This book is a result of a workshop, the 8th of the successful TopoInVis workshop series, held in 2019 in Nykoeping, Sweden. The workshop regularly gathers some of the world's leading experts in this field. Thereby, it provides a forum for discussions on the latest advances in the field with a focus on finding practical solutions to open problems in topological data analysis for visualization. The contributions provide introductory and novel research articles including new concepts for the analysis of multivariate and time-dependent data, robust computational approaches for the extraction and approximations of topological structures with theoretical guarantees, and applications of topological scalar and vector field analysis for visualization. The applications span a wide range of scientific areas comprising climate science, material sciences, fluid dynamics, and astronomy. In addition, community efforts with respect to joint software development are reported and discussed.

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 technologies employed in airborne optical imaging seekers.

Biomedical signals provide unprecedented insight into abnormal or anomalous neurological conditions. The computer-aided diagnosis (CAD) system plays a key role in detecting neurological abnormalities and improving diagnosis and treatment consistency in medicine. This book covers different aspects of biomedical signals-based systems used in the automatic detection/identification of neurological disorders. Several biomedical signals are introduced and analyzed, including electroencephalogram (EEG), electrocardiogram (ECG), heart rate (HR), magnetoencephalogram (MEG), and electromyogram (EMG). It explains the role of the CAD system in processing biomedical signals and the application to neurological disorder diagnosis. The book provides the basics of biomedical signal processing, optimization methods, and machine learning/deep learning techniques used in designing CAD systems for neurological disorders.

The book presents selected methods for accelerating image retrieval and classification in large collections of images using what are referred to as 'hand-crafted features.' It introduces readers to novel rapid image description methods based on local and global features, as well as several techniques for comparing images. Developing content-based image comparison, retrieval and classification methods that simulate human visual perception is an arduous and complex process. The book's main focus is on the application of these methods in a relational database context. The methods presented are suitable for both general-type and medical images. Offering a valuable textbook for upper-level undergraduate or graduate-level courses on computer science or engineering, as well as a guide for computer vision researchers, the book focuses on techniques that work under real-world large-dataset conditions.

This textbook is designed for postgraduate studies in the field of 3D Computer Vision. It also provides a useful reference for industrial practitioners; for example, in the areas of 3D data capture, computer-aided geometric modelling and industrial quality assurance. This second edition is a significant upgrade of existing topics with novel findings. Additionally, it has new material covering consumer-grade RGB-D cameras, 3D morphable models, deep learning on 3D datasets, as well as new applications in the 3D digitization of cultural heritage and the 3D phenotyping of crops. Overall, the book covers three main areas: 3D imaging, including passive 3D imaging, active triangulation 3D imaging, active time-of-flight 3D imaging, consumer RGB-D cameras, and 3D data representation and visualisation; 3D shape analysis, including local descriptors, registration, matching, 3D morphable models, and deep learning on 3D datasets; and 3D applications, including 3D face recognition, cultural heritage and 3D phenotyping of plants. 3D computer vision is a rapidly advancing area in computer science. There are many real-world applications that demand high-performance 3D imaging and analysis and, as a result, many new techniques and commercial products have been developed. However, many challenges remain on how to analyse the captured data in a way that is sufficiently fast, robust and accurate for the application. Such challenges include metrology, semantic segmentation, classification and recognition. Thus, 3D imaging, analysis and their applications remain a highly-active research field that will continue to attract intensive attention from the research community with the ultimate goal of fully automating the 3D data capture, analysis and inference pipeline.

Congruences are ubiquitous in computer science, engineering, mathematics, and related areas. Developing techniques for finding (the number of) solutions of congruences is an important problem. But there are many scenarios in which we are interested in only a subset of the solutions; in other words, there are some restrictions. What do we know about these restricted congruences, their solutions, and applications? This book introduces the tools that are needed when working on restricted congruences and then systematically studies a variety of restricted congruences. Restricted Congruences in Computing defines several types of restricted congruence, obtains explicit formulae for the number of their solutions using a wide range of tools and techniques, and discusses their applications in cryptography, information security, information theory, coding theory, string theory, quantum field theory, parallel computing, artificial intelligence, computational biology, discrete mathematics, number theory, and more. This is the first book devoted to restricted congruences and their applications. It will be of interest to graduate students and researchers across computer science, electrical engineering, and mathematics.

