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This volume includes papers presented at IIH-MSP 2017, the 13th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, held from 12 to 15 August 2017 in Matsue, Shimane, Japan. The conference addresses topics ranging from information hiding and security, and multimedia signal processing and networking, to bio-inspired multimedia technologies and systems. This volume of Smart Innovation, Systems and Technologies focuses on subjects related to massive image/video compression and transmission for emerging networks, advances in speech and language processing, 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. Updated with the latest research outcomes and findings, the papers presented appeal to researchers and students who are interested in the corresponding fields.

Image Processing and Communications represents an exciting and dynamic part of the information area. This book consists of 52 scientific and technical papers from 14 Nations, after a careful selection performed by many international reviewers. The papers are conveniently grouped into 6 chapters: - Computer Vision and Image Processing - Biometric - Recognition and Classification - Biomedical Image Processing - Applications - Communications. Each chapter focuses on a specific topic, presents results, and points out challenges and future directions.

This book is a collection of the papers accepted by the ICIVIS 2022—The International Conference on Image, Vision and Intelligent Systems, held on August 15–17, 2022, in Jinan, China. The topics focus but are not limited to image, vision and intelligent systems. Each part can be used as an excellent reference by industry practitioners, university faculties, research fellows and undergraduates as well as graduate students who need to build a knowledge base of the most current advances and state of practice in the topics covered by this conference proceedings.

This book is a collection of the papers accepted by the ICIVIS 2021—The International Conference on Image, Vision and Intelligent Systems held on June 15–17, 2021, in Changsha, China. The topics focus but are not limited to image, vision and intelligent systems. Each part can be used as an excellent reference by industry practitioners, university faculties, research fellows and undergraduates as well as graduate students who need to build a knowledge base of the most current advances and state-of-practice in the topics covered by this conference proceedings.

This book collects selected papers from the 7th Conference on Signal and Information Processing, Networking and Computers held in Rizhao, China, on September 21-23, 2020.The 7th International Conference on Signal and Information Processing, Networking and Computers (ICSINC) was held in Rizhao, China, on September 21-23, 2020.

This book is a collection of the best research papers presented at the 8th International Conference on Innovations in Electronics and Communication Engineering at Guru Nanak Institutions Hyderabad, India. Featuring contributions by researchers, technocrats and experts, the book covers various areas of communication engineering, like signal processing, VLSI design, embedded systems, wireless communications, and electronics and communications in general, as well as cutting-edge technologies. As such, it is a valuable reference resource for young researchers.

This book contains extended versions of papers presented at the international Conference VIPIMAGE 2009 – ECCOMAS Thematic Conference on Computational Vision and Medical Image, that was held at Faculdade de Engenharia da Universidade do Porto, Portugal, from 14th to 16th of October 2009. This conference was the second ECCOMAS thematic conference on computational vision and medical image processing. It covered topics related to image processing and analysis, medical imaging and computational modelling and simulation, considering their multidisciplinary nature. The book collects the state-of-the-art research, methods and new trends on the subject of computational vision and medical image processing contributing to the development of these knowledge areas.

This textbook for a one semester introductory course in digital signal processing for senior undergraduate and first year graduate students in electrical and computer engineering departments is concise, highly readable, and yet provides comprehensive coverage of the topic. Each new topic is presented with examples and figures. The highly mathematical content of the topic is presented lucidly to make the learning the subject easier. Practical aspects of the subject are clearly indicated so that the student can apply the principles in real applications. Matlab programs for FIR and IIR filter design are provided as supplementary material online.

This book presents experimental investigations and digital image processing, highlighting the interaction of polarized radiation with phase-inhomogeneous and optically anisotropic biological layers. The promising and efficient use of vector-parametric description of the formation of polarization-inhomogeneous object fields is noted. Applications of a set of Mueller-matrix polarimetry methods are highlighted. The book includes- structural and logical scheme of multi-parameter (singular, interference and layer-by-layer Stokes-polarimetric), polarization-correlation study of the structure of distributions of the number of singularities, maps of local contrast of interference distributions and layer-by-layer maps of microscopic polarization azimuth and ellipticity; determination of relationships between changes in the magnitude of statistical parameters characterizing polarization-correlation distributions and pathology of prostate tumors.

