As colour imaging takes on increasing importance in a range of products and technologies, colour fidelity across different media has become essential.

This book has arisen from the need for a specialist text that brings together key developments in colour management technology and findings from the colour engineering research community.

Edited by highly regarded specialists in colour management systems, Colour Engineering introduces the reader systematically to the art of constistent quality of image reproduction - regardless of the monitor or graphic user interface employed.

Features:

• a thorough review of the elements of colour science that apply to colour imaging.

• a comprehensive analysis of methods for characterizing devices in the colour imaging chain.

• a review of the key topics in colour management.

• the different approaches to implementing colour systems at some of the leading exponents in the imaging industry.

This book presents cutting-edge research on various ways to bridge the semantic gap in image and video analysis. The respective chapters address different stages of image processing, revealing that the first step is a future extraction, the second is a segmentation process, the third is object recognition, and the fourth and last involve the semantic interpretation of the image. The semantic gap is a challenging area of research, and describes the difference between low-level features extracted from the image and the high-level semantic meanings that people can derive from the image. The result greatly depends on lower level vision techniques, such as feature selection, segmentation, object recognition, and so on. The use of deep models has freed humans from manually selecting and extracting the set of features. Deep learning does this automatically, developing more abstract features at the successive levels. The book offers a valuable resource for researchers, practitioners, students and professors in Computer Engineering, Computer Science and related fields whose work involves images, video analysis, image interpretation and so on.

This book constitutes the refereed proceedings of the 17th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2021, held virtually and in Hersonissos, Crete, Greece, in June 2021. The 50 full papers and 11 short papers presented were carefully reviewed and selected from 113 submissions. They cover a broad range of topics related to technical, legal, and ethical aspects of artificial intelligence systems and their applications and are organized in the following sections: adaptive modeling/ neuroscience; AI in biomedical applications; AI impacts/ big data; automated machine learning; autonomous agents; clustering; convolutional NN; data mining/ word counts; deep learning; fuzzy modeling; hyperdimensional computing; Internet of Things/ Internet of energy; machine learning; multi-agent systems; natural language; recommendation systems; sentiment analysis; and smart blockchain applications/ cybersecurity. Chapter "Improving the Flexibility of Production Scheduling in Flat Steel Production Through Standard and AI-based Approaches: Challenges and Perspective" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Augmented Reality (AR) refers to the merging of a live view of the physical, real world with context-sensitive, computer-generated images to create a mixed reality. Through this augmented vision, a user can digitally interact with and adjust information about their surrounding environment on-the-fly. "Handbook of Augmented Reality" provides an extensive overview of the current and future trends in Augmented Reality, and chronicles the dramatic growth in this field. The book includes contributions from world expert s in the field of AR from academia, research laboratories and private industry. Case studies and examples throughout the handbook help introduce the basic concepts of AR, as well as outline the Computer Vision and Multimedia techniques most commonly used today. The book is intended for a wide variety of readers including academicians, designers, developers, educators, engineers, practitioners, researchers, and graduate students. This book can also be beneficial for business managers, entrepreneurs, and investors.

This book explores a central question in the study of depth perception - 'does the visual system rely upon objective knowledge and subjective meaning to specify visual depth?' Linton advances an alternative interpretation to the generally accepted affirmative answer, according to which many of the apparent contributions of knowledge and meaning to depth perception are better understood as contributions to our post-perceptual cognition of depth. In order to defend this position a new account of visual cognition is required, as well as a better understanding of the optical and physiological cues to depth. This book will appeal to students and researchers in psychology, vision science, and philosophy, as well as technologists and content creators working in virtual and augmented reality.

This useful textbook/reference presents an accessible primer on the fundamentals of image texture analysis, as well as an introduction to the K-views model for extracting and classifying image textures. Divided into three parts, the book opens with a review of existing models and algorithms for image texture analysis, before delving into the details of the K-views model. The work then concludes with a discussion of popular deep learning methods for image texture analysis. Topics and features: provides self-test exercises in every chapter; describes the basics of image texture, texture features, and image texture classification and segmentation; examines a selection of widely-used methods for measuring and extracting texture features, and various algorithms for texture classification; explains the concepts of dimensionality reduction and sparse representation; discusses view-based approaches to classifying images; introduces the template for the K-views algorithm, as well as a range of variants of this algorithm; reviews several neural network models for deep machine learning, and presents a specific focus on convolutional neural networks. This introductory text on image texture analysis is ideally suitable for senior undergraduate and first-year graduate students of computer science, who will benefit from the numerous clarifying examples provided throughout the work.

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.

