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Books > Computing & IT > Applications of computing > Image processing
This book carries forward recent work on visual patterns and structures in digital images and introduces a near set-based a topology of digital images. Visual patterns arise naturally in digital images viewed as sets of non-abstract points endowed with some form of proximity (nearness) relation. Proximity relations make it possible to construct uniform topologies on the sets of points that constitute a digital image. In keeping with an interest in gaining an understanding of digital images themselves as a rich source of patterns, this book introduces the basics of digital images from a computer vision perspective. In parallel with a computer vision perspective on digital images, this book also introduces the basics of proximity spaces. Not only the traditional view of spatial proximity relations but also the more recent descriptive proximity relations are considered. The beauty of the descriptive proximity approach is that it is possible to discover visual set patterns among sets that are non-overlapping and non-adjacent spatially. By combining the spatial proximity and descriptive proximity approaches, the search for salient visual patterns in digital images is enriched, deepened and broadened. A generous provision of Matlab and Mathematica scripts are used in this book to lay bare the fabric and essential features of digital images for those who are interested in finding visual patterns in images. The combination of computer vision techniques and topological methods lead to a deep understanding of images.
In this book, three main notions will be used in the editors search of improvements in various areas of computer graphics: Artificial Intelligence, Viewpoint Complexity and Human Intelligence. Several Artificial Intelligence techniques are used in presented intelligent scene modelers, mainly declarative ones. Among them, the mostly used techniques are Expert systems, Constraint Satisfaction Problem resolution and Machine-learning. The notion of viewpoint complexity, that is complexity of a scene seen from a given viewpoint, will be used in improvement proposals for a lot of computer graphics problems like scene understanding, virtual world exploration, image-based modeling and rendering, ray tracing and radiosity. Very often, viewpoint complexity is used in conjunction with Artificial Intelligence techniques like Heuristic search and Problem resolution. The notions of artificial Intelligence and Viewpoint Complexity may help to automatically resolve a big number of computer graphics problems. However, there are special situations where is required to find a particular solution for each situation. In such a case, human intelligence has to replace, or to be combined with, artificial intelligence. Such cases, and proposed solutions are also presented in this book.
Advancements in digital sensor technology, digital image analysis techniques, as well as computer software and hardware have brought together the fields of computer vision and photogrammetry, which are now converging towards sharing, to a great extent, objectives and algorithms. The potential for mutual benefits by the close collaboration and interaction of these two disciplines is great, as photogrammetric know-how can be aided by the most recent image analysis developments in computer vision, while modern quantitative photogrammetric approaches can support computer vision activities. Devising methodologies for automating the extraction of man-made objects (e.g. buildings, roads) from digital aerial or satellite imagery is an application where this cooperation and mutual support is already reaping benefits. The valuable spatial information collected using these interdisciplinary techniques is of improved qualitative and quantitative accuracy. This book offers a comprehensive selection of high-quality and in-depth contributions from world-wide leading research institutions, treating theoretical as well as implementational issues, and representing the state-of-the-art on this subject among the photogrammetric and computer vision communities.
Soft Computing Approach to Pattern Classification and Object Recognition establishes an innovative, unified approach to supervised pattern classification and model-based occluded object recognition. The book also surveys various soft computing tools, fuzzy relational calculus (FRC), genetic algorithm (GA) and multilayer perceptron (MLP) to provide a strong foundation for the reader. The supervised approach to pattern classification and model-based approach to occluded object recognition are treated in one framework , one based on either a conventional interpretation or a new interpretation of multidimensional fuzzy implication (MFI) and a novel notion of fuzzy pattern vector (FPV). By combining practice and theory, a completely independent design methodology was developed in conjunction with this supervised approach on a unified framework, and then tested thoroughly against both synthetic and real-life data. In the field of soft computing, such an application-oriented design study is unique in nature. The monograph essentially mimics the cognitive process of human decision making, and carries a message of perceptual integrity in representational diversity. Soft Computing Approach to Pattern Classification and Object Recognition is intended for researchers in the area of pattern classification and computer vision. Other academics and practitioners will also find the book valuable.
