Marking a distinct departure from the perspectives of frame theory and discrete transforms, this book provides a comprehensive mathematical and algorithmic introduction to wavelet theory. As such, it can be used as either a textbook or reference guide. As a textbook for graduate mathematics students and beginning researchers, it offers detailed information on the basic theory of framelets and wavelets, complemented by self-contained elementary proofs, illustrative examples/figures, and supplementary exercises. Further, as an advanced reference guide for experienced researchers and practitioners in mathematics, physics, and engineering, the book addresses in detail a wide range of basic and advanced topics (such as multiwavelets/multiframelets in Sobolev spaces and directional framelets) in wavelet theory, together with systematic mathematical analysis, concrete algorithms, and recent developments in and applications of framelets and wavelets. Lastly, the book can also be used to teach on or study selected special topics in approximation theory, Fourier analysis, applied harmonic analysis, functional analysis, and wavelet-based signal/image processing.

The purpose of this volume is to present current work of the Intelligent Computer Graphics community, a community growing up year after year. This volume is a kind of continuation of the previously published Springer volume "Artificial Int- ligence Techniques for Computer Graphics". Nowadays, intelligent techniques are more and more used in Computer Graphics in order, not only to optimise the pr- essing time, but also to find more accurate solutions for a lot of Computer Gra- ics problems, than with traditional methods. What are intelligent techniques for Computer Graphics? Mainly, they are te- niques based on Artificial Intelligence. So, problem resolution (especially constraint satisfaction) techniques, as well as evolutionary techniques, are used in Declarative scene Modelling; heuristic search techniques, as well as strategy games techniques, are currently used in scene understanding and in virtual world exploration; multi-agent techniques and evolutionary algorithms are used in behavioural animation; and so on. However, even if in most cases the used intelligent techniques are due to Artificial - telligence, sometimes, simple human intelligence can find interesting solutions in cases where traditional Computer Graphics techniques, even combined with Artificial Intelligence ones, cannot propose any satisfactory solution. A good example of such a case is the one of scene understanding, in the case where several parts of the scene are impossible to access.

"Blind Signal Processing: Theory and Practice" not only introduces related fundamental mathematics, but also reflects the numerous advances in the field, such as probability density estimation-based processing algorithms, underdetermined models, complex value methods, uncertainty of order in the separation of convolutive mixtures in frequency domains, and feature extraction using Independent Component Analysis (ICA). At the end of the book, results from a study conducted at Shanghai Jiao Tong University in the areas of speech signal processing, underwater signals, image feature extraction, data compression, and the like are discussed.

This book will be of particular interest to advanced undergraduate students, graduate students, university instructors and research scientists in related disciplines. Xizhi Shi is a Professor at Shanghai Jiao Tong University.

Inspection is crucial to the management of ageing infrastructure. Visual information on structures is regularly collected but very little work exists on its organised and quantitative analysis, even though image processing can significantly enhance these inspection processes and transfer real financial and safety benefits to the managers, owners and users. Additionally, new opportunities exist in the fast evolving sectors of wind and wave energy to add value to image-based inspection techniques. This book is a first for structural engineers and inspectors who wish to harness the full potential of cameras as an inspection tool. It is particularly directed to the inspection of offshore and marine structures and the application of image-based methods in underwater inspections. It outlines a set of best practice guidelines for obtaining imagery, then the fundamentals of image processing are covered along with several image processing techniques which can be used to assess multiple damage forms: crack detection, corrosion detection, and depth analysis of marine growth on offshore structures. The book provides benchmark performance measures for these techniques under various visibility conditions using an image repository which will help inspectors to envisage the effectiveness of the techniques when applied. MATLAB (R) scripts and access to the underwater image repository are included so readers can run these techniques themselves. Practising engineers and managers of infrastructure assets are guided in image processing based inspection. Researchers can use this book as a primer, and it also suits advanced graduate courses in infrastructure management or on applied image processing.

