Thisbookpresentsmaterialwhichismorealgorithmicallyorientedthanmost alternatives.Italsodealswithtopicsthatareatorbeyondthestateoftheart. Examples include practical and applicable wavelet and other multiresolution transform analysis. New areas are broached like the ridgelet and curvelet transforms. The reader will ?nd in this book an engineering approach to the interpretation of scienti?c data. Compared to the 1st Edition, various additions have been made throu- out, and the topics covered have been updated. The background or en- ronment of this book's topics include continuing interest in e-science and the virtual observatory, which are based on web based and increasingly web service based science and engineering. Additional colleagues whom we would like to acknowledge in this 2nd edition include: Bedros Afeyan, Nabila Aghanim, Emmanuel Cand' es, David Donoho, Jalal Fadili, and Sandrine Pires, We would like to particularly - knowledge Olivier Forni who contributed to the discussion on compression of hyperspectral data, Yassir Moudden on multiwavelength data analysis and Vicent Mart' ?nez on the genus function. The cover image to this 2nd edition is from the Deep Impact project. It was taken approximately 8 minutes after impact on 4 July 2005 with the CLEAR6 ?lter and deconvolved using the Richardson-Lucy method. We thank Don Lindler, Ivo Busko, Mike A'Hearn and the Deep Impact team for the processing of this image and for providing it to us.

This book presents important research findings and recent innovations in the field of machine learning and signal processing. A wide range of topics relating to machine learning and signal processing techniques and their applications are addressed in order to provide both researchers and practitioners with a valuable resource documenting the latest advances and trends. The book comprises a careful selection of the papers submitted to the 2015 International Conference on Machine Learning and Signal Processing (MALSIP 2015), which was held on 15-17 December 2015 in Ho Chi Minh City, Vietnam with the aim of offering researchers, academicians, and practitioners an ideal opportunity to disseminate their findings and achievements. All of the included contributions were chosen by expert peer reviewers from across the world on the basis of their interest to the community. In addition to presenting the latest in design, development, and research, the book provides access to numerous new algorithms for machine learning and signal processing for engineering problems.

This book presents 13 peer-reviewed papers as written results from the 2005 workshop "Topology-Based Methods in Visualization" that was initiated to enable additional stimulation in this field. It contains a survey of the state-of-the-art, as well original work by leading experts that has not been published before, spanning both theory and applications. It captures key concepts and novel ideas and serves as an overview of current trends in its subject.

This book offers readers fresh insights on applying Extended Reality to Digital Anatomy, a novel emerging discipline. Indeed, the way professors teach anatomy in classrooms is changing rapidly as novel technology-based approaches become ever more accessible. Recent studies show that Virtual (VR), Augmented (AR), and Mixed-Reality (MR) can improve both retention and learning outcomes. Readers will find relevant tutorials about three-dimensional reconstruction techniques to perform virtual dissections. Several chapters serve as practical manuals for students and trainers in anatomy to refresh or develop their Digital Anatomy skills. We developed this book as a support tool for collaborative efforts around Digital Anatomy, especially in distance learning, international and interdisciplinary contexts. We aim to leverage source material in this book to support new Digital Anatomy courses and syllabi in interdepartmental, interdisciplinary collaborations. Digital Anatomy - Applications of Virtual, Mixed and Augmented Reality provides a valuable tool to foster cross-disciplinary dialogues between anatomists, surgeons, radiologists, clinicians, computer scientists, course designers, and industry practitioners. It is the result of a multidisciplinary exercise and will undoubtedly catalyze new specialties and collaborative Master and Doctoral level courses world-wide. In this perspective, the UNESCO Chair in digital anatomy was created at the Paris Descartes University in 2015 (www.anatomieunesco.org). It aims to federate the education of anatomy around university partners from all over the world, wishing to use these new 3D modeling techniques of the human body.

The contributions for this book have been gathered over several years from conferences held in the series of Mechatronics and Machine Vision in Practice, the latest of which was held in Ankara, Turkey. The essential aspect is that they concern practical applications rather than the derivation of mere theory, though simulations and visualization are important components. The topics range from mining, with its heavy engineering, to the delicate machining of holes in the human skull or robots for surgery on human flesh. Mobile robots continue to be a hot topic, both from the need for navigation and for the task of stabilization of unmanned aerial vehicles. The swinging of a spray rig is damped, while machine vision is used for the control of heating in an asphalt-laying machine. Manipulators are featured, both for general tasks and in the form of grasping fingers. A robot arm is proposed for adding to the mobility scooter of the elderly. Can EEG signals be a means to control a robot? Can face recognition be achieved in varying illumination?"