Due to the rapid increase in readily available computing power, a corre sponding increase in the complexity of problems being tackled has occurred in the field of systems as a whole. A plethora of new methods which can be used on the problems has also arisen with a constant desire to deal with more and more difficult applications. Unfortunately by increasing the ac curacy in models employed along with the use of appropriate algorithms with related features, the resultant necessary computations can often be of very high dimension. This brings with it a whole new breed of problem which has come to be known as "The Curse of Dimensionality" . The expression "Curse of Dimensionality" can be in fact traced back to Richard Bellman in the 1960's. However, it is only in the last few years that it has taken on a widespread practical significance although the term di mensionality does not have a unique precise meaning and is being used in a slightly different way in the context of algorithmic and stochastic complex ity theory or in every day engineering. In principle the dimensionality of a problem depends on three factors: on the engineering system (subject), on the concrete task to be solved and on the available resources. A system is of high dimension if it contains a lot of elements/variables and/or the rela tionship/connection between the elements/variables is complicated."
Spectacular advances during the last decade have altered the
related disciplines of computing and telecommunications beyond all
recognition. The developments in the"enabling technologies,"which
have made these advances possible, have been less obvious to the
casual observer. The subject of this book is one of these
technologies--the coding of still images and picture sequences
(video).
Video monitoring has become a vital aspect within the global society as it helps prevent crime, promote safety, and track daily activities such as traffic. As technology in the area continues to improve, it is necessary to evaluate how video is being processed to improve the quality of images. Applied Video Processing in Surveillance and Monitoring Systems investigates emergent techniques in video and image processing by evaluating such topics as segmentation, noise elimination, encryption, and classification. Featuring real-time applications, empirical research, and vital frameworks within the field, this publication is a critical reference source for researchers, professionals, engineers, academicians, advanced-level students, and technology developers.
Expand your creative ability by mastering the software tools. "DVD Authoring with Adobe Encore DVD" covers the toolset in a manner that demonstrates real-world application. The downloadable resources with source material walks you through the process. You will learn how to avoid common pitfalls and learn about the entire DVD authoring workflow.
The rapid advancements in image communication technologies are documented in the book series, Advances in Image Communication. Each publication provides an in-depth exploration of an intrinsic element of the multi-disciplinary field and together they form a comprehensive overview of the whole. This volume, the fifth in the series, examines the definition, study and use of the wavelet transform in communications for two-dimensional (2-D) digital signals. The transform is used for signal reorganization before compression and the trade-off between these two steps and the whole compression process is discussed. The five chapters specifically present the theory of wavelets applied to images, then applications of compression of still images and sequences. Chapter 1 introduces biorthogonal bases of compactly supported wavelets: this generalization of orthonormal wavelet theory allows the use of linear phase filters. A non rectangular wavelet representation of 2-D signals is developed in the second chapter: the properties usually used with wavelets, phase, linearity, and regularity are discussed. Chapter 3 is composed of three parts: a description of commonly used biorthogonal wavelets; a presentation of vector quantization algorithms; a consideration of lattice vector quantization followed by a discussion of the bit allocation procedure (with experimental results given). The fourth chapter deals with a region-based discrete wavelet transform for image coding. Chapter 5 investigates the transmission of image sequences: wavelet transforms and motion estimation are detailed in a multiconstraint approach of image sequence coding.
Image segmentation consists of dividing an image domain into disjoint regions according to a characterization of the image within or in-between the regions. Therefore, segmenting an image is to divide its domain into relevant components. The efficient solution of the key problems in image segmentation promises to enable a rich array of useful applications. The current major application areas include robotics, medical image analysis, remote sensing, scene understanding, and image database retrieval. The subject of this book is image segmentation by variational methods with a focus on formulations which use closed regular plane curves to define the segmentation regions and on a level set implementation of the corresponding active curve evolution algorithms. Each method is developed from an objective functional which embeds constraints on both the image domain partition of the segmentation and the image data within or in-between the partition regions. The necessary conditions to optimize the objective functional are then derived and solved numerically. The book covers, within the active curve and level set formalism, the basic two-region segmentation methods, multiregion extensions, region merging, image modeling, and motion based segmentation. To treat various important classes of images, modeling investigates several parametric distributions such as the Gaussian, Gamma, Weibull, and Wishart. It also investigates non-parametric models. In motion segmentation, both optical flow and the movement of real three-dimensional objects are studied.