Edited by a renowned international expert in the field, Nuclear Medicine Physics offers an up-to-date, state-of-the-art account of the physics behind the theoretical foundation and applications of nuclear medicine. It covers important physical aspects of the methods and instruments involved in modern nuclear medicine, along with related biological topics. The book first discusses the physics of and machines for producing radioisotopes suitable for use in conventional nuclear medicine and PET. After focusing on positron physics and the applications of positrons in medicine and biology, it describes the use of radiopharmaceuticals in molecular imaging, clinical, and research studies. The text then covers modern radiation detectors and measuring methods, including those used in nuclear imaging, as well as numerous imaging methodologies and models, such as two- and three-dimensional image reconstruction algorithms, data processing sequences, new nuclear oncology techniques, and physiological models of the central nervous system. It also introduces biological systems theory, nuclear medicine methods as systems theory procedures, and aspects of kinetic modeling. The final chapter explores dosimetry and the biological effects of ionizing radiation. With many new developments occurring in nuclear medicine, it is important to understand how advanced approaches are being used in emerging applications. Offering invaluable insight into this growth, Nuclear Medicine Physics provides in-depth descriptions of new radiolabeled biological drugs, new cell labeling techniques, new technical concepts in radiation detection, improvements in instrumentation, and much more.

The compendium presents the latest results of the most prominent competitions held in the field of Document Analysis and Text Recognition. It includes a description of the participating systems and the underlying methods on one hand and the datasets used together with evaluation metrics on the other hand. This volume also demonstrates with examples, how to organize a competition and how to make it successful. It will be an indispensable handbook to the document image analysis community.

High Efficiency Video Coding and Other Emerging Standards provides an overview of high efficiency video coding (HEVC) and all its extensions and profiles. There are nearly 300 projects and problems included, and about 400 references related to HEVC alone. Next generation video coding (NGVC) beyond HEVC is also described. Other video coding standards such as AVS2, DAALA, THOR, VP9 (Google), DIRAC, VC1, and AV1 are addressed, and image coding standards such as JPEG, JPEG-LS, JPEG2000, JPEG XR, JPEG XS, JPEG XT and JPEG-Pleno are also listed. Understanding of these standards and their implementation is facilitated by overview papers, standards documents, reference software, software manuals, test sequences, source codes, tutorials, keynote speakers, panel discussions, reflector and ftp/web sites - all in the public domain. Access to these categories is also provided.

This much-needed text brings the treatment of optical pattern recognition up-to-date in one comprehensive resource. Optical pattern recognition, one of the first implementations of Fourier Optics, is now widely used, and this text provides an accessible introduction for readers who wish to get to grips with how holography is applied in a practical context. A wide range of devices are addressed from a user perspective and are accompanied with detailed tables enabling performance comparison, in addition to chapters exploring computer-generated holograms, optical correlator systems, and pattern matching algorithms. This book will appeal to both lecturers and research scientists in the field of electro-optic devices and systems. Features: Covers a range of new developments, including computer-generated holography and 3D image recognition Accessible without a range of prior knowledge, providing a clear exposition of technically difficult concepts Contains extensive examples throughout to reinforce learning

This book presents the theoretical basis and applications of biomedical signal analysis and processing. Initially, the nature of the most common biomedical signals, such as electroencephalography, electromyography, electrocardiography and others, is described. The theoretical basis of linear signal processing is summarized, with continuous and discrete representation, linear filters and convolutions, Fourier and Wavelets transforms. Machine learning concepts are also presented, from classic methods to deep neural networks. Finally, several applications in neuroscience are presented and discussed, involving diagnosis and therapy, in addition to other applications. Features: Explains signal processing of neuroscience applications using modern data science techniques. Provides comprehensible review on biomedical signals nature and acquisition aspects. Focusses on selected applications of neurosciences, cardiovascular, muscle related biomedical areas. Includes computational intelligence, machine learning and biomedical signal processing and analysis. Reviews theoretical basis of deep learning and state-of-the-art biomedical signal processing and analysis. This book is aimed at researchers, graduate students in biomedical signal processing, signal processing, electrical engineering, neuroscience, and computer science.