This book deals with the concept of medical ultrasound imaging and discusses array signal processing in ultrasound. Signal processing using different beamforming techniques in order to achieve a desirable reconstructed image and, consequently, obtain useful information about the imaging medium is the main focus of this book. In this regard, the principles of image reconstruction techniques in ultrasound imaging are fully described, and the required processing steps are completely expanded and analyzed in detail. Simulation results to compare the performance of different beamformers are also included in this book to visualize their differences to the reader. Other advanced techniques in the field of medical ultrasound data processing, as well as their corresponding recent achievements, are also presented in this book. Simply put, in this book, processing of medical ultrasound data from different aspects and acquiring information from them in different manners are covered and organized in different chapters. Before going through the detailed explanation in each chapter, it gives the reader an overview of the considered issue and focuses his\her mind on the challenge ahead. The contents of the book are also presented in such a way that they are easy for the reader to understand. This book is recommended for researchers who study medical ultrasound data processing.

This book investigates the image watermarking domain, analyzing and comparing image watermarking techniques that exist in current literature. The author's goal is to aid researchers and students in their studies in the vast and important domain of image watermarking, including its advantages and risks. The book has three chapters: image watermarking using data compression; speech modulation for image watermarking; and secure image watermarking based on LWT and SVD.In addition, this book: Investigates the image watermarking domain, analyzing and comparing current image watermarking techniquesIncludes detail on image encryption and mathematical tools used for image watermarkingCovers image watermarking using data compression, speech modulation for image watermarking, and more

​Signal Processing in Medicine and Biology: Innovations in Big Data Processing provides an interdisciplinary look at state-of-the-art innovations in biomedical signal processing, especially as it applies to large data sets and machine learning. Chapters are presented with detailed mathematics and complete implementation specifics so that readers can completely master these techniques. The book presents tutorials and examples of successful applications and will appeal to a wide range of professionals, researchers, and students interested in applications of signal processing, medicine, and biology at the intersection between healthcare, engineering, and computer science.

Image denoising, image deblurring, image inpainting, super-resolution, and compressed sensing reconstruction have important application value in engineering practice, and they are also the hot frontiers in the field of image processing. This book focuses on the numerical analysis of ill condition of imaging inverse problems and the methods of solving imaging inverse problems based on operator splitting. Both algorithmic theory and numerical experiments have been addressed. The book is divided into six chapters, including preparatory knowledge, ill-condition numerical analysis and regularization method of imaging inverse problems, adaptive regularization parameter estimation, and parallel solution methods of imaging inverse problem based on operator splitting. Although the research methods in this book take image denoising, deblurring, inpainting, and compressed sensing reconstruction as examples, they can also be extended to image processing problems such as image segmentation, hyperspectral decomposition, and image compression. This book can benefit teachers and graduate students in colleges and universities, or be used as a reference for self-study or further study of image processing technology engineers.

This book provides a comprehensive guide to 3D Light-Field camera based imaging, exploring the working principles, developments and its applications in fluid mechanics and aerodynamics measurements. It begins by discussing the fundamentals of Light-Field imaging and theoretical resolution analysis, before touching upon the detailed optics design and micro-lens array assembly. Subsequently, Light-Field calibration methods that compensate for optical distortions and establish the relations between the image and real-word 3D coordinates are covered. This is followed by Light-Field 3D reconstruction algorithms which are elaborated for micrometer-scale particles and centimeter-scale physical models. Last but not least, implementations of the preceding procedures to selected fundamental and applied flow measurement scenarios are provided at the end of the book. Development and Application of Light-Field Cameras in Fluid Measurements gives an in-depth analysis of each topic discussed, making it ideal as both an introductory and reference guide for researchers and postgraduates interested in 3D flow measurements.