Machine vision systems offer great potential in a large number of areas of manufacturing industry and are used principally for Automated Visual Inspection and Robot Vision. This publication presents the state of the art in image processing. It discusses techniques which have been developed for designing machines for use in industrial inspection and robot control, putting the emphasis on software and algorithms. A comprehensive set of image processing subroutines, which together form the basic vocabulary for the versatile image processing language IIPL, is presented. This language has proved to be extremely effective, working as a design tool, in solving numerous practical inspection problems. The merging of this language with Prolog provides an even more powerful facility which retains the benefits of human and machine intelligence. The authors bring together the practical experience and the picture material from a leading industrial research laboratory and the mathematical foundations necessary to understand and apply concepts in image processing. Interactive Image Processing is a self-contained reference book that can also be used in graduate level courses in electrical engineering, computer science and physics.

Since computer vision¿s humble beginnings in the 1960s, a substantial amount of related research has been biologically inspired, using the human eye and visual perception as a model from which to work. Panoramic vision is a subset of computer vision that focuses on the creation and analysis of images with unusually wide fields of view that extend far beyond a single camera snapshot. It has broad implications for commercial and web-based multimedia applications, such as games, virtual reality, surveillance, and teleconferencing. This volume collects the works of researchers who have worked extensively in the field and covers a wide array of topics in this promising new area. In addition to providing a concise historical perspective on panoramic imaging, the book features representative sections on the design of panoramic image capturing systems, the theory involved in the imaging process, software techniques for creating panoramic images, and applications that use panoramic images. It will help readers to understand the more technical aspects of panoramic vision, such as sensor design and imaging techniques. Interest in panoramic vision will only increase over time, as faster computers and larger bandwidth become available and as specialized cameras become cheaper through economies of scale. Researchers and professionals in computer vision, imaging and robotics (machine vision) will find the book an authoritative and indispensable resource for panoramic vision concepts and methods.

This textbook deals with the basics and methods of photogrammetry and laser scanning which are used to determine the form and location of objects, with measurements provided by sensors placed in air planes as well as on terrestrial platforms. Many examples and exercises with solutions are included. Photogrammetry, Laserscanning.

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.

This Special Edited Volume is a unique approach towards Computational solution for the upcoming field of study called Vision Science. From a scientific firmament Optics, Ophthalmology, and Optical Science has surpassed an Odyssey of optimizing configurations of Optical systems, Surveillance Cameras and other Nano optical devices with the metaphor of Nano Science and Technology. Still these systems are falling short of its computational aspect to achieve the pinnacle of human vision system. In this edited volume much attention has been given to address the coupling issues Computational Science and Vision Studies. It is a comprehensive collection of research works addressing various related areas of Vision Science like Visual Perception and Visual system, Cognitive Psychology, Neuroscience, Psychophysics and Ophthalmology, linguistic relativity, color vision etc. This issue carries some latest developments in the form of research articles and presentations. The volume is rich of contents with technical tools for convenient experimentation in Vision Science. There are 18 research papers having significance in an array of application areas. The volume claims to be an effective compendium of computing developments like Frequent Pattern Mining, Genetic Algorithm, Gabor Filter, Support Vector Machine, Region Based Mask Filter, 4D stereo camera systems, Principal Component Analysis etc. The detailed analysis of the papers can immensely benefit to the researchers of this domain. It can be an Endeavour in the pursuit of adding value in the existing stock of knowledge in Vision Science.

• Readers will gain an understanding of the optical technology, material science, and semiconductor device technology behind image acquisition devices • Research on image information is stable but slowly growing and several universities globally teach related courses for which this is valuable supplementary reading • This book offers a unique focus on the devices used in image sensors and displays

For junior- to graduate-level courses in computer graphics. Assuming no background in computer graphics, this junior- to graduate-level textbook presents basic principles for the design, use, and understanding of computer graphics systems and applications. The authors, authorities in their field, offer an integrated approach to two-dimensional and three-dimensional graphics topics. A comprehensive explanation of the popular OpenGL programming package, along with C++ programming examples illustrates applications of the various functions in the OpenGL basic library and the related GLU and GLUT packages.