Video text detection provides an efficient approach to the indexing, classification, retrieval and understanding of visual content.

This unique text/reference presents a systematic introduction to the latest developments in video text detection. Opening with a discussion of the underlying theory and a brief history of video text detection, the text proceeds to cover pre-processing and post-processing techniques, character segmentation and recognition, identification of non-English scripts, techniques for multi-modal analysis, and performance evaluation. The detection of text from both natural video scenes and artificially inserted captions is examined. Various applications of the technology are also reviewed, from license plate recognition and road navigation assistance, to sports analysis and video advertising systems.

Topics and features: explains the fundamental theory in a succinct manner, supplemented with thorough, up-to-date references for further reading; highlights practical techniques to help the reader understand and develop their own detection systems and video text-based applications; discusses the state of the field from historical progress to the latest cutting-edge developments; serves as an easy-to-navigate reference, presenting the material in self-contained chapters; reviews the entire process from pre-processing to post-processing, including non-English script detection and advanced multi-modal techniques.

This accessible yet comprehensive overview of video text detection is essential reading for advanced students and researchers in pattern recognition, document analysis, image processing, video retrieval and related fields.

Multimedia surveillance systems is an emerging field that includes signal and image processing, communications, and computer vision. Multimedia Video-Based Surveillance Systems: Requirements, Issues and Solutions, combines the most recent research results from these areas for use by engineers and end-users involved in the design of surveillance systems in the fields of transportation and services. The book covers emerging surveillance requirements, including new digital sensors for real-time acquisition of surveillance data, low-level image processing algorithms, and event detection methods. It also discusses problems related to knowledge representation in surveillance systems, wireless and wired multimedia networks, and a new generation of surveillance communication tools. Timely information is presented on digital watermarking, broadband multimedia transmission, legal use of surveillance systems, performance evaluation criteria, and other new and emerging topics, along with applications for transports and pedestrian monitoring. The information contained in Multimedia Video-Based Surveillance Systems: Requirements, Issues and Solutions, bridges the distance between present practice and research findings, and the book is an indispensable reference tool for professional engineers.

The advent of X-ray Computed Tomography (CT) as a tool for the soil sciences almost 40 years ago has revolutionised the field. Soil is the fragile, thin layer of material that exists above earth's geological substrates upon which so much of life on earth depends. However a major limitation to our understanding of how soils behave and function is due to its complex, opaque structure that hinders our ability to assess its porous architecture without disturbance. X-ray imagery has facilitated the ability to truly observe soil as it exists in three dimensions and across contrasting spatial and temporal scales in the field in an undisturbed fashion. This book gives a comprehensive overview of the "state of the art" in a variety of application areas where this type of imaging is used, including soil water physics and hydrology, agronomic management of soils, and soil-plant-microbe interactions. It provides the necessary details for entry level readers in the crucial areas of sample preparation, scanner optimisation and image processing and analysis. Drawing on experts across the globe, from both academia and industry, the book covers the necessary "dos and don'ts", but also offers insights into the future of both technology and science. The wider application of the book is provided by dedicated chapters on how the data from such imagery can be incorporated into models and how the technology can be interfaced with other relevant technical applications. The book ends with a future outlook from the four editors, each of whom has over 20 years of experience in the application of X-ray CT to soil science.

The current popular and scientific interest in virtual environments has provided a new impetus for investigating binaural and spatial hearing. However, the many intriguing phenomena of spatial hearing have long made it an exciting area of scientific inquiry. Psychophysical and physiological investigations of spatial hearing seem to be converging on common explanations of underlying mechanisms. These understandings have in turn been incorporated into sophisticated yet mathematically tractable models of binaural interaction. Thus, binaural and spatial hearing is one of the few areas in which professionals are soon likely to find adequate physiological explanations of complex psychological phenomena that can be reasonably and usefully approximated by mathematical and physical models. This volume grew out of the Conference on Binaural and Spatial Hearing, a four-day event held at Wright-Patterson Air Force Base in response to rapid developments in binaural and spatial hearing research and technology. Meant to be more than just a proceedings, it presents chapters that are longer than typical proceedings papers and contain considerably more review material, including extensive bibliographies in many cases. Arranged into topical sections, the chapters represent major thrusts in the recent literature. The authors of the first chapter in each section have been encouraged to take a broad perspective and review the current state of literature. Subsequent chapters in each section tend to be somewhat more narrowly focused, and often emphasize the authors' own work. Thus, each section provides overview, background, and current research on a particular topic. This book is significant in that it reviews the important work during the past 10 to 15 years, and provides greater breadth and depth than most of the previous works.