This book offers the first comprehensive and practice-oriented guide to condition monitoring algorithms in MATLAB®. After a concise introduction to vibration theory and signal processing techniques, the attention is moved to the algorithms. Each signal processing algorithm is presented in depth, from the theory to the application, and including extensive explanations on how to use the corresponding toolbox in MATLAB®. In turn, the book introduces various techniques for synthetic signals generation, as well as vibration-based analysis techniques for large data sets. A practical guide on how to directly access data from industrial condition monitoring systems (CMS) using MATLAB®.NET Libraries is also included. Bridging between research and practice, this book offers an extensive guide on condition monitoring algorithms to both scholars and professionals. “Condition Monitoring Algorithms in MATLAB® is a great resource for anyone in the field of condition monitoring. It is a unique as it presents the theory, and a number of examples in Matlab®, which greatly improve the learning experience. It offers numerous examples of coding styles in Matlab, thus supporting graduate students and professionals writing their own codes.'Dr. Eric Bechhoefer Founder and CEO of GPMS Developer of the Foresight MX Health and Usage Monitoring System

This textbook provides an introduction to the study of digital signal processing, employing a top-to-bottom structure to motivate the reader, a graphical approach to the solution of the signal processing mathematics, and extensive use of MATLAB.In contrast to the conventional teaching approach, the book offers a top-down approach which first introduces students to digital filter design, provoking questions about the mathematical tools required. The following chapters provide answers to these questions, introducing signals in the discrete domain, Fourier analysis, filters in the time domain and the Z-transform. The author introduces the mathematics in a conceptual manner with figures to illustrate the physical meaning of the equations involved. Chapter six builds on these concepts and discusses advanced filter design, and chapter seven discusses matters of practical implementation. This book introduces the corresponding MATLAB functions and programs in everychapter with examples, and the final chapter introduces the actual real-time filter from MATLAB.Aimed primarily at undergraduate students in electrical and electronic engineering, this book enables the reader to implement a digital filter using MATLAB.Deliver the conceptual knowledge of digital signal processing with extensive use of the illustrations from practical viewpoint. Also, the digital signal processing is initiated from the digital not from the continuous domain.

Pregnancy is a critical time for the health of the mother and the fetus, with important potential risks for both. Tools for antenatal diagnosis and pregnancy monitoring can support prevention and management of potential risks and complications. In particular, the perinatal period, spanning from the third trimester of pregnancy up to one month after birth, is the most critical for the baby. For this reason, in the last decades, biomedical engineering supported and fostered the scientific research towards the identification of new models, parameters, algorithms, and tools that can improve the quality of fetal monitoring, predict the outcomes and allow physicians to intervene in an appropriate manner to ensure a healthy future for the baby. This book follows the First International Summer School on Technologies and Signal Processing in Perinatal Medicine and reflects some of its most important master lectures. It represents a valuable guide for students and young researchers approaching this topic for the first time, as well as experienced researchers and practitioners looking for a clear representation of the themes and techniques presented by recognized experts in the field. Presents current and innovative technologies for fetal and neonatal monitoring Emphasis on both technology/signal processing and clinical aspectsOffers a clear didactic approach to the subject matter

Graph spectral image processing is the study of imaging data from a graph frequency perspective. Modern image sensors capture a wide range of visual data including high spatial resolution/high bit-depth 2D images and videos, hyperspectral images, light field images and 3D point clouds. The field of graph signal processing – extending traditional Fourier analysis tools such as transforms and wavelets to handle data on irregular graph kernels – provides new flexible computational tools to analyze and process these varied types of imaging data. Recent methods combine graph signal processing ideas with deep neural network architectures for enhanced performances, with robustness and smaller memory requirements.The book is divided into two parts. The first is centered on the fundamentals of graph signal processing theories, including graph filtering, graph learning and graph neural networks. The second part details several imaging applications using graph signal processing tools, including image and video compression, 3D image compression, image restoration, point cloud processing, image segmentation and image classification, as well as the use of graph neural networks for image processing.

Advances in Imaging and Electron Physics, Volume 218 merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The series features articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science, digital image processing, electromagnetic wave propagation, electron microscopy and the computing methods used in all these domains. Specific chapters in this release cover Phase retrieval methods applied to coherent imaging, X-ray phase-contrast imaging: a broad overview of some fundamentals, Graphene and borophene as nanoscopic materials for electronics – with review of the physics, and more. - Provides the authority and expertise of leading contributors from an international board of authors - Presents the latest release in the Advances in Imaging and Electron Physics series - Updated release includes the latest information on the Coulomb Interactions in Charged Particle Beams

This book systematically summarizes China Internet development over the past 25 years, highlighting its strong impact on China's economy and society, and discussing the Chinese people's transition from beneficiaries and participants to builders, contributors and joint maintainers of cyberspace development. It describes the development achievements, status and development and trends in China Internet in 2019, systematically summarizes the main lessons learned during development, and analyzes China's strategic planning and policy actions. Further, it discusses topics such as development outcomes, future trends in information infrastructure, network information technology, digital economy, e-government, construction and management of network contents, cyberspace security, the legal construction of cyberspace, and international cyberspace governance. In addition, the book suggests improvements to the index system for China Internet development and offers an overall assessment of cyberspace security and informatization work throughout China in order to comprehensively and accurately demonstrate the level of China Internet development.

