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This book introduces audio watermarking methods for copyright protection, which has drawn extensive attention for securing digital data from unauthorized copying. The book is divided into two parts. First, an audio watermarking method in discrete wavelet transform (DWT) and discrete cosine transform (DCT) domains using singular value decomposition (SVD) and quantization is introduced. This method is robust against various attacks and provides good imperceptible watermarked sounds. Then, an audio watermarking method in fast Fourier transform (FFT) domain using SVD and Cartesian-polar transformation (CPT) is presented. This method has high imperceptibility and high data payload and it provides good robustness against various attacks. These techniques allow media owners to protect copyright and to show authenticity and ownership of their material in a variety of applications. · Features new methods of audio watermarking for copyright protection and ownership protection · Outlines techniques that provide superior performance in terms of imperceptibility, robustness, and data payload · Includes applications such as data authentication, data indexing, broadcast monitoring, fingerprinting, etc.
This book introduces audio watermarking methods in transform domain based on matrix decomposition for copyright protection. Chapter 1 discusses the application and properties of digital watermarking. Chapter 2 proposes a blind lifting wavelet transform (LWT) based watermarking method using fast Walsh Hadamard transform (FWHT) and singular value decomposition (SVD) for audio copyright protection. Chapter 3 presents a blind audio watermarking method based on LWT and QR decomposition (QRD) for audio copyright protection. Chapter 4 introduces an audio watermarking algorithm based on FWHT and LU decomposition (LUD). Chapter 5 proposes an audio watermarking method based on LWT and Schur decomposition (SD). Chapter 6 explains in details on the challenges and future trends of audio watermarking in various application areas. Introduces audio watermarking methods for copyright protection and ownership protection; Describes watermarking methods with encryption and decryption that provide excellent performance in terms of imperceptibility, robustness, and data payload; Discusses in details on the challenges and future research direction of audio watermarking in various application areas.
This book provides information on digital audio watermarking, its applications, and its evaluation for copyright protection of audio signals – both basic and advanced. The author covers various advanced digital audio watermarking algorithms that can be used for copyright protection of audio signals. These algorithms are implemented using hybridization of advanced signal processing transforms such as fast discrete curvelet transform (FDCuT), redundant discrete wavelet transform (RDWT), and another signal processing transform such as discrete cosine transform (DCT). In these algorithms, Arnold scrambling is used to enhance the security of the watermark logo. This book is divided in to three portions: basic audio watermarking and its classification, audio watermarking algorithms, and audio watermarking algorithms using advance signal transforms. The book also covers optimization based audio watermarking. Describes basic of digital audio watermarking and its applications, including evaluation parameters for digital audio watermarking algorithms; Provides audio watermarking algorithms using advanced signal transformations; Provides optimization based audio watermarking algorithms.
This book introduces methods for copyright protection and compression for speech signals. The first method introduces copyright protection of speech signal using watermarking; the second introduces compression of the speech signal using Compressive Sensing (CS). Both methods are tested and analyzed. The speech watermarking method uses technology such as Finite Ridgelet Transform (FRT), Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). The performance of the method is evaluated and compared with existing watermarking methods. In the speech compression method, the standard Compressive Sensing (CS) process is used for compression of the speech signal. The performance of the proposed method is evaluated using various transform bases like Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Singular Value Decomposition (SVD), and Fast Discrete Curvelet Transform (FDCuT).
The book includes the insights that reflect ‘Advances in Computer and Computational Sciences’ from upcoming researchers and leading academicians across the globe. It contains the high-quality peer-reviewed papers of ‘International Conference on Computer, Communication and Computational Sciences (IC4S 2017), held during 11–12 October, 2017 in Thailand. These papers are arranged in the form of chapters. The content of this book is divided into two volumes that cover variety of topics such as intelligent hardware and software design, advanced communications, intelligent computing techniques, intelligent image processing, and web and informatics. This book helps the perspective readers’ from computer industry and academia to derive the advances of next generation computer and communication technology and shape them into real life applications.