Highlights the Emergence of Image Processing in Food and Agriculture In addition to uses specifically related to health and other industries, biological imaging is now being used for a variety of applications in food and agriculture. Bio-Imaging: Principles, Techniques, and Applications fully details and outlines the processes of bio-imaging applicable to food and agriculture, and connects other bio-industries, as well as relevant topics. Due to the noncontact and nondestructive nature of the technology, biological imaging uses unaltered samples, and allows for internal quality evaluation and the detection of defects. Compared to conventional methods, biological imaging produces results that are more consistent and reliable, and can ensure quality monitoring for a variety of practices used in food and agriculture industries as well as many other biological industries. The book highlights every imaging technique available along with their components, image acquisition procedures, advantages, and comparisons to other approaches. Describes essential components of imaging technique in great detail Incorporates case studies in appropriate chapters Contains a wide range of applications from a number of biological fields Bio-Imaging: Principles, Techniques, and Applications focuses on the imaging techniques for biological materials and the application of biological imaging. This technology, which is quickly becoming a standard practice in agriculture and food-related industries, can aid in enhanced process efficiency, quality assurance, and food safety management overall.

This volume offers a valuable starting point for anyone interested in learning computational diffusion MRI and mathematical methods for brain connectivity, while also sharing new perspectives and insights on the latest research challenges for those currently working in the field. Over the last decade, interest in diffusion MRI has virtually exploded. The technique provides unique insights into the microstructure of living tissue and enables in-vivo connectivity mapping of the brain. Computational techniques are key to the continued success and development of diffusion MRI and to its widespread transfer into the clinic, while new processing methods are essential to addressing issues at each stage of the diffusion MRI pipeline: acquisition, reconstruction, modeling and model fitting, image processing, fiber tracking, connectivity mapping, visualization, group studies and inference. These papers from the 2016 MICCAI Workshop "Computational Diffusion MRI" - which was intended to provide a snapshot of the latest developments within the highly active and growing field of diffusion MR - cover a wide range of topics, from fundamental theoretical work on mathematical modeling, to the development and evaluation of robust algorithms and applications in neuroscientific studies and clinical practice. The contributions include rigorous mathematical derivations, a wealth of rich, full-color visualizations, and biologically or clinically relevant results. As such, they will be of interest to researchers and practitioners in the fields of computer science, MR physics, and applied mathematics.

This book presents in a systematic manner the advanced technologies used for various modern robot applications. By bringing fresh ideas, new concepts, novel methods and tools into robot control, robot vision, human robot interaction, teleoperation of robot and multiple robots system, we are to provide a state-of-the-art and comprehensive treatment of the advanced technologies for a wide range of robotic applications. Particularly, we focus on the topics of advanced control and obstacle avoidance techniques for robot to deal with unknown perturbations, of visual servoing techniques which enable robot to autonomously operate in a dynamic environment, and of advanced techniques involved in human robot interaction. The book is primarily intended for researchers and engineers in the robotic and control community. It can also serve as complementary reading for robotics at the both graduate and undergraduate levels.

With the constant increase in applications involving image processing and multimedia procedures digital signal processing (DSP) is important for modern information engineering. One- and Multidimensional Signal Processing provides an introduction to the algorithmic basics of image and TV communication systems as well as for systems in automation and robotic applications using sensor based imaging techniques. This novel combination of both one- and multidimensional signal processing discusses the similarities between the two and aids the understanding of one theory over the other.
* Presents an applications-oriented approach to image processing including TV signal processing and discusses image scanning and the use of DSP procedures or digital filters
* Provides clear and comprehensive coverage of basic concepts such as spatial frequency, spatio-temporal signal processing and the spectral representation of motion and tracking of moving objects
* Features examples of applications including image pick-up and display as well as still image filtering and image sequence interpolation
* Introduces new design strategies for finite-impulse response (FIR) filters for image processing applciations using spatial and frequency design constraints
* Includes an introduction to nonlinear image processing techniques applying edge detection operators, morphological operators and rank order filters
Such a practical book will have wide-ranging appeal as a valuable resource for researchers and developers and as an ideal introductory text for senior undergraduate and postgraduate students.