Principles of Image Printing Technology is a unique review of technology use in the printing industry since the time of the medieval engravers and busy newsroom typesetters. It provides a historical review of the advancement of technology and describes in-depth both technical fundamentals and industrial procedures. Intended primarily for students in graphic communications programs, this book includes all the necessary background for understanding printing technology. In addition, by providing findings from basic research studies and industrial processes that have been omitted elsewhere in published volumes, it offers a useful guide to researchers and professionals in the printing industry.

This book presents the select proceedings of Control Instrumentation and System Conference, (CISCON 2020) held at Manipal Institute of Technology, MAHE, Manipal. It examines a wide spectrum covering the latest trends in the fields of instrumentation, sensors and systems, and industrial automation and control. The topics covered include image and signal processing, robotics, renewable energy, power systems and power drives, performance attributes of MEMS, multi-sensor data fusion, machine learning, optimization techniques, process control, safety monitoring, safety critical control, supervisory control, system modeling and virtual instrumentation. The book is a valuable reference for researchers and professionals interested in sensors, adaptive control, automation and control and allied fields.

This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for deep learning, Natural Language Processing (NLP), speech recognition, and general predictive analytics. The book provides a hands-on approach to TensorFlow fundamentals for a broad technical audience—from data scientists and engineers to students and researchers. The authors begin by working through some basic examples in TensorFlow before diving deeper into topics such as CNN, RNN, LSTM, and GNN. The book is written for those who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open source Python libraries. The authors demonstrate TensorFlow projects on Single Board Computers (SBCs).

This volume provides international case studies of practical and advanced methods using satellite images integrated with other airborne, drone images and field data to monitor infrastructure. The book is timely, as infrastructure spending by national governments is increasing and robust monitoring techniques are needed to keep pace with climate change impacts affecting infrastructures globally. The expert international contributions that comprise the book provide examples of advanced methods using InSAR, high-resolution optical and radar images, LIDAR, UAV, geophysical techniques and their applications to civil infrastructure. The case studies focus on high-resolution, rapid time-series radar interferometry to monitor highways, railways, pipelines, bridges, urban, and water conveyance infrastructures. Other case studies use optical and radar images to characterize urban infrastructure and monitor damages from floods, oil spills and conflicts. The case studies are global focusing on infrastructure projects in Canada, Dominica Guyana, India Italy, Syria Taiwan, United States and the United Kingdom. This compilation of selected case studies will provide useful guidelines for the civil infrastructure characterization and monitoring communities. The book will be of interest to infrastructure consultants and professionals, scientific communities in earth observation and advanced imaging methods, and researchers and professors in earth sciences, climate change, and civil and geoengineering.

This book covers current technological innovations and applications in image processing, introducing analysis techniques and describing applications in remote sensing and manufacturing, among others. The authors include new concepts of color space transformation like color interpolation, among others. Also, the concept of Shearlet Transform and Wavelet Transform and their implementation are discussed. The authors include a perspective about concepts and techniques of remote sensing like image mining, geographical, and agricultural resources. The book also includes several applications of human organ biomedical image analysis. In addition, the principle of moving object detection and tracking — including recent trends in moving vehicles and ship detection – is described.Presents developments of current research in various areas of image processing;Includes applications of image processing in remote sensing, astronomy, and manufacturing;Pertains to researchers, academics, students, and practitioners in image processing.

This book provides a comprehensive study of the research outcomes on memristor emulator circuits and includes various analog applications as examples. The authors describe in detail how to design different types of memristor emulators, using active and passive components for different applications. Most of the emulator circuits presented in this book are new and are the outcomes of the authors'recent research. Coverage also includes the latest technological advances in memristor and memristor emulators. Readers will benefit from an understanding of the fundamental concepts and potential applications related to memristors, since these emulator circuits can be built in the laboratory using inexpensive, off-the-shelf circuit components.Introduces readers to memristor emulator circuit design, using regular off-the-shelf circuit components;Describes analog applications of memristors that can be verified by the proposed emulator circuits;Includesa brief overview of the updated mathematical models of the memristor device, with different material implementations;Equips readers to understand the three fingerprints of memristors, which make them unique, compared to the three known, passive elements (resistor, inductor and capacitor).