"This book introduces readers to state-of-art research in multimedia watermarking in the different disciplines of watermarking, addressing the different aspects of advanced watermarking research; modeling and theoretical analysis, advanced embedding and extraction techniques, software and hardware implementations, and performance evaluations of watermarking systems"--Provided by publisher.
Exchange of information and innovative ideas are necessary to accelerate the development of technology. With advent of technology, intelligent and soft computing techniques came into existence with a wide scope of implementation in engineering sciences. Keeping this ideology in preference, this book includes the insights that reflect the ‘Advances in Computer and Computational Sciences’ from upcoming researchers and leading academicians across the globe. It contains high-quality peer-reviewed papers of ‘International Conference on Computer, Communication and Computational Sciences (ICCCCS 2016), held during 12-13 August, 2016 in Ajmer, India'. These papers are arranged in the form of chapters. The content of the book is divided into two volumes that cover variety of topics such as intelligent hardware and software design, advanced communications, power and energy optimization, intelligent techniques used in internet of things, intelligent image processing, advanced software engineering, evolutionary and soft computing, security and many more. This book helps the perspective readers’ from computer industry and academia to derive the advances of next generation computer and communication technology and shape them into real life applications.
This book features papers presented at IIH-MSP 2018, the 14th International Conference on Intelligent Information Hiding and Multimedia Signal Processing. The scope of IIH-MSP included information hiding and security, multimedia signal processing and networking, and bio-inspired multimedia technologies and systems. The book discusses subjects related to massive image/video compression and transmission for emerging networks, advances in speech and language processing, recent advances in information hiding and signal processing for audio and speech signals, intelligent distribution systems and applications, recent advances in security and privacy for multimodal network environments, multimedia signal processing, and machine learning. Presenting the latest research outcomes and findings, it is suitable for researchers and students who are interested in the corresponding fields. IIH-MSP 2018 was held in Sendai, Japan on 26–28 November 2018. It was hosted by Tohoku University and was co‐sponsored by the Fujian University of Technology in China, the Taiwan Association for Web Intelligence Consortium in Taiwan, and the Swinburne University of Technology in Australia, as well as the Fujian Provincial Key Laboratory of Big Data Mining and Applications (Fujian University of Technology) and the Harbin Institute of Technology Shenzhen Graduate School in China.
​This book provides various speech enhancement algorithms for digital hearing aids. It covers information on noise signals extracted from silences of speech signal. The description of the algorithm used for this purpose is also provided. Different types of adaptive filters such as Least Mean Squares (LMS), Normalized LMS (NLMS) and Recursive Lease Squares (RLS) are described for noise reduction in the speech signals. Different types of noises are taken to generate noisy speech signals, and therefore information on various noises signals is provided. The comparative performance of various adaptive filters for noise reduction in speech signals is also described. In addition, the book provides a speech enhancement technique using adaptive filtering and necessary frequency strength enhancement using wavelet transform as per the requirement of audiogram for digital hearing aids. Presents speech enhancement techniques for improving performance of digital hearing aids; Covers various types of adaptive filters and their advantages and limitations; Provides a hybrid speech enhancement technique using wavelet transform and adaptive filters.
This book constitutes the thoroughly refereed proceedings of the Eleventh International Symposium on Natural Language Processing (SNLP-2016), held in Phranakhon Si Ayutthaya, Thailand on February 10–12, 2016. The SNLP promotes research in natural language processing and related fields, and provides a unique opportunity for researchers, professionals and practitioners to discuss various current and advanced issues of interest in NLP. The 2016 symposium was expanded to include the First Workshop in Intelligent Informatics and Smart Technology. Of the 66 high-quality papers accepted, this book presents twelve from the Symposium on Natural Language Processing track and ten from the Workshop in Intelligent Informatics and Smart Technology track (SSAI: Special Session on Artificial Intelligence).