Digital Watermarking Techniques in Curvelet and Ridgelet Domain
Digital Watermarking Techniques in Curvelet and Ridgelet Domain

Author: Channapragada Rama Seshagiri Rao

Publisher: Springer

Published: 2016-05-20

Total Pages: 108

ISBN-13: 3319329510

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This book describes the design, development, and testing of a novel digital watermarking technique for color images using Magic Square and Ridgelet transforms. The novel feature of the method is that it generates and uses multiple copies of the digital watermark. The book describes how the method was tested for embedding digital watermarks into color cover images, resulting in very high PSNR value and yielding comparable results with existing watermarking techniques.To reach this new method, eight different techniques are designed, developed and tested. First, the authors test two digital watermarking techniques based on encryption: Image Watermark Using Complete Complementary Code Technique (CCCT) and Image Watermarking Using CCC-Fast Walsh Hadamard Transform Technique (CCC-FWHTT). Next, four digital watermarking techniques based on curvelet transforms are discussed: Image Watermarking Using Curvelet Transform (WCT), Watermark Wavelets in Curvelets of Cover Image (WWCT), Resized Watermark into Curvelets of Cover Image (RWCT), and Resized Watermark Wavelets into Curvelets of Cover Image (RWWCT). Then, two final techniques are presented: Image Watermarking Based on Magic Square (MST) and Image watermarking based on Magic Square and Ridgelet Transform (MSRTT). Future research directions are explored in the final chapter.Designed for professionals and researchers in computer graphics and imaging, Digital Watermarking Techniques in Curvelet and Ridgelet Domain is also a useful tool for advanced-level students.

A Wavelet Tour of Signal Processing
A Wavelet Tour of Signal Processing

Author: Stephane Mallat

Publisher: Academic Press

Published: 2008-12-18

Total Pages: 829

ISBN-13: 0080922023

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Mallat's book is the undisputed reference in this field - it is the only one that covers the essential material in such breadth and depth. - Laurent Demanet, Stanford UniversityThe new edition of this classic book gives all the major concepts, techniques and applications of sparse representation, reflecting the key role the subject plays in today's signal processing. The book clearly presents the standard representations with Fourier, wavelet and time-frequency transforms, and the construction of orthogonal bases with fast algorithms. The central concept of sparsity is explained and applied to signal compression, noise reduction, and inverse problems, while coverage is given to sparse representations in redundant dictionaries, super-resolution and compressive sensing applications.Features:* Balances presentation of the mathematics with applications to signal processing* Algorithms and numerical examples are implemented in WaveLab, a MATLAB toolboxNew in this edition* Sparse signal representations in dictionaries* Compressive sensing, super-resolution and source separation* Geometric image processing with curvelets and bandlets* Wavelets for computer graphics with lifting on surfaces* Time-frequency audio processing and denoising* Image compression with JPEG-2000* New and updated exercisesA Wavelet Tour of Signal Processing: The Sparse Way, Third Edition, is an invaluable resource for researchers and R&D engineers wishing to apply the theory in fields such as image processing, video processing and compression, bio-sensing, medical imaging, machine vision and communications engineering.Stephane Mallat is Professor in Applied Mathematics at École Polytechnique, Paris, France. From 1986 to 1996 he was a Professor at the Courant Institute of Mathematical Sciences at New York University, and between 2001 and 2007, he co-founded and became CEO of an image processing semiconductor company. - Includes all the latest developments since the book was published in 1999, including its application to JPEG 2000 and MPEG-4 - Algorithms and numerical examples are implemented in Wavelab, a MATLAB toolbox - Balances presentation of the mathematics with applications to signal processing

Biometrics: Concepts, Methodologies, Tools, and Applications
Biometrics: Concepts, Methodologies, Tools, and Applications

Author: Management Association, Information Resources

Publisher: IGI Global

Published: 2016-08-30

Total Pages: 1887

ISBN-13: 1522509844

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Security and authentication issues are surging to the forefront of the research realm in global society. As technology continues to evolve, individuals are finding it easier to infiltrate various forums and facilities where they can illegally obtain information and access. By implementing biometric authentications to these forums, users are able to prevent attacks on their privacy and security. Biometrics: Concepts, Methodologies, Tools, and Applications is a multi-volume publication highlighting critical topics related to access control, user identification, and surveillance technologies. Featuring emergent research on the issues and challenges in security and privacy, various forms of user authentication, biometric applications to image processing and computer vision, and security applications within the field, this publication is an ideal reference source for researchers, engineers, technology developers, students, and security specialists.

Bayesian Astrophysics
Bayesian Astrophysics

Author: Andrés Asensio Ramos

Publisher: Cambridge University Press

Published: 2018-04-26

Total Pages: 209

ISBN-13: 1107102138

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Provides an overview of the fundamentals of Bayesian inference and its applications within astrophysics, for graduate students and researchers.

Academic Press Library in Signal Processing
Academic Press Library in Signal Processing

Author: Paulo S.R. Diniz

Publisher: Academic Press

Published: 2013-09-21

Total Pages: 1559

ISBN-13: 0123972264

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This first volume, edited and authored by world leading experts, gives a review of the principles, methods and techniques of important and emerging research topics and technologies in machine learning and advanced signal processing theory. With this reference source you will: - Quickly grasp a new area of research - Understand the underlying principles of a topic and its application - Ascertain how a topic relates to other areas and learn of the research issues yet to be resolved - Quick tutorial reviews of important and emerging topics of research in machine learning - Presents core principles in signal processing theory and shows their applications - Reference content on core principles, technologies, algorithms and applications - Comprehensive references to journal articles and other literature on which to build further, more specific and detailed knowledge - Edited by leading people in the field who, through their reputation, have been able to commission experts to write on a particular topic

Texture Feature Extraction Techniques for Image Recognition
Texture Feature Extraction Techniques for Image Recognition

Author: Jyotismita Chaki

Publisher: Springer Nature

Published: 2019-10-24

Total Pages: 109

ISBN-13: 9811508534

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The book describes various texture feature extraction approaches and texture analysis applications. It introduces and discusses the importance of texture features, and describes various types of texture features like statistical, structural, signal-processed and model-based. It also covers applications related to texture features, such as facial imaging. It is a valuable resource for machine vision researchers and practitioners in different application areas.

Fundamentals of Image Data Mining
Fundamentals of Image Data Mining

Author: Dengsheng Zhang

Publisher: Springer Nature

Published: 2021-06-25

Total Pages: 383

ISBN-13: 3030692515

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This unique and useful textbook presents a comprehensive review of the essentials of image data mining, and the latest cutting-edge techniques used in the field. The coverage spans all aspects of image analysis and understanding, offering deep insights into areas of feature extraction, machine learning, and image retrieval. The theoretical coverage is supported by practical mathematical models and algorithms, utilizing data from real-world examples and experiments. Topics and features: Describes essential tools for image mining, covering Fourier transforms, Gabor filters, and contemporary wavelet transforms Develops many new exercises (most with MATLAB code and instructions) Includes review summaries at the end of each chapter Analyses state-of-the-art models, algorithms, and procedures for image mining Integrates new sections on pre-processing, discrete cosine transform, and statistical inference and testing Demonstrates how features like color, texture, and shape can be mined or extracted for image representation Applies powerful classification approaches: Bayesian classification, support vector machines, neural networks, and decision trees Implements imaging techniques for indexing, ranking, and presentation, as well as database visualization This easy-to-follow, award-winning book illuminates how concepts from fundamental and advanced mathematics can be applied to solve a broad range of image data mining problems encountered by students and researchers of computer science. Students of mathematics and other scientific disciplines will also benefit from the applications and solutions described in the text, together with the hands-on exercises that enable the reader to gain first-hand experience of computing.

Machine Learning and IoT for Intelligent Systems and Smart Applications
Machine Learning and IoT for Intelligent Systems and Smart Applications

Author: Madhumathy P

Publisher: CRC Press

Published: 2021-11-17

Total Pages: 243

ISBN-13: 1000484963

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The fusion of AI and IoT enables the systems to be predictive, prescriptive, and autonomous, and this convergence has evolved the nature of emerging applications from being assisted to augmented, and ultimately to autonomous intelligence. This book discusses algorithmic applications in the field of machine learning and IoT with pertinent applications. It further discusses challenges and future directions in the machine learning area and develops understanding of its role in technology, in terms of IoT security issues. Pertinent applications described include speech recognition, medical diagnosis, optimizations, predictions, and security aspects. Features: Focuses on algorithmic and practical parts of the artificial intelligence approaches in IoT applications. Discusses supervised and unsupervised machine learning for IoT data and devices. Presents an overview of the different algorithms related to Machine learning and IoT. Covers practical case studies on industrial and smart home automation. Includes implementation of AI from case studies in personal and industrial IoT. This book aims at Researchers and Graduate students in Computer Engineering, Networking Communications, Information Science Engineering, and Electrical Engineering.

Acta Numerica 2006: Volume 15
Acta Numerica 2006: Volume 15

Author: Arieh Iserles

Publisher: Cambridge University Press

Published: 2006-08-03

Total Pages: 658

ISBN-13: 9780521868150

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A high-impact factor, prestigious annual publication containing invited surveys by subject leaders: essential reading for all practitioners and researchers.