Lifting dual tree complex wavelets transform

We describe the lifting dual tree complex wavelet transform (LDTCWT), a type of lifting wavelets remodeling that produce complex coefficients by employing a dual tree of lifting wavelets filters to get its real part and imaginary part. Permits the remodel to produce approximate shift invariance, directionally selective filters and reduces the computation time (properties lacking within the classical wavelets transform). We describe a way to estimate the accuracy of this approximation and style appropriate filters to attain this. These benefits are often exploited among applications like denoising, segmentation, image fusion and compression. The results of applications shrinkage denoising demonstrate objective and subjective enhancements over the dual tree complex wavelet transform (DTCWT). The results of the shrinkage denoising example application indicate empirical and subjective enhancements over the DTCWT. The new transform with the DTCWT provide a trade-off between denoising computational competence of performance, and memory necessities. We tend to use the PSNR (peak signal to noise ratio) alongside the structural similarity index measure (SSIM) and the SSIM map to estimate denoised image quality

Comparative Analysis of Techniques Used to Detect Copy-Move Tampering for Real-World Electronic Images

Evolution of high computational powerful computers, easy availability of several innovative editing software package and high-definition quality-based image capturing tools follows to effortless result in producing image forgery. Though, threats for security and misinterpretation of digital images and scenes have been observed to be happened since a long period and also a lot of research has been established in developing diverse techniques to authenticate the digital images. On the contrary, the research in this region is not limited to checking the validity of digital photos but also to exploring the specific signs of distortion or forgery. This analysis would not require additional prior information of intrinsic content of corresponding digital image or prior embedding of watermarks. In this paper, recent growth in the area of digital image tampering identification have been discussed along with benchmarking study has been shown with qualitative and quantitative results. With variety of methodologies and concepts, different applications of forgery detection have been discussed with corresponding outcomes especially using machine and deep learning methods in order to develop efficient automated forgery detection system. The future applications and development of advanced soft-computing based techniques in digital image forgery tampering has been discussed

Discrete Wavelet Transforms

The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications

Comparative Analysis of Techniques Used to Detect Copy-Move Tampering for Real-World Electronic Images

Evolution of high computational powerful computers, easy availability of several innovative editing software package and high-definition quality-based image capturing tools follows to effortless result in producing image forgery. Though, threats for security and misinterpretation of digital images and scenes have been observed to be happened since a long period and also a lot of research has been established in developing diverse techniques to authenticate the digital images. On the contrary, the research in this region is not limited to checking the validity of digital photos but also to exploring the specific signs of distortion or forgery. This analysis would not require additional prior information of intrinsic content of corresponding digital image or prior embedding of watermarks. In this paper, recent growth in the area of digital image tampering identification have been discussed along with benchmarking study has been shown with qualitative and quantitative results. With variety of methodologies and concepts, different applications of forgery detection have been discussed with corresponding outcomes especially using machine and deep learning methods in order to develop efficient automated forgery detection system. The future applications and development of advanced soft-computing based techniques in digital image forgery tampering has been discussed

A Review of Audio Features and Statistical Models Exploited for Voice Pattern Design

Audio fingerprinting, also named as audio hashing, has been well-known as a powerful technique to perform audio identification and synchronization. It basically involves two major steps: fingerprint (voice pattern) design and matching search. While the first step concerns the derivation of a robust and compact audio signature, the second step usually requires knowledge about database and quick-search algorithms. Though this technique offers a wide range of real-world applications, to the best of the authors' knowledge, a comprehensive survey of existing algorithms appeared more than eight years ago. Thus, in this paper, we present a more up-to-date review and, for emphasizing on the audio signal processing aspect, we focus our state-of-the-art survey on the fingerprint design step for which various audio features and their tractable statistical models are discussed.Comment: http://www.iaria.org/conferences2015/PATTERNS15.html ; Seventh International Conferences on Pervasive Patterns and Applications (PATTERNS 2015), Mar 2015, Nice, Franc