This book provides a survey of deep learning approaches to domain adaptation in computer vision. It gives the reader an overview of the state-of-the-art research in deep learning based domain adaptation. This book also discusses the various approaches to deep learning based domain adaptation in recent years. It outlines the importance of domain adaptation for the advancement of computer vision, consolidates the research in the area and provides the reader with promising directions for future research in domain adaptation.Divided into four parts, the first part of this book begins with an introduction to domain adaptation, which outlines the problem statement, the role of domain adaptation and the motivation for research in this area. It includes a chapter outlining pre-deep learning era domain adaptation techniques. The second part of this book highlights feature alignment based approaches to domain adaptation. The third part of this book outlines image alignment procedures for domain adaptation. The final section of this book presents novel directions for research in domain adaptation. This book targets researchers working in artificial intelligence, machine learning, deep learning and computer vision. Industry professionals and entrepreneurs seeking to adopt deep learning into their applications will also be interested in this book.

This book provides an in-depth coverage of the most recent developments in the field of wireless underground communications, from both theoretical and practical perspectives. The authors identify technical challenges and discuss recent results related to improvements in wireless underground communications and soil sensing in Internet of Underground Things (IOUT). The book covers both existing network technologies and those currently in development in three major areas of SitS: wireless underground communications, subsurface sensing, and antennas in the soil medium. The authors explore novel applications of Internet of Underground Things in digital agriculture and autonomous irrigation management domains. The book is relevant to wireless researchers, academics, students, and decision agriculture professionals. The contents of the book are arranged in a comprehensive and easily accessible format.Focuses on fundamental issues of wireless underground communication and subsurface sensing;Includes advanced treatment of IOUT custom applications of variable-rate technologies in the field of decision agriculture, and covers protocol design and wireless underground channel modeling;Provides a detailed set of path loss, antenna, and wireless underground channel measurements in various novel Signals in the Soil (SitS) testbed settings.

This book provides readers with the necessary background information and advanced concepts in the field of circuits, at the crossroads between physics, mathematics and system theory. It covers various engineering subfields, such as electrical devices and circuits, and their electronic counterparts. Based on the idea that a modern university course should provide students with conceptual tools to understand the behavior of both linear and nonlinear circuits, to approach current problems posed by new, cutting-edge devices and to address future developments and challenges, the book places equal emphasis on linear and nonlinear, two‐terminal and multi‐terminal, as well as active and passive circuit components. This second volume focuses on dynamical circuits, which are characterized by time evolution and by the concept of state. The content is divided into a set of introductory and a set of advanced‐level topics, mirroring the approach used in the previously published volume. Whenever possible, circuits are compared to physical systems of different natures (e.g. mechanical or biological) that exhibit the same dynamical behavior. The book also features a wealth of examples and numerous solved problems. Further topics, such as a more general framing of linear and nonlinear components, will be discussed in volume 3.

This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas ofimage analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.

This book serves as an easily accessible reference for wireless digital communication systems. Topics are presented with simple but non-trivial examples and then elaborated with their variations and sophistications. The book includes numerous examples and exercises to illustrate key points. For this new edition, a set of problems at the end of each chapter is added, for a total of 298 problems. The book emphasizes both practical problem solving and a thorough understanding of fundamentals, aiming to realize the complementary relationship between practice and theory. Though the author emphasizes wireless radio channels, the fundamentals that are covered here are useful to different channels - digital subscriber line, coax, power lines, optical fibers, and even Gigabit serial connections. The material in chapters 5 (OFDM), 6 (Channel coding), 7 (Synchronization), and 8 (Transceivers) contains new and updated information, not explicitly available in typical textbooks, anduseful in practice. For example, in chapter 5, all known orthogonal frequency division multiplex signals are derived from its digitized analog FDM counterparts. Thus, it is flexible to have different pulse shape for subcarriers, and it can be serial transmission as well as block transmission. Currently predominant cyclic prefix based OFDM is a block transmission using rectangular pulse in time domain. This flexibility may be useful in certain applications. For additional information, consult the book support website: https://baycorewireless.com