This book reviews the state of the art in deep learning approaches to high-performance robust disease detection, robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities), and the construction and mining of large-scale radiology databases. It particularly focuses on the application of convolutional neural networks, and on recurrent neural networks like LSTM, using numerous practical examples to complement the theory. The book's chief features are as follows: It highlights how deep neural networks can be used to address new questions and protocols, and to tackle current challenges in medical image computing; presents a comprehensive review of the latest research and literature; and describes a range of different methods that employ deep learning for object or landmark detection tasks in 2D and 3D medical imaging. In addition, the book examines a broad selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to text and image deep embedding for a large-scale chest x-ray image database; and discusses how deep learning relational graphs can be used to organize a sizable collection of radiology findings from real clinical practice, allowing semantic similarity-based retrieval.The intended reader of this edited book is a professional engineer, scientist or a graduate student who is able to comprehend general concepts of image processing, computer vision and medical image analysis. They can apply computer science and mathematical principles into problem solving practices. It may be necessary to have a certain level of familiarity with a number of more advanced subjects: image formation and enhancement, image understanding, visual recognition in medical applications, statistical learning, deep neural networks, structured prediction and image segmentation.

This comprehensive and timely publication aims to be an essential reference source, building on the available literature in the field of Gamification for the economic and social development of countries while providing further research opportunities in this dynamic and growing field. Thus, the book aims to provide the opportunity for a reflection on this important issue, increasing the understanding of the importance of Gamification in the context of organizations' improvements, providing relevant academic work, empirical research findings and, an overview of this relevant field of study. This text will provide the resources necessary for policymakers, technology developers, and managers to adopt and implement solutions for a more digital era.

This volume is the most comprehensive reference work on visual communications to date. An international group of well-known experts in the field provide up-to-date and in-depth contributions on topics such as fundamental theory, international standards for industrial applications, high definition television, optical communications networks, and VLSI design. The book includes information for learning about both the fundamentals of image/video compression as well as more advanced topics in visual communications research. In addition, the Handbook of Visual Communications explores the latest developments in the field, such as model-based image coding, and provides readers with insight into possible future developments.
Key Features
* Displays comprehensive coverage from fundamental theory to international standards and VLSI design
* Includes 518 pages of contributions from well-known experts
* please keep this feature current with the page count]
* Presents state-of-the-art knowledge--the most up-to-date and accurate information on various topics in the field
* Provides an extensive overview of international standards for industrial applications

Modern life is increasingly relying on digital technology, which in turn runs on mathematics. However, this underlying math is hidden from us. That is mostly a good thing since we do not want to be solving equations and calculating fractions just to get things done in our everyday business. But the mathematical details do matter for anyone who wants to understand how stuff works, or wishes to create something new in the jungle of apps and algorithms. This book takes a look at the mathematical models behind weather forecasting, climate change prediction, artificial intelligence, medical imaging and computer graphics. The reader is expected to have only a curious mind; technical math skills are not needed for enjoying this text.

This thesis reports on sparsity-based multipath exploitation methods for through-the-wall radar imaging. Multipath creates ambiguities in the measurements provoking unwanted ghost targets in the image. This book describes sparse reconstruction methods that are not only suppressing the ghost targets, but using multipath to one's advantage. With adopting the compressive sensing principle, fewer measurements are required for image reconstruction as compared to conventional techniques. The book describes the development of a comprehensive signal model and some associated reconstruction methods that can deal with many relevant scenarios, such as clutter from building structures, secondary reflections from interior walls, as well as stationary and moving targets, in urban radar imaging. The described methods are evaluated here using simulated as well as measured data from semi-controlled laboratory experiments.

This book provides a deep analysis and wide coverage of the very strong trend in computer vision and visual indexing and retrieval, covering such topics as incorporation of models of Human Visual attention into analysis and retrieval tasks. It makes the bridge between psycho-visual modelling of Human Visual System and the classical and most recent models in visual content indexing and retrieval. The large spectrum of visual tasks, such as recognition of textures in static images, of actions in video content, image retrieval, different methods of visualization of images and multimedia content based on visual saliency are presented by the authors. Furthermore, the interest in visual content is modelled with the means of the latest classification models such as Deep Neural Networks is also covered in this book. This book is an exceptional resource as a secondary text for researchers and advanced level students, who are involved in the very wide research in computer vision, visual information indexing and retrieval. Professionals working in this field will also be interested in this book as a reference.

This book includes original research findings in the field of memetic algorithms for image processing applications. It gathers contributions on theory, case studies, and design methods pertaining to memetic algorithms for image processing applications ranging from defence, medical image processing, and surveillance, to computer vision, robotics, etc. The content presented here provides new directions for future research from both theoretical and practical viewpoints, and will spur further advances in the field.

This book presents different approaches on multi-modality imaging with a focus on biomedical applications. Medical imaging can be divided into two categories: functional (related to physiological body measurements) and anatomical (structural) imaging modalities. In particular, this book covers imaging combinations coming from the usual popular modalities (such as the anatomical modalities, e.g. X-ray, CT and MRI), and it also includes some promising and new imaging modalities that are still being developed and improved (such as infrared thermography (IRT) and photoplethysmography imaging (PPGI)), implying potential approaches for innovative biomedical applications. Moreover, this book includes a variety of tools on computer vision, imaging processing, and computer graphics, which led to the generation and visualization of 3D models, making the most recent advances in this area possible. This is an ideal book for students and biomedical engineering researchers covering the biomedical imaging field.