Security and privacy are paramount concerns in information processing systems, which are vital to business, government and military operations and, indeed, society itself. Meanwhile, the expansion of the Internet and its convergence with telecommunication networks are providing incredible connectivity, myriad applications and, of course, new threats. Data and Applications Security XVII: Status and Prospects
describes original research results, practical experiences and
innovative ideas, all focused on maintaining security and privacy
in information processing systems and applications that pervade
cyberspace. The areas of coverage include: This book is the seventeenth volume in the series produced by the International Federation for Information Processing (IFIP) Working Group 11.3 on Data and Applications Security. It presents a selection of twenty-six updated and edited papers from the Seventeenth Annual IFIP TC11 / WG11.3 Working Conference on Data and Applications Security held at Estes Park, Colorado, USA in August 2003, together with a report on the conference keynote speech and a summary of the conference panel. The contents demonstrate the richness and vitality of the discipline, and other directions for future research in data and applications security. Data and Applications Security XVII: Status and Prospects is an invaluable resource for information assurance researchers, faculty members and graduate students, as well as for individuals engaged in research and development in the information technology sector.
The Distinguished Dissertation Series is published on behalf of the Conference of Professors and Heads of Computing and the British Computer Society, who annually select the best British PhD dissertations in computer science for publication. The dissertations are selected on behalf of the CPHC by a panel of eight academics. Each dissertation chosen makes a noteworthy contribution to the subject and reaches a high standard of exposition, placing all results clearly in the context of computer science as a whole. In this way computer scientists with significantly different interests are able to grasp the essentials - or even find a means of entry - to an unfamiliar research topic. This book investigates how information contained in multiple, overlapping images of a scene may be combined to produce images of superior quality. This offers possibilities such as noise reduction, extended field of view, blur removal, increased spatial resolution and improved dynamic range. Potential applications cover fields as diverse as forensic video restoration, remote sensing, video compression and digital video editing. The book covers two aspects that have attracted particular attention in recent years: image mosaicing, whereby multiple images are aligned to produce a large composite; and super-resolution, which permits restoration at an increased resolution of poor quality video sequences by modelling and removing imaging degradations including noise, blur and spacial-sampling. It contains a comprehensive coverage and analysis of existing techniques, and describes in detail novel, powerful and automatic algorithms (based on a robust, statistical framework) for applying mosaicing and super-resolution. The algorithms may be implemented directly from the descriptions given here. A particular feature of the techniques is that it is not necessary to know the camera parameters (such as position and focal length) in order to apply them. Throughout the book, examples are given on real image sequences, covering a variety of applications including: the separation of latent marks in forensic images; the automatic creation of 360 panoramic mosaics; and super-resolution restoration of various scenes, text, and faces in lw-quality video.
Image communication technologies have advanced rapidly in recent years and the book series, Advances in Image Communication is dedicated to documenting these developments. Third in the series, this publication contributes as effectively as its forerunners to the multidisciplinary overview afforded by the series as a whole. At the same time, it stands alone as a comprehensive synopsis of its own particular area of interest. The book specifically explores two complementary topics, namely: the coding algorithms made to compress the data rate of digital moving-picture sequences (video-telephony, television TV] and high-definition television HDTV]) and the transmission on Asynchronous Transfer Mode ATM] networks (packet-switching transmission media). It provides an in-depth view of the current state-of-the-art and endeavors to stimulate increasing research efforts for the future.
Signal processing applications have burgeoned in the past decade.
During the same time, signal processing techniques have matured
rapidly and now include tools from many areas of mathematics,
computer science, physics, and engineering. This trend will
continue as many new signal processing applications are opening up
in consumer products and communications systems.