This book provides an in-depth overview of artificial intelligence and deep learning approaches with case studies to solve problems associated with biometric security such as authentication, indexing, template protection, spoofing attack detection, ROI detection, gender classification etc. This text highlights a showcase of cutting-edge research on the use of convolution neural networks, autoencoders, recurrent convolutional neural networks in face, hand, iris, gait, fingerprint, vein, and medical biometric traits. It also provides a step-by-step guide to understanding deep learning concepts for biometrics authentication approaches and presents an analysis of biometric images under various environmental conditions. This book is sure to catch the attention of scholars, researchers, practitioners, and technology aspirants who are willing to research in the field of AI and biometric security.

Case-based reasoning in design is becoming an important approach to computer-support for design as well as an important component in understanding the design process. Design has become a major focus for problem solving paradigms due to its complexity and open-ended nature. This book presents a clear description of how case-based reasoning can be applied to design problems, including the representation of design cases, indexing and retrieving design cases, and the range of paradigms for adapting design cases. With a focus on design, this book differs from others that provide a generalist view of case-based reasoning.
This volume provides two important contributions to the area:
* a general description of the issues and alternatives in applying case-based reasoning to design, and
* a description of specific implementations of case-based design.
Through this combination, the reader will learn about both the general issues and the practical problems in supporting design through case-based reasoning. This book was prepared to fill a gap in the literature on the unique problems that design introduces to computational paradigms developed in computer science. It also addresses the needs of computational support for design problem solving from both theoretical and practical perspectives.

This book is concerned with the processing of signals that have been sampled and digitized. The authors present algorithms for the optimization, random simulation, and numerical integration of probability densities for applications of Bayesian inference to signal processing. In particular, methods are developed for the computation of marginal densities and evidence, and are applied to previously intractable problems either involving large numbers of parameters or where the signal model is of a complex form. The emphasis is on the applications of these methods notably to the restoration of digital audio recordings and biomedical data. After a chapter which sets out the main principles of Bayesian inference applied to signal processing, subsequent chapters cover numerical approaches to these techniques, the use of Markov chain Monte Carlo methods, the identification of abrupt changes in data using the Bayesian piecewise linear model, and identifying missing samples in digital audio signals.

Digital Image Processing with C++ presents the theory of digital image processing, and implementations of algorithms using a dedicated library. Processing a digital image means transforming its content (denoising, stylizing, etc.), or extracting information to solve a given problem (object recognition, measurement, motion estimation, etc.). This book presents the mathematical theories underlying digital image processing, as well as their practical implementation through examples of algorithms implemented in the C++ language, using the free and easy-to-use CImg library. Chapters cover in a broad way the field of digital image processing and proposes practical and functional implementations of each method theoretically described. The main topics covered include filtering in spatial and frequency domains, mathematical morphology, feature extraction and applications to segmentation, motion estimation, multispectral image processing and 3D visualization. Students or developers wishing to discover or specialize in this discipline, teachers and researchers wishing to quickly prototype new algorithms, or develop courses, will all find in this book material to discover image processing or deepen their knowledge in this field.

This book is a comprehensive, hands-on guide to the basics of data mining and machine learning with a special emphasis on supervised and unsupervised learning methods. The book lays stress on the new ways of thinking needed to master in machine learning based on the Python, R, and Java programming platforms. This book first provides an understanding of data mining, machine learning and their applications, giving special attention to classification and clustering techniques. The authors offer a discussion on data mining and machine learning techniques with case studies and examples. The book also describes the hands-on coding examples of some well-known supervised and unsupervised learning techniques using three different and popular coding platforms: R, Python, and Java. This book explains some of the most popular classification techniques (K-NN, Naive Bayes, Decision tree, Random forest, Support vector machine etc,) along with the basic description of artificial neural network and deep neural network. The book is useful for professionals, students studying data mining and machine learning, and researchers in supervised and unsupervised learning techniques.

Integrates rational approximation with adaptive filtering, providing viable, numerically reliable procedures for creating adaptive infinite impulse response (IIR) filters. The choice of filter structure to adapt, algorithm design and the approximation properties for each type of algorithm are also addressed. This work recasts the theory of adaptive IIR filters by concentrating on recursive lattice filters, freeing systems from the need for direct-form filters.;A solutions manual is available for instructors only. College or university bookstores may order five or more copies at a special student price which is available upon request.