Focusing on mathematical methods in computer tomography, Image Processing: Tensor Transform and Discrete Tomography with MATLAB (R) introduces novel approaches to help in solving the problem of image reconstruction on the Cartesian lattice. Specifically, it discusses methods of image processing along parallel rays to more quickly and accurately reconstruct images from a finite number of projections, thereby avoiding overradiation of the body during a computed tomography (CT) scan. The book presents several new ideas, concepts, and methods, many of which have not been published elsewhere. New concepts include methods of transferring the geometry of rays from the plane to the Cartesian lattice, the point map of projections, the particle and its field function, and the statistical model of averaging. The authors supply numerous examples, MATLAB (R)-based programs, end-of-chapter problems, and experimental results of implementation. The main approach for image reconstruction proposed by the authors differs from existing methods of back-projection, iterative reconstruction, and Fourier and Radon filtering. In this book, the authors explain how to process each projection by a system of linear equations, or linear convolutions, to calculate the corresponding part of the 2-D tensor or paired transform of the discrete image. They then describe how to calculate the inverse transform to obtain the reconstruction. The proposed models for image reconstruction from projections are simple and result in more accurate reconstructions. Introducing a new theory and methods of image reconstruction, this book provides a solid grounding for those interested in further research and in obtaining new results. It encourages readers to develop effective applications of these methods in CT.

Based on the experiences of the Department of Information Engineering of the University of Pisa and the Radar and Surveillance System (RaSS) national laboratory of the National Interuniversity Consortium of Telecommunication (CNIT), Radar Imaging for Maritime Observation presents the most recent results in radar imaging for maritime observation. The book explores both the areas of sea surface remote sensing and maritime surveillance providing key theoretical concepts of SAR and ISAR imaging and more advanced and ad-hoc techniques for applications in maritime scenarios. The book is organized in two sections. The first section discusses the fundamentals of standard SAR/ISAR processing and novel imaging techniques, such as Bistatic, Passive, and, 3D Interferometric ISAR. The second section focuses on the applications and results obtained by processing real data from maritime observations like SAR image processing for oil spill, detection in SAR images and fractal analysis. Useful to both beginners and experts in maritime observation, this book provides several examples of (mainly space-borne) radar imaging of maritime targets. Nevertheless, the same principles and techniques apply to the case of manned or unmanned carriers and to ground and air moving targets.

1 Introduction.- 2 Continuous-Time Quadratic Guaranteed Cost Filtering.- 3 Discrete-Time Quadratic Guaranteed Cost Filtering.- 4 Continuous-Time Set-Valued State Estimation and Model Validation.- 5 Discrete-Time Set-Valued State Estimation.- 6 Robust State Estimation with Discrete and Continuous Measurements.- 7 Set-Valued State Estimation with Structured Uncertainty.- 8 Robust H? Filtering with Structured Uncertainty.- 9 Robust Fixed Order H? Filtering.- 10 Set-Valued State Estimation for Nonlinear Uncertain Systems.- 11 Robust Filtering Applied to Induction Motor Control.- References.

The analysis of QoE is not an easy task, especially for multimedia services, because all the factors (technical and non-technical) that directly or indirectly influence the user-perceived quality have to be considered. This book describes different methods to investigate users' QoE from the viewpoint of technical and non-technical parameters using multimedia services. It discusses the subjective methods for both controlled and uncontrolled environments. Collected datasets are used to analyze users' profiles, which sheds light on key factors to help network service providers understand end-users' behavior and expectations. Important adaptive video streaming technologies are discussed that run on unmanaged networks to achieve certain QoS features. The authors present a scheduling method to allocate resources to the end-user based on users' QoE and optimizes the power efficiency of users' device for LTE-A. Lastly, two key aspects of 5G networks are presented: QoE using multimedia services (VoIP and video), and power-saving model for mobile device and virtual base station.