Advances in Imaging and Electron Physics, Volume 209, merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The series features extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science, digital image processing, electromagnetic wave propagation, electron microscopy and the computing methods used in all these domains. - Contains contributions from leading authorities on the subject matter - Informs and updates on the latest developments in the field of imaging and electron physics - Provides practitioners interested in microscopy, optics, image processing, mathematical morphology, electromagnetic fields, electrons and ion emission with a valuable resource - Features extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science and digital image processing

This book covers all main aspects of guidance information processing technologies for airborne optical imaging seekers, including theoretical models; image pre-processing; automatic target detection, recognition and tracking; and embedded real-time processing systems. The book is divided into three major sections: firstly, a theoretical model for optical-seeker information processing is introduced; then information processing methods are presented, including target modeling, online image pre-processing, typical surface fixed-target detection and recognition, and moving-target detection and recognition; lastly, embedded real-time processing systems are introduced, including new system architectures, image processing ASIC/SoC design, embedded real-time operating systems, system implementation aspects, and system testing and evaluation technologies. The book offers a unique and valuable resource, helping readers understand both fundamental and advanced information processing technologiesemployed in airborne optical imaging seekers.

This book provides a platform for exploring nature-inspired optimization techniques in the context of imaging applications. Optimization has become part and parcel of all computational vision applications, and since the amount of data used in these applications is vast, the need for optimization techniques has increased exponentially. These accuracy and complexity are a major area of concern when it comes to practical applications. However, these optimization techniques have not yet been fully explored in the context of imaging applications. By presenting interdisciplinary concepts, ranging from optimization to image processing, the book appeals to a broad readership, while also encouraging budding engineers to pursue and employ innovative nature-inspired techniques for image processing applications.

Image quality assessment (IQA) is an essential technique in the design of modern, large-scale image and video processing systems. This book introduces and discusses in detail topics related to IQA, including the basic principles of subjective and objective experiments, biological evidence for image quality perception, and recent research developments. In line with recent trends in imaging techniques and to explain the application-specific utilization, it particularly focuses on IQA for stereoscopic (3D) images and medical images, rather than on planar (2D) natural images. In addition, a wealth of vivid, specific figures and formulas help readers deepen their understanding of fundamental and new applications for image quality assessment technology. This book is suitable for researchers, clinicians and engineers as well as students working in related disciplines, including imaging, displaying, image processing, and storage and transmission. By reviewing and presenting the latest advances, and new trends and challenges in the field, it benefits researchers and industrial R&D engineers seeking to implement image quality assessment systems for specific applications or design/optimize image/video processing algorithms.

This edited volume contains technical contributions in the field of computer vision and image processing presented at the First International Conference on Computer Vision and Image Processing (CVIP 2016). The contributions are thematically divided based on their relation to operations at the lower, middle and higher levels of vision systems, and their applications. The technical contributions in the areas of sensors, acquisition, visualization and enhancement are classified as related to low-level operations. They discuss various modern topics – reconfigurable image system architecture, Scheimpflug camera calibration, real-time autofocusing, climate visualization, tone mapping, super-resolution and image resizing. The technical contributions in the areas of segmentation and retrieval are classified as related to mid-level operations. They discuss some state-of-the-art techniques – non-rigid image registration, iterative image partitioning, egocentric object detection and video shot boundary detection. The technical contributions in the areas of classification and retrieval are categorized as related to high-level operations. They discuss some state-of-the-art approaches – extreme learning machines, and target, gesture and action recognition. A non-regularized state preserving extreme learning machine is presented for natural scene classification. An algorithm for human action recognition through dynamic frame warping based on depth cues is given. Target recognition in night vision through convolutional neural network is also presented. Use of convolutional neural network in detecting static hand gesture is also discussed. Finally, the technical contributions in the areas of surveillance, coding and data security, and biometrics and document processing are considered as applications of computer vision and image processing. They discuss some contemporary applications. A few of them are a system for tackling blind curves, a quick reaction target acquisition and tracking system, an algorithm to detect for copy-move forgery based on circle block, a novel visual secret sharing scheme using affine cipher and image interleaving, a finger knuckle print recognition system based on wavelet and Gabor filtering, and a palmprint recognition based on minutiae quadruplets.