Scalar diffraction from a circular aperture is a ubiquitous problem that arises in a variety of disciplines, such as optics (lenses), acoustics (speakers), electromagnetics (dish antennas), and ultrasonics (piston transducers). The problem endures despite centuries of research because each new generation of researchers rediscovers it and adds some novel insight or new result to the existing literature. Scalar Diffraction from a Circular Aperture promises a few new results and several novel insights, particularly with regard to spatial averaging. Although the text emphasizes ultrasonic diffraction, the results and insights developed are general and may be applied to the many practical problems involving scalar diffraction from a circular aperture. Included are novel insights on mirror-image diffraction, autoconvolution diffraction, and coherent and incoherent averaging. Examples from ultrasonic imaging, a coherent imaging modality, are used to develop a fairly general theory that connects over a century of research on scalar diffraction from a circular aperture. The material is based on a synthesis of mathematics, physical optics, linear systems theory, and scalar diffraction theory. Thus, engineers, scientists, mathematicians, and students working in optics, acoustics, antenna design, biomedical engineering, non-destructive testing, and astronomy will find Scalar Diffraction from a Circular Aperture interesting, provocative, and useful.

To enhance the overall viewing experience (for cinema, TV, games, AR/VR) the media industry is continuously striving to improve image quality. Currently the emphasis is on High Dynamic Range (HDR) and Wide Colour Gamut (WCG) technologies, which yield images with greater contrast and more vivid colours. The uptake of these technologies, however, has been hampered by the significant challenge of understanding the science behind visual perception. Vision Models for High Dynamic Range and Wide Colour Gamut Imaging provides university researchers and graduate students in computer science, computer engineering, vision science, as well as industry R&D engineers, an insight into the science and methods for HDR and WCG. It presents the underlying principles and latest practical methods in a detailed and accessible way, highlighting how the use of vision models is a key element of all state-of-the-art methods for these emerging technologies.

The text covers recent advances in artificial intelligence, smart computing, and their applications in augmenting medical and health care systems. It will serve as an ideal reference text for graduate students and academic researchers in diverse engineering fields including electrical, electronics and communication, computer, and biomedical. The book- Presents architecture, characteristics, and applications of artificial intelligence and smart computing in health care systems Highlight privacy issues faced in health care and health informatics using artificial intelligence and smart computing technologies. Discusses nature-inspired computing algorithms for the brain-computer interface. Covers graph neural network application in the medical domain. Provides insights into the state-of-the-art Artificial Intelligence and Smart Computing enabling and emerging technologies. This book text discusses recent advances and applications of artificial intelligence and smart technologies in the field of healthcare. It highlights privacy issues faced in health care and health informatics using artificial intelligence and smart computing technologies. It covers nature-inspired computing algorithms such as genetic algorithms, particle swarm optimization algorithms, and common scrambling algorithms to study brain-computer interfaces. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and biomedical engineering.

The book augurs to be a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives orient to offer an overview to the elementary concepts and practices appropriate to DIP as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to: Applications and tools for image processing, fundamentals with several implementation examples Concepts of image formation, OpenCV installation with step-by-step screen shots Concepts behind intensity, brightness and contrast, color models Ways by which noises are created in an image and the possible remedial measures Edge detection, Image segmentation, classification, regression, Classification algorithms Importance of frequency domain in image processing field Relevant code snippets and the MATLAB codes, several interesting set of simple programs in OpenCV and Python to aid learning and for complete understanding The video lectures for specific topics through YouTube by the authors enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quiz, review questions etc., fully prepares the readers for further study. Graduate Students, Post Graduate students, Researchers, and anyone in general interested in Image Processing, Computer Vision, Machine Learning domains etc. can find this book an excellent starting point for information and as an able ally.

1. Covers latest concepts in image processing and intelligent computing systems. 2. Presents the applications of image processing based intelligent systems. 3. Covers latest research topics in the field. 4. Written in a comprehensive and simple manner. 5. The text is accompanied by tables and illustrative figures for better understanding of the topic.

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.

Traditionally, scientific fields have defined boundaries, and scientists work on research problems within those boundaries. However, from time to time those boundaries get shifted or blurred to evolve new fields. For instance, the original goal of computer vision was to understand a single image of a scene, by identifying objects, their structure, and spatial arrangements. This has been referred to as image understanding. Recently, computer vision has gradually been making the transition away from understanding single images to analyzing image sequences, or video understanding. Video understanding deals with understanding of video sequences, e. g., recognition of gestures, activities, facial expressions, etc. The main shift in the classic paradigm has been from the recognition of static objects in the scene to motion-based recognition of actions and events. Video understanding has overlapping research problems with other fields, therefore blurring the fixed boundaries. Computer graphics, image processing, and video databases have obvious overlap with computer vision. The main goal of computer graphics is to gener ate and animate realistic looking images, and videos. Researchers in computer graphics are increasingly employing techniques from computer vision to gen erate the synthetic imagery. A good example of this is image-based rendering and modeling techniques, in which geometry, appearance, and lighting is de rived from real images using computer vision techniques. Here the shift is from synthesis to analysis followed by synthesis."