This book presents covert, semi-covert and overt techniques for communication over printed media by modifying images, texts or barcodes within the document. Basic and advanced techniques are discussed aimed to modulate information into images, texts and barcodes. Conveying information over printed media can be useful for content authentication, author copyright, information and piracy product deterrent, side information for marketing, among other applications. Practical issues are discussed and experiments are provided to evaluate competitive approaches for hard-copy communication. This book is a useful resource for researchers, practitioners and graduate students in the field of hard-copy communication by providing the fundamentals, basic and advanced techniques as examples of approaches to address the hard-copy media distortions and particularities.

The Second Edition is an updated revision to the authors highly successful and widely used introduction to the principles and application of the statistical theory of signal detection. This book emphasizes those theories that have been found to be particularly useful in practice including principles applied to detection problems encountered in digital communications, radar, and sonar.
Detection processing based upon the fast Fourier transform

Semantic-based visual information retrieval is one of the most challenging research directions of content-based visual information retrieval. It provides efficient tools for access, interaction, searching, and retrieving from collected databases of visual media. Building on research from over 30 leading experts from around the world, ""Semantic-Based Visual Information Retrieval"" presents state-of-the-art advancements and developments in the field, and also brings a selection of techniques and algorithms about semantic-based visual information retrieval. It covers many critical issues, such as: multi-level representation and description, scene understanding, semantic modeling, image and video annotation, humancomputer interaction, and more. ""Semantic-Based Visual Information Retrieval"" also explains detailed solutions to a wide range of practical applications. Researchers, students, and practitioners will find this comprehensive and detailed volume to be a roadmap for applying suitable methods in semantic-based visual information retrieval.

Mathematical morphology (MM) is a theory for the analysis of spatial structures. It is called morphology since it aims at analyzing the shape and form of objects, and it is mathematical in the sense that the analysis is based on set theory, topology, lattice algebra, random functions, and so on. MM is not only a "theory", but also a powerful image analysis "technique". The purpose of the present book is to provide the image analysis community with a snapshot of current theoretical and applied developments of MM. The book consists of 45 contributions classified by subject. It demonstrates a range of topics suited to the morphological approach.

Photographic imagery has come a long way from the pinhole cameras of the nineteenth century. Digital imagery, and its applications, develops in tandem with contemporary society's sophisticated literacy of this subtle medium. This book examines the ways in which digital images have become ever more ubiquitous as legal and medical evidence, just as they have become our primary source of news and have replaced paper-based financial documentation. Crucially, the contributions also analyze the very profound problems which have arisen alongside the digital image, issues of veracity and progeny that demand systematic and detailed response: It looks real, but is it? What camera captured it? Has it been doctored or subtly altered? Attempting to provide answers to these slippery issues, the book covers how digital images are created, processed and stored before moving on to set out the latest techniques for forensically examining images, and finally addressing practical issues such as courtroom admissibility. In an environment where even novice users can alter digital media, this authoritative publication will do much so stabilize public trust in these real, yet vastly flexible, images of the world around us.

This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics.

This volume presents the peer-reviewed proceedings of the international conference Imaging, Vision and Learning Based on Optimization and PDEs (IVLOPDE), held in Bergen, Norway, in August/September 2016. The contributions cover state-of-the-art research on mathematical techniques for image processing, computer vision and machine learning based on optimization and partial differential equations (PDEs). It has become an established paradigm to formulate problems within image processing and computer vision as PDEs, variational problems or finite dimensional optimization problems. This compact yet expressive framework makes it possible to incorporate a range of desired properties of the solutions and to design algorithms based on well-founded mathematical theory. A growing body of research has also approached more general problems within data analysis and machine learning from the same perspective, and demonstrated the advantages over earlier, more established algorithms. This volume will appeal to all mathematicians and computer scientists interested in novel techniques and analytical results for optimization, variational models and PDEs, together with experimental results on applications ranging from early image formation to high-level image and data analysis.

This book covers the key advances in computerized facial beauty analysis, with an emphasis on data-driven research and the results of quantitative experiments. It takes a big step toward practical facial beauty analysis, proposes more reliable and stable facial features for beauty analysis and designs new models, methods, algorithms and schemes while implementing a facial beauty analysis and beautification system. This book also tests some previous putative rules and models for facial beauty analysis by using computationally efficient mathematical models and algorithms, especially large scale database-based and repeatable experiments.The first section of this book provides an overview of facial beauty analysis. The base of facial beauty analysis, i.e., facial beauty features, is presented in part two. Part three describes hypotheses on facial beauty, while part four defines data-driven facial beauty analysis models. This book concludes with the authors explaining how to implement their new facial beauty analysis system.This book is designed for researchers, professionals and post graduate students working in the field of facial beauty analysis, computer vision, human-machine interface, pattern recognition and biometrics. Those involved in interdisciplinary fields with also find the contents useful. The ideas, means and conclusions for beauty analysis are valuable for researchers and the system design and implementation can be used as models for practitioners and engineers.

This book brings the reader up-to-date on all aspects concerning ECCM at the antenna level. It is a reference tool for professionals seeking quick answers to on-the-job problems. This text delivers an accurate description of working principles, processing schemes and performance evaluation techniques. In addition, it provides engineering details on the newest digital techiques for sidelobe jamming cancellation and digital beamforming (DFB).