Bayesian probability theory and maximum entropy methods are at the core of a new view of scientific inference. These new' ideas, along with the revolution in computational methods afforded by modern computers, allow astronomers, electrical engineers, image processors of any type, NMR chemists and physicists, and anyone at all who has to deal with incomplete and noisy data, to take advantage of methods that, in the past, have been applied only in some areas of theoretical physics. This volume records the Proceedings of Eleventh Annual Maximum Entropy' Workshop, held at Seattle University in June, 1991. These workshops have been the focus of a group of researchers from many different fields, and this diversity is evident in this volume. There are tutorial papers, theoretical papers, and applications in a very wide variety of fields. Almost any instance of dealing with incomplete and noisy data can be usefully treated by these methods, and many areas of theoretical research are being enhanced by the thoughtful application of Bayes' theorem. The contributions contained in this volume present a state-of-the-art review that will be influential and useful for many years to come.

This book contains thirteen contributions from invited experts of international recognition addressing important issues in shape analysis in medical image analysis, including techniques for image segmentation, registration, modelling and classification and applications in biology, as well as in cardiac, brain, spine, chest, lung and clinical practice.

This volume treats topics such as for example, anatomic and functional shape representation and matching; shape-based medical image segmentation; shape registration; statistical shape analysis; shape deformation; shape-based abnormity detection; shape tracking and longitudinal shape analysis; machine learning for shape modeling and analysis; shape-based computer-aided-diagnosis; shape-based medical navigation; benchmark and validation of shape representation, analysis and modeling algorithms.

This work will be of interest to researchers, students and manufacturers in the fields of artificial intelligence, bioengineering, biomechanics, computational mechanics, computational vision, computer sciences, human motion, mathematics, medical imaging, medicine, pattern recognition and physics.

This book covers recent advances in image processing and imaging sciences from an optimization viewpoint, especially convex optimization with the goal of designing tractable algorithms. Throughout the handbook, the authors introduce topics on the most key aspects of image acquisition and processing that are based on the formulation and solution of novel optimization problems. The first part includes a review of the mathematical methods and foundations required, and covers topics in image quality optimization and assessment. The second part of the book discusses concepts in image formation and capture from color imaging to radar and multispectral imaging. The third part focuses on sparsity constrained optimization in image processing and vision and includes inverse problems such as image restoration and de-noising, image classification and recognition and learning-based problems pertinent to image understanding. Throughout, convex optimization techniques are shown to be a critically important mathematical tool for imaging science problems and applied extensively. Convex Optimization Methods in Imaging Science is the first book of its kind and will appeal to undergraduate and graduate students, industrial researchers and engineers and those generally interested in computational aspects of modern, real-world imaging and image processing problems.

This volume describes the status of fractal imaging research and looks to future directions. It will be useful to researchers in the areas of fractal image compression, analysis, and synthesis, iterated function systems, and fractals in education. In particular it includes a vision for the future of these areas. It aims to provide an efficient means by which researchers can look back over the last decade at what has been achieved, and look forward towards second-generation fractal imaging. The articles in themselves are not meant to be detailed reviews or expositions, but to serve as signposts to the state of the art in their areas. What is important is what they mention and what tools and ideas are seen now to be relevant to the future. The contributors, a number of whom have been involved since the start, are active in fractal imaging, and provide a well-informed viewpoint on both the status and the future. Most were invited participants at a meeting on Fractals in Multimedia held at the IMA in January 2001. Some goals of the mini-symposium, shared with this volume, were to demonstrate that the fractal viewpoint leads to a broad collection of useful mathematical tools, common themes, new ways of looking at and thinking about existing algorithms and applications in multimedia, and to consider future developments. This book should be useful to commercial and university researchers in the rapidly evolving field of digital imaging, specifically, chief information officers, professors, software engineers, and graduate students in the mathematical sciences. While much of the content is quite technical, it contains pointers to the state-of-the-art and the future in fractal imaging.

Provides a technical introduction to deepfakes, its benefits, and the potential harms Presents practical approaches of creation and detection of deepfakes using Deep Learning (DL) Techniques Draws attention towards various challenging issues and societal impact of deepfakes with their existing solutions Includes research analysis in the domain of DL fakes for assisting the creation and detection of deepfakes applications Discusses future research directions with emergence of deepfakes technology

In this introduction to vision models and their use in image and video processing applications, prominent authors take on an engineering and signal processing approach. It is intended for an engineering audience that wants to use and become familiar with vision models.