Robust digital watermarking techniques for multimedia protection

The growing problem of the unauthorized reproduction of digital multimedia data such as movies, television broadcasts, and similar digital products has triggered worldwide efforts to identify and protect multimedia contents. Digital watermarking technology provides law enforcement officials with a forensic tool for tracing and catching pirates. Watermarking refers to the process of adding a structure called a watermark to an original data object, which includes digital images, video, audio, maps, text messages, and 3D graphics. Such a watermark can be used for several purposes including copyright protection, fingerprinting, copy protection, broadcast monitoring, data authentication, indexing, and medical safety. The proposed thesis addresses the problem of multimedia protection and consists of three parts. In the first part, we propose new image watermarking algorithms that are robust against a wide range of intentional and geometric attacks, flexible in data embedding, and computationally fast. The core idea behind our proposed watermarking schemes is to use transforms that have different properties which can effectively match various aspects of the signal's frequencies. We embed the watermark many times in all the frequencies to provide better robustness against attacks and increase the difficulty of destroying the watermark. The second part of the thesis is devoted to a joint exploitation of the geometry and topology of 3D objects and its subsequent application to 3D watermarking. The key idea consists of capturing the geometric structure of a 3D mesh in the spectral domain by computing the eigen-decomposition of the mesh Laplacian matrix. We also use the fact that the global shape features of a 3D model may be reconstructed using small low-frequency spectral coefficients. The eigen-analysis of the mesh Laplacian matrix is, however, prohibitively expensive. To lift this limitation, we first partition the 3D mesh into smaller 3D sub-meshes, and then we repeat the watermark embedding process as much as possible in the spectral coefficients of the compressed 3D sub-meshes. The visual error of the watermarked 3D model is evaluated by computing a nonlinear visual error metric between the original 3D model and the watermarked model obtained by our proposed algorithm. The third part of the thesis is devoted to video watermarking. We propose robust, hybrid scene-based MPEG video watermarking techniques based on a high-order tensor singular value decomposition of the video image sequences. The key idea behind our approaches is to use the scene change analysis to embed the watermark repeatedly in a fixed number of the intra-frames. These intra-frames are represented as 3D tensors with two dimensions in space and one dimension in time. We embed the watermark information in the singular values of these high-order tensors, which have good stability and represent the video properties. Illustration of numerical experiments with synthetic and real data are provided to demonstrate the potential and the much improved performance of the proposed algorithms in multimedia watermarking

AUDIO WATERMARKING WITH ANGLE QUANTIZATION BASED ON DISCRETE WAVELET TRANSFORM AND SINGULAR VALUE DECOMPOSITION

An audio watermark is a unique electronic identifier embedded in an audio signal, typically used to identify ownership of copyright. Proposed work is a new method of audio watermark hiding inside another bigger cover standard audio cover. The method includes ‘harr’ wavelet based Discrete Wavelet Transform decomposition of frequencies hence the audio samples of watermark gets hidden only those parts of cover audio where human ears are less sensible according to Human Auditory System. Proposed method also includes the Singular Value Decomposition, which is required for making our method robust against the various communication of processing attacks like compression, filtering, fading or noise addition. Proposed work is also using the concept of angular modulation which initially modifies the audio watermark in to provide extra security and also extra robustness in communication. The design is been develop on MATLAB 2013b version and verification of design o the same.&nbsp

A Framework for Multimedia Data Hiding (Security)

With the proliferation of multimedia data such as images, audio, and video, robust digital watermarking and data hiding techniques are needed for copyright protection, copy control, annotation, and authentication. While many techniques have been proposed for digital color and grayscale images, not all of them can be directly applied to binary document images. The difficulty lies in the fact that changing pixel values in a binary document could introduce Irregularities that is very visually noticeable. We have seen but limited number of papers proposing new techniques and ideas for document image watermarking and data hiding. In this paper, we present an overview and summary of recent developments on this important topic, and discuss important issues such as robustness and data hiding capacity of the different techniques