discrete Cosine Transformation (DCT). Red color component of the image is used for applying the DWT for embedding the watermark. After this, DCT is implemented on the 8×8 block of the image. Using this functionality a more secure and robust image is found

The success of internet technology transform the world of technology and fashioned our life such a lot easier. The matter of duplication and unauthorized use of information become a great threat within the field of technology. To beat these problems, techniques like digital watermarking, steganography and cryptography were introduced. The approach of embedding a secret data associated with the digital signal inside the signal itself is digital watermarking. For embedding and detecting the watermark different techniques are used; spatial domain techniques like Least Significant Bit (LSB) and Patch Work Algorithm, then the frequency domain techniques such as Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) and Discrete Fourier Transform (DFT) are some of them. Combination of DCT & DWT technique for digital watermarking is proposed here. The proposed methodology is implemented in MATLAB 2017a simulator and result is analysed using evaluation parameters like Peak Signal to Noise Ratio (PSNR) & Mean Square Error (MSE). PSNR value obtained for the case of watermarking using DWT is 27.46 and MSE value is 17.45. The value of PSNR for watermarking using DCT is 41.4 and for MSE the value is 0.67. The PSNR and MSE values obtained for watermarking using LSB technique is 50.55 and 0.58. The proposed method improves the watermarked image quality and the MSE & PSNR value obtained is 0.52 and 51.017 respectively.

Blind digital speech watermarking based on Eigen-value quantization in DWT

In this paper, a robust algorithm of digital image watermarking based on discrete wavelet transform is introduced It uses blind watermarking technique. Digital image watermarking is one such technology that has been developed to protect digital images from illegal manipulations. In particular, digital image watermarking algorithms which are based on the discrete wavelet transform have been widely recognized to be more prevalent than others. This is due to the wavelets' excellent spatial localization, frequency spread, and multi-resolution characteristics, which are similar to the theoretical models of the human visual system.

Code division multiple access (CDMA) promises to become the enabling technology for the future generation of satellite communications. For instance, CDMA is being used in Globalstar, Skybridge and is also proposed for the satellite component of UMTS. The evolution of satellite systems towards multimedia communications, necessitates not only wideband CDMA but also requires a hybrid code and time division multiple access (CTDMA) technique because of the packet nature of the data. In this paper, we give an overview of the challenges in designing a wideband CTDMA modem. As a first challenge, the wideband nature of the CDMA modem dictates that the tracking loops of the modem can no longer be executed in software but must be fully integrated in VLSI. Second, the packet based nature of the communication in a CTDMA modem requires ultra fast acquisition for each packet. The extremely low signal-to-noise ratio in satellite communications largely complicates this fast acquisition task.

Automatic Digital Modulation Recognition (ADMR) is becoming an interesting problem with various civil and military applications. In this paper, an ADMR algorithm in Multi-Carrier Code Division Multiple Access (MC-CDMA) systems using Discrete Transforms (DTs) and Mel-Frequency Cepstral Coefficients (MFCCs) is proposed. This algorithm uses various DT techniques such as the Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Discrete Sine Transform (DST) with MFCCs to extract features from the modulated signal and a Support Vector Machine (SVM) to classify the modulation orders. The proposed algorithm avoids over fitting and local optimal problems that appear in Artificial Neural Networks (ANNs). Simulation results shows the classifier is capable of recognizing the modulation scheme with high accuracy up to 90% - 100% using DWT, DCT and DST for some modulation schemes over a wide Signal-to-Noise Ratio (SNR) range in the presence of Additive White Gaussian Noise (AWGN) and Rayleigh fading channel, particularly at a low Signal-to-Noise ratios (SNRs).

Telemedicine is well known application where enormous amount of medical data need to be transferred securely over network and manipulate effectively. Security of digital data, especially medical images, becomes important for many reasons such as confidentiality, authentication and integrity. Digital watermarking has emerged as a advanced technology to enhance the security of digital images. The insertion of watermark in medical images can authenticate it and guarantee its integrity. The watermark must be generally hidden does not affect the quality of the medical image. In this paper, we propose blind watermarking based on Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD), we compare the performance of this technique with watermarking based DWT and SVD. The proposed method DWT, DCT and SVD comparatively better than DWT and SVD method.