This book introduces new techniques for cellular image feature extraction, pattern recognition and classification. The authors use the antinuclear antibodies (ANAs) in patient serum as the subjects and the Indirect Immunofluorescence (IIF) technique as the imaging protocol to illustrate the applications of the described methods. Throughout the book, the authors provide evaluations for the proposed methods on two publicly available human epithelial (HEp-2) cell datasets: ICPR2012 dataset from the ICPR'12 HEp-2 cell classification contest and ICIP2013 training dataset from the ICIP'13 Competition on cells classification by fluorescent image analysis. First, the reading of imaging results is significantly influenced by one's qualification and reading systems, causing high intra- and inter-laboratory variance. The authors present a low-order LP21 fiber mode for optical single cell manipulation and imaging staining patterns of HEp-2 cells. A focused four-lobed mode distribution is stable and effective in optical tweezer applications, including selective cell pick-up, pairing, grouping or separation, as well as rotation of cell dimers and clusters. Both translational dragging force and rotational torque in the experiments are in good accordance with the theoretical model. With a simple all-fiber configuration, and low peak irradiation to targeted cells, instrumentation of this optical chuck technology will provide a powerful tool in the ANA-IIF laboratories. Chapters focus on the optical, mechanical and computing systems for the clinical trials. Computer programs for GUI and control of the optical tweezers are also discussed. to more discriminative local distance vector by searching for local neighbors of the local feature in the class-specific manifolds. Encoding and pooling the local distance vectors leads to salient image representation. Combined with the traditional coding methods, this method achieves higher classification accuracy. Then, a rotation invariant textural feature of Pairwise Local Ternary Patterns with Spatial Rotation Invariant (PLTP-SRI) is examined. It is invariant to image rotations, meanwhile it is robust to noise and weak illumination. By adding spatial pyramid structure, this method captures spatial layout information. While the proposed PLTP-SRI feature extracts local feature, the BoW framework builds a global image representation. It is reasonable to combine them together to achieve impressive classification performance, as the combined feature takes the advantages of the two kinds of features in different aspects. Finally, the authors design a Co-occurrence Differential Texton (CoDT) feature to represent the local image patches of HEp-2 cells. The CoDT feature reduces the information loss by ignoring the quantization while it utilizes the spatial relations among the differential micro-texton feature. Thus it can increase the discriminative power. A generative model adaptively characterizes the CoDT feature space of the training data. Furthermore, exploiting a discriminant representation allows for HEp-2 cell images based on the adaptive partitioned feature space. Therefore, the resulting representation is adapted to the classification task. By cooperating with linear Support Vector Machine (SVM) classifier, this framework can exploit the advantages of both generative and discriminative approaches for cellular image classification. The book is written for those researchers who would like to develop their own programs, and the working MatLab codes are included for all the important algorithms presented. It can also be used as a reference book for graduate students and senior undergraduates in the area of biomedical imaging, image feature extraction, pattern recognition and classification. Academics, researchers, and professional will find this to be an exceptional resource.

Managing and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety of important graph topics such as graph languages, indexing, clustering, data generation, pattern mining, classification, keyword search, pattern matching, and privacy. It also studies a number of domain-specific scenarios such as stream mining, web graphs, social networks, chemical and biological data. The chapters are written by well known researchers in the field, and provide a broad perspective of the area. This is the first comprehensive survey book in the emerging topic of graph data processing.
Managing and Mining Graph Data is designed for a varied audience composed of professors, researchers and practitioners in industry. This volume is also suitable as a reference book for advanced-level database students in computer science and engineering.

Digital fundus images can effectively diagnose glaucoma and diabetes retinopathy, while infrared imaging can show changes in the vascular tissues. Likening the eye to the conventional camera, Image Analysis and Modeling in Ophthalmology explores the application of advanced image processing in ocular imaging. This book considers how images can be used to effectively diagnose ophthalmologic problems. It introduces multi-modality image processing algorithms as a means for analyzing subtle changes in the eye. It details eye imaging, textural imaging, and modeling, and highlights specific imaging and modeling techniques. The book covers the detection of diabetes retinopathy, glaucoma, anterior segment eye abnormalities, instruments on detection of glaucoma, and development of human eye models using computational fluid dynamics and heat transfer principles to predict inner temperatures of the eye from its surface temperature. It presents an ultrasound biomicroscopy (UBM) system for anterior chamber angle imaging and proposes an automated anterior segment eye disease classification system that can be used for early disease diagnosis and treatment management. It focuses on the segmentation of the blood vessels in high-resolution retinal images and describes the integration of the image processing methodologies in a web-based framework aimed at retinal analysis. The authors introduce the A-Levelset algorithm, explore the ARGALI system to calculate the cup-to-disc ratio (CDR), and describe the Singapore Eye Vessel Assessment (SIVA) system, a holistic tool which brings together various technologies from image processing and artificial intelligence to construct vascular models from retinal images. The text furnishes the working principles of mechanical and optical instruments for the diagnosis and healthcare administration of glaucoma, reviews state-of-the-art CDR calculation detail, and discusses the existing methods and databases. Image Analysis and Modeling in Ophthalmology includes the latest research development in the field of eye modeling and the multi-modality image processing techniques in ocular imaging. It addresses the differences, performance measures, advantages and disadvantages of various approaches, and provides extensive reviews on related fields.