Ultra-High Field Neuro MRI is a comprehensive reference and educational resource on the current state of neuroimaging at ultra-high field (UHF), with an emphasis on 7T. Sections cover the MR physics aspects of UHF, including the technical challenges and practical solutions that have enabled the rapid growth of 7T MRI. Individual chapters are dedicated to the different techniques that most strongly benefit from UHF, as well as chapters with a focus on different application areas in anatomical, functional and metabolic imaging. Finally, several chapters highlight the neurological and psychiatric applications for which 7T has shown benefits. The book is aimed at scientists who develop MR technologies and support clinical and neuroscience research, as well as users who want to benefit from UHF neuro MR techniques in their work. It also provides a comprehensive introduction to the field.
This book provides detailed practical guidelines on how to develop an efficient pathological brain detection system, reflecting the latest advances in the computer-aided diagnosis of structural magnetic resonance brain images. Matlab codes are provided for most of the functions described. In addition, the book equips readers to easily develop the pathological brain detection system further on their own and apply the technologies to other research fields, such as Alzheimer's detection, multiple sclerosis detection, etc.
The design and construction of three-dimensional 3-D] object recognition systems has long occupied the attention of many computer vision researchers. The variety of systems that have been developed for this task is evidence both of its strong appeal to researchers and its applicability to modern manufacturing, industrial, military, and consumer environments. 3-D object recognition is of interest to scientists and engineers in several different disciplines due to both a desire to endow computers with robust visual capabilities, and the wide applications which would benefit from mature and robust vision systems. However, 3-D object recognition is a very complex problem, and few systems have been developed for actual production use; most existing systems have been developed for experimental use by researchers only. This edited collection of papers summarizes the state of the art in 3-D object recognition using examples of existing 3-D systems developed by leading researchers in the field. While most chapters describe a complete object recognition system, chapters on biological vision, sensing, and early processing are also included. The volume will serve as a valuable reference source for readers who are involved in implementing model-based object recognition systems, stimulating the cross-fertilisation of ideas in the various domains.
The area of adaptive systems, which encompasses recursive identification, adaptive control, filtering, and signal processing, has been one of the most active areas of the past decade. Since adaptive controllers are fundamentally nonlinear controllers which are applied to nominally linear, possibly stochastic and time-varying systems, their theoretical analysis is usually very difficult. Nevertheless, over the past decade much fundamental progress has been made on some key questions concerning their stability, convergence, performance, and robustness. Moreover, adaptive controllers have been successfully employed in numerous practical applications, and have even entered the marketplace.
With a preface by Ton Kalker. Informed Watermarking is an essential tool for both academic and professional researchers working in the areas of multimedia security, information embedding, and communication. Theory and practice are linked, particularly in the area of multi-user communication. From the Preface: Watermarking has become a more mature discipline with proper foundation in both signal processing and information theory. We can truly say that we are in the era of "second generation" watermarking. This book is first in addressing watermarking problems in terms of second-generation insights. It provides a complete overview of the most important results on capacity and security. The Costa scheme, and in particular a simpler version of it, the Scalar Costa scheme, is studied in great detail. An important result of this book is that it is possible to approach the Shannon limit within a few decibels in a practical system. These results are verified on real-world data, not only the classical category of images, but also on chemical structure sets. Inspired by the work of Moulin and O'Sullivan, this book also addresses security aspects by studying AGWN attacks in terms of game theory. "The authors of Informed Watermarking give a well-written exposA(c) of how watermarking came of age, where we are now, and what to expect in the future. It is my expectation that this book will be a standard reference on second-generation watermarking for the years to come." Ton Kalker, Technische Universiteit Eindhoven
Multimedia Signals and Systems is an essential text for
professional and academic researchers and students in the field of
multimedia.
Video Object Extraction and Representation: Theory and Applications is an essential reference for electrical engineers working in video; computer scientists researching or building multimedia databases; video system designers; students of video processing; video technicians; and designers working in the graphic arts. In the coming years, the explosion of computer technology will enable a new form of digital media. Along with broadband Internet access and MPEG standards, this new media requires a computational infrastructure to allow users to grab and manipulate content. The book reviews relevant technologies and standards for content-based processing and their interrelations. Within this overview, the book focuses upon two problems at the heart of the algorithmic/computational infrastructure: video object extraction, or how to automatically package raw visual information by content; and video object representation, or how