Security and authentication of the people information is effectively provided through various watermarking algorithms. Most of the conventional watermarking algorithms have their own drawbacks in maintaining the quality and security of the image against various attacks. In order to overcome the above stated issues, a watermarking technique based on optimization is required for preserving image quality. In this paper, singular value decomposition (SVD) based digital image watermarking (DIW) scheme is proposed in hybrid discrete cosine transform (DCT) and discrete wavelet transform (DWT) using optimization algorithms like particle swarm optimization (PSO) and Jaya algorithm. The watermark image (WI) is embedded into low frequency DWT sub-band of DCT of cover image. PSO and Jaya algorithms are applied to improve the security threats and quality by assessing the fitness function. The work involves in utilizing the feature points in embedding of watermarks and analyzing the impact of various types of attacks with respect to image quality. The performance parameters like peak signal to noise ratio (PSNR), Structural Similarity Index (SSIM) and correlation coefficient of fitness function given by PSO and Jaya algorithm.

This paper deals with a new digital audio watermarking scheme based on Code Division Multiple Access (CDMA) technique. In digital communication, CDMA allows several users to share the same communication channel without interference from each other. The present work proposes to embed multiple watermarks in the same audio channel in order to increase the embedded information. Our main objective is to emphasize the impact of spreading codes on the performance of CDMA based watermarking system. This performance will be evaluated in terms of transparency, detection reliability of the watermark and its robustness against various disturbances.

In this paper, we propose a new algorithm of image watermarking based on Discrete Wavelet Transform (DWT) including a function for pixels movement. The proposed algorithm uses DWT of two levels in order to compact a higher energy in component LL1, and Contrast Sensitivity Function (CSF) to improve the invisibility and robustness, the new Function of Pixel Movement (PMF) is applied to increase the security properties. Pixel Movement Function (PMF) is a function of N iteration inside each block, this function required a changeable key K calculated in each iteration N for the position of each block. Numerical experiments are performed to demonstrate that the proposed method can improve watermarking quality in terms of imperceptibility of watermark, capacity of insertion and robustness against different attacks such as Joint Photographic Experts Group (JPEG) compression, noise addition and geometrical attacks.

<span>Digital watermarking is the process of embedding particular information into other signal data in such a way that the quality of the original data is maintained and secured. Watermarking can be performed on images, videos, texts, or audio to protect them from copyright violation. Among all of these types of watermarking, audio watermarking techniques are gaining more interest and becoming more challenging because the quality of such signals is highly affected by the watermarked code. This paper introduces some efficient approaches that have capability to maintain the signals’ quality and preserves the important features of the audio signals. Moreover, the proposed digital audio watermarking approaches are performed in the transform domain. These approaches are gaining more attention due to their robustness or resistance to the attackers. These transform domains include discrete cosine transform (DCT), short-term Fourier transform (STFT), and digital wavelet transform (DWT). Furthermore, the most digital wavelet transforms were found to be applicable for speech watermarking are the Haar and the Daubechies-4. </span>

Gaussian noise is an important problem in computer vision. The novel methods that become popular in recent years for Gaussian noise reduction are Bayesian techniques in wavelet domain. In wavelet domain, the Bayesian techniques require a prior distribution of wavelet coefficients. In general case, the wavelet coefficients might be better modeled by non-Gaussian density such as Laplacian, two-sided gamma, and Pearson type VII densities. However, statistical analysis of textural image is Gaussian model. So, we require flexible model between non-Gaussian and Gaussian models. Indeed, Gumbel density is a suitable model. So, we present new Bayesian estimator for Gumbel random vectors in AWGN (additive white Gaussian noise). The proposed method is applied to dual-tree complex wavelet transform (DT-CWT) as well as orthogonal discrete wavelet transform (DWT). The simulation results show that our proposed methods outperform the state-of-the-art methods qualitatively and quantitatively.