This graduate textbook explains image reconstruction technologies based on region-based binocular and trinocular stereo vision, and object, pattern and relation matching. It further discusses principles and applications of multi-sensor fusion and content-based retrieval. Rich in examples and excises, the book concludes image engineering studies for electrical engineering and computer science students.

This graduate textbook presents fundamentals, applications and evaluation of image segregation, unit description, feature measurement and pattern recognition. Analysis on textile, shape and motion are discussed and mathematical tools are employed extensively. Rich in examples and excises, it prepares electrical engineering and computer science students with knowledge and skills for further studies on image understanding.

This graduate textbook explains image geometry, and elaborates on image enhancement in spatial and frequency domain, unconstrained and constrained restoration and restoration from projection, and discusses various coding technologies such as predictive coding and transform coding. Rich in examples and exercises, it prepares electrical engineering and computer science students for further studies on image analysis and understanding.

This edited volume contains technical contributions in the field of computer vision and image processing presented at the First International Conference on Computer Vision and Image Processing (CVIP 2016). The contributions are thematically divided based on their relation to operations at the lower, middle and higher levels of vision systems, and their applications. The technical contributions in the areas of sensors, acquisition, visualization and enhancement are classified as related to low-level operations. They discuss various modern topics – reconfigurable image system architecture, Scheimpflug camera calibration, real-time autofocusing, climate visualization, tone mapping, super-resolution and image resizing.The technical contributions in the areas of segmentation and retrieval are classified as related to mid-level operations. They discuss some state-of-the-art techniques – non-rigid image registration, iterative image partitioning, egocentric object detection and video shot boundary detection.The technical contributions in the areas of classification and retrieval are categorized as related to high-level operations. They discuss some state-of-the-art approaches – extreme learning machines, and target, gesture and action recognition. A non-regularized state preserving extreme learning machine is presented for natural scene classification. An algorithm for human action recognition through dynamic frame warping based on depth cues is given. Target recognition in night vision through convolutional neural network is also presented. Use of convolutional neural network in detecting static hand gesture is also discussed.Finally, the technical contributions in the areas of surveillance, coding and data security, and biometrics and document processing are considered as applications of computer vision and image processing. They discuss some contemporary applications. A few of them are a system for tackling blind curves, a quick reaction target acquisition and tracking system, an algorithm to detect for copy-move forgery based on circle block, a novel visual secret sharing scheme using affine cipher and image interleaving, a finger knuckle print recognition system based on wavelet and Gabor filtering, anda palmprint recognition based on minutiae quadruplets.

This book provides an introduction to fuzzy logic approaches useful in image processing. The authors start by introducing image processing tasks of low and medium level such as thresholding, enhancement, edge detection, morphological filters, and segmentation and shows how fuzzy logic approaches apply. The book is divided into two parts. The first includes vagueness and ambiguity in digital images, fuzzy image processing, fuzzy rule based systems, and fuzzy clustering. The second part includes applications to image processing, image thresholding, color contrast enhancement, edge detection, morphological analysis, and image segmentation. Throughout, they describe image processing algorithms based on fuzzy logic under methodological aspects in addition to applicative aspects. Implementations in java are provided for the various applications.

This book discusses the design of multi-camera systems and their application to fields such as the virtual reality, gaming, film industry, medicine, automotive industry, drones, etc. The authors cover the basics of image formation, algorithms for stitching a panoramic image from multiple cameras, and multiple real-time hardware system architectures, in order to have panoramic videos. Several specific applications of multi-camera systems are presented, such as depth estimation, high dynamic range imaging, and medical imaging.

This book presents medical image watermarking techniques and algorithms for telemedicine and other emerging applications. This book emphasizes on medical image watermarking to ensure the authenticity of transmitted medical information. It begins with an introduction of digital watermarking, important characteristics, novel applications, different watermarking attacks and standard benchmark tools. This book also covers spatial and transform domain medical image watermarking techniques and their merits and limitations. The authors have developed improved/novel watermarking techniques for telemedicine applications that offer higher robustness, better perceptual quality and increased embedding capacity and secure watermark. The suggested methods may find potential applications in the prevention of patient identity theft and health data management issues which is a growing concern in telemedicine applications. This book provides a sound platform for understanding the medical image watermarking paradigm for researchers in the field and advanced-level students. Industry professionals working in this field, as well as other emerging applications demanding robust and secure watermarking will find this book useful as a reference.