This hands-on textbook/reference presents an introduction to the fundamental aspects of modelling and simulation, both for those wishing to learn about this methodology and also for those who have a need to apply it in their work. The text is supported by illustrative examples, drawn from projects formulated within the domains of discrete-event dynamic systems (DEDS) and continuous-time dynamic systems (CTDS). This updated new edition has been enhanced with new illustrative case studies, and additional examples demonstrating some new features and the effectiveness of the ABCmod conceptual modelling framework. Changes that facilitate the development of simulation models with ABSmod/J are illustrated. New material includes a presentation of the experimentation strategy called "design of experiments" and three new chapters that explore the optimization-simulation interface. Topics and features: presents a goal-based and project-oriented perspective of modelling and simulation; describes the ABCmod framework, an activity-based conceptual modelling framework for DEDS; examines the simulation-optimization interface in both the CTDS and DEDS domains; provides numerous illustrative examples, case studies and useful algorithms, as well as exercises and projects at the end of most chapters; includes appendices on probability and statistics, the GPSS programming environment, and relevant MATLAB features; provides supplementary software and teaching support material at an associated website, including lecture slides and a methodology for organizing student projects. Serving as an essential guide to the foundations of modelling and simulation, this practical primer is ideal for senior undergraduate and junior graduate-level students. Also suitable for self-study, the book will be of great benefit to professionals seeking insight into the vast potential of this rapidly evolving problem-solving paradigm.

Neutrosophic Set in Medical Image Analysis gives an understanding of the concepts of NS, along with knowledge on how to gather, interpret, analyze and handle medical images using NS methods. It presents the latest cutting-edge research that gives insight into neutrosophic set's novel techniques, strategies and challenges, showing how it can be used in biomedical diagnoses systems. The neutrosophic set (NS), which is a generalization of fuzzy set, offers the prospect of overcoming the restrictions of fuzzy-based approaches to medical image analysis.

This book illustrates the application of fractional calculus in crowd dynamics via modeling and control groups of pedestrians. Decision-making processes, conservation laws of mass/momentum, and micro-macro models are employed to describe system dynamics while cooperative movements in micro scale, and fractional diffusion in macro scale are studied to control the group of pedestrians. Obtained work is included in the Intelligent Evacuation Systems that is used for modeling and to control crowds of pedestrians. With practical issues considered, this book is of interests to mathematicians, physicists, and engineers.

This book provides a unique view of human activity recognition, especially fine-grained human activity structure learning, human-interaction recognition, RGB-D data based action recognition, temporal decomposition, and causality learning in unconstrained human activity videos. The techniques discussed give readers tools that provide a significant improvement over existing methodologies of video content understanding by taking advantage of activity recognition. It links multiple popular research fields in computer vision, machine learning, human-centered computing, human-computer interaction, image classification, and pattern recognition. In addition, the book includes several key chapters covering multiple emerging topics in the field. Contributed by top experts and practitioners, the chapters present key topics from different angles and blend both methodology and application, composing a solid overview of the human activity recognition techniques.

Proceedings of the International Conference on Human-centric Computing and Embedded and Multimedia Computing (HumanCom & EMC 2011) will cover topics of HumanCom and EMC, the current hot topics satisfying the world-wide ever-changing needs. Human-centric computing is to create novel solutions so that the humans are always connected, portable, and available. As with pervasive-computing, human-centric computing requires a variety of devices; however, such devices exist simply to obtain inputs from the human and are embedded in objects that humans interact with on a daily basis. Moreover, during the past couple of decades, Information Science technologies influenced and changed every aspect of our lives and our cultures. Without various Information Science technology-based applications, it would be difficult to keep information stored securely, to process information efficiently, and to communicate conveniently. Embedded computing ranges from portable devices such as digital watches and MP3 players, to large stationary installations like traffic lights, factory controllers, or the systems controlling nuclear power plants. Complexity varies from low, with a single microcontroller chip, to very high with multiple units, peripherals and networks mounted inside a large chassis or enclosure. Multimedia computing covers multimedia I/O devices, OS, storage systems, streaming media middleware, continuous media representations, media coding, media processing, etc., and also includes multimedia communications; real-time protocols, end-to-end streaming media, resource allocation, multicast protocols, and multimedia applications; databases, distributed collaboration, video conferencing, 3D virtual environments.