The book is a collection of invited chapters by experts in Chinese document and text processing, and is part of a series on Language Processing, Pattern Recognition, and Intelligent Systems. The chapters introduce the latest advances and state-of-the-art methods for Chinese document image analysis and recognition, font design, text analysis and speaker recognition. Handwritten Chinese character recognition and text line recognition are at the core of document image analysis (DIA), and therefore, are addressed in four chapters for different scripts (online characters, offline characters, ancient characters, and text lines). Two chapters on character recognition pay much attention to deep convolutional neural networks (CNNs), which are widely used and performing superiorly in various pattern recognition problems. A chapter is contributed to describe a large handwriting database consisting both online and offline characters and text pages. Postal mail reading and writer identification, addressed in two chapters, are important applications of DIA. The collection can serve as reference for students and engineers in Chinese document and text processing and their applications.

Corona SDK is one of the most powerful tools used to create games and apps for mobile devices. The market requires speed; new developers need to operate quickly and efficiently. Create 2D Mobile Games with Corona SDK gives you the tools needed to master Corona - even within the framework of professional constraints. A must-read guide, this book gives you fast, accurate tips to learn the programming language necessary to create games. Read it sequentially or as an FAQ and you will have the tools you need to create any base game before moving on to advanced topics. The tutorial-based format: Contains step-by-step directions complete with coding and screenshots Is filled with tutorials, tips, and links to useful online resources Includes a comprehensive companion website featuring online exercise files to practice coding, full build samples from the text, additional book details, and more!

Avoiding heavy mathematics and lengthy programming details, Digital Image Processing: An Algorithmic Approach with MATLAB (R) presents an easy methodology for learning the fundamentals of image processing. The book applies the algorithms using MATLAB (R), without bogging down students with syntactical and debugging issues. One chapter can typically be completed per week, with each chapter divided into three sections. The first section presents theoretical topics in a very simple and basic style with generic language and mathematics. The second section explains the theoretical concepts using flowcharts to streamline the concepts and to form a foundation for students to code in any programming language. The final section supplies MATLAB codes for reproducing the figures presented in the chapter. Programming-based exercises at the end of each chapter facilitate the learning of underlying concepts through practice. This textbook equips undergraduate students in computer engineering and science with an essential understanding of digital image processing. It will also help them comprehend more advanced topics and sophisticated mathematical material in later courses. A color insert is included in the text while various instructor resources are available on the author's website.

As one of the most promising biometric technologies, vein pattern recognition (VPR) is quickly taking root around the world and may soon dominate applications where people focus is key. Among the reasons for VPR's growing acceptance and use: it is more accurate than many other biometric methods, it offers greater resistance to spoofing, it focuses on people and their privacy, and has few negative cultural connotations. Vein Pattern Recognition: A Privacy-Enhancing Biometric provides a comprehensive and practical look at biometrics in general and at vein pattern recognition specifically. It discusses the emergence of this reliable but underutilized technology and evaluates its capabilities and benefits. The author, Chuck Wilson, an industry veteran with more than 25 years of experience in the biometric and electronic security fields, examines current and emerging VPR technology along with the myriad applications of this dynamic technology. Wilson explains the use of VPR and provides an objective comparison of the different biometric methods in use today-including fingerprint, eye, face, voice recognition, and dynamic signature verification. Highlighting current VPR implementations, including its widespread acceptance and use for identity verification in the Japanese banking industry, the text provides a complete examination of how VPR can be used to protect sensitive information and secure critical facilities. Complete with best-practice techniques, the book supplies invaluable guidance on selecting the right combination of biometric technologies for specific applications and on properly implementing VPR as part of an overall security system.