This book describes the fundamental building-block of many new computer vision systems: dense and robust correspondence estimation. Dense correspondence estimation techniques are now successfully being used to solve a wide range of computer vision problems, very different from the traditional applications such techniques were originally developed to solve. This book introduces the techniques used for establishing correspondences between challenging image pairs, the novel features used to make these techniques robust, and the many problems dense correspondences are now being used to solve. The book provides information to anyone attempting to utilize dense correspondences in order to solve new or existing computer vision problems. The editors describe how to solve many computer vision problems by using dense correspondence estimation. Finally, it surveys resources, code and data, necessary for expediting the development of effective correspondence-based computer vision systems.

This book presents a comprehensive treatise on Riemannian geometric computations and related statistical inferences in several computer vision problems. This edited volume includes chapter contributions from leading figures in the field of computer vision who are applying Riemannian geometric approaches in problems such as face recognition, activity recognition, object detection, biomedical image analysis, and structure-from-motion. Some of the mathematical entities that necessitate a geometric analysis include rotation matrices (e.g. in modeling camera motion), stick figures (e.g. for activity recognition), subspace comparisons (e.g. in face recognition), symmetric positive-definite matrices (e.g. in diffusion tensor imaging), and function-spaces (e.g. in studying shapes of closed contours).

This book presents the use of efficient Evolutionary Computation (EC) algorithms for solving diverse real-world image processing and pattern recognition problems. It provides an overview of the different aspects of evolutionary methods in order to enable the reader in reaching a global understanding of the field and, in conducting studies on specific evolutionary techniques that are related to applications in image processing and pattern recognition. It explains the basic ideas of the proposed applications in a way that can also be understood by readers outside of the field. Image processing and pattern recognition practitioners who are not evolutionary computation researchers will appreciate the discussed techniques beyond simple theoretical tools since they have been adapted to solve significant problems that commonly arise on such areas. On the other hand, members of the evolutionary computation community can learn the way in which image processing and pattern recognition problems can be translated into an optimization task. The book has been structured so that each chapter can be read independently from the others. It can serve as reference book for students and researchers with basic knowledge in image processing and EC methods.

This text covers state-of-the-art color image and video enhancement techniques. The book examines the multivariate nature of color image/video data as it pertains to contrast enhancement, color correction (equalization, harmonization, normalization, balancing, constancy, etc.), noise removal and smoothing. This book also discusses color and contrast enhancement in vision sensors and applications of image and video enhancement.

This book first introduces classic as well as recent computational models for just-noticeable-difference (JND) applications. Since the discrete cosine transform (DCT) is applied in many image and video standards (JPEG, MPEG-1/2/4, H.261/3), the book also includes a comprehensive survey of computational models for JND that are based on DCT. The visual factors used in these computational models are reviewed in detail. Further, an extensive comparative analysis of these models using quantitative and qualitative performance criteria is presented, which compares the noise shaping performance of these models with subjective evaluation and the accuracy between the estimated JND thresholds and subjective evaluation.There are many surveys available on computational models for JND; however, these surveys seldom compare the performance of computational models that are based on DCT. The authors'survey of the computational models and their in-depth review of the visual factors used in them will help readers understand perceptual image coding based on DCT. The book also provides a comparative analysis of several perceptual image coders that are based on DCT, which are compatible with the highly popular and widely adopted JPEG standard.

This thesis primarily focuses on how to carry out intelligent sensing and understand the high-dimensional and low-quality visual information. After exploring the inherent structures of the visual data, it proposes a number of computational models covering an extensive range of mathematical topics, including compressive sensing, graph theory, probabilistic learning and information theory. These computational models are also applied to address a number of real-world problems including biometric recognition, stereo signal reconstruction, natural scene parsing, and SAR image processing.

This fourth 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 Image, Video Processing and Analysis, Hardware, Audio, Acoustic and Speech Processing. 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 Image, Video Processing and Analysis, Hardware, Audio, Acoustic and Speech Processing - Presents core principles and shows their application - 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