Create code art, visualizations, and interactive applications with this powerful yet simple computer language and programming environment Learn how to code 2D and 3D animation, pixel-level imaging, motion effects, and physics simulations Take a creative and fun approach to learning creative computer programming If you're interested in creating cutting-edge code-based art and animations, you've come to the right place! Processing (available at www.processing.org) is a revolutionary open source programming language and environment designed to bridge the gap between programming and art, allowing non-programmers to learn programming fundamentals as easily as possible, and empowering anyone to produce beautiful creations using math patterns. With the software freely available, Processing provides an accessible alternative to using Flash for creative coding and computational artboth on and off the Web. This book is written especially for artists, designers, and other creative professionals and students exploring code art, graphics programming, and computational aesthetics. The book provides a solid and comprehensive foundation in programming, including object-oriented principles, and introduces you to the easy-to-grasp Processing language, so no previous coding experience is necessary. The book then goes through using Processing to code lines, curves, shapes, and motion, continuing to the point where you'll have mastered Processing and can really start to unleash your creativity with realistic physics, interactivity, and 3D! In the final chapter, you'll even learn how to extend your Processing skills by working directly with the powerful Java programming languagethe language Processing itselfis built with. You'll learn: The fundamentals of creative computer programming--from procedural programming, to object-oriented programming, to pure Java programming How to virtually draw, paint, and sculpt using computer code and clearly explained mathematical concepts 2D and 3D programming techniques, motion design, and cool graphics effects How to code your own pixel-level imaging effects, such as image contrast, color saturation, custom gradients and more Advanced animation techniques, including realistic physics and artificial life simulation Summary of Contents PART ONE: THEORY OF PROCESSING AND COMPUTATIONAL ART Chapter 1: Code Art Chapter 2: Creative Coding Chapter 3: Code Grammar 101 Chapter 4: Computer Graphics, the Fun, Easy Way Chapter 5: The Processing Environment PART TWO: PUTTING THEORY INTO PRACTICE Chapter 6: Lines Chapter 7: Curves Chapter 8: Object-Oriented Programming Chapter 9: Shapes Chapter 10: Color and Imaging Chapter 11: Motion Chapter 12: Interactivity Chapter 13: 3D Chapter 14: 3D Rendering in Java Mode PART THREE: REFERENCE Appendix A: Processing Language API Appendix B: Math Reference Appendix C: Integrating Processing within Java

The purpose of this book is to provide a practical introduction to the th- ries, techniques and applications of image fusion. The present work has been designed as a textbook for a one-semester ?nal-year undergraduate, or ?r- year graduate, course in image fusion. It should also be useful to practising engineers who wish to learn the concepts of image fusion and apply them to practical applications. In addition, the book may also be used as a supp- mentary text for a graduate course on topics in advanced image processing. The book complements the author's previous work on multi-sensor data [1] fusion by concentrating exclusively on the theories, techniques and app- cations of image fusion. The book is intended to be self-contained in so far as the subject of image fusion is concerned, although some prior exposure to the ?eld of computer vision and image processing may be helpful to the reader. Apart from two preliminary chapters, the book is divided into three parts.

The realistic generation of virtual doubles of real-world actors has been the focus of computer graphics research for many years. However, some problems still remain unsolved: it is still time-consuming to generate character animations using the traditional skeleton-based pipeline, passive performance capture of human actors wearing arbitrary everyday apparel is still challenging, and until now, there is only a limited amount of techniques for processing and modifying mesh animations, in contrast to the huge amount of skeleton-based techniques. In this thesis, we propose algorithmic solutions to each of these problems. First, two efficient mesh-based alternatives to simplify the overall character animation process are proposed. Although abandoning the concept of a kinematic skeleton, both techniques can be directly integrated in the traditional pipeline, generating animations with realistic body deformations. Thereafter, three passive performance capture methods are presented which employ a deformable model as underlying scene representation. The techniques are able to jointly reconstruct spatio-temporally coherent time-varying geometry, motion, and textural surface appearance of subjects wearing loose and everyday apparel. Moreover, the acquired high-quality reconstructions enable us to render realistic 3D Videos. At the end, two novel algorithms for processing mesh animations are described. The first one enables the fully-automatic conversion of a mesh animation into a skeletonbased animation and the second one automatically converts a mesh animation into an animation collage, a new artistic style for rendering animations. The methods described in the thesis can be regarded as solutions to specific problems or important building blocks for a larger application. As a whole, they form a powerful system to accurately capture, manipulate and realistically render realworld human performances, exceeding the capabilities of many related capture techniques. By this means, we are able to correctly capture the motion, the timevarying details and the texture information of a real human performing, and transform it into a fully-rigged character animation, that can be directly used by an animator, or use it to realistically display the actor from arbitrary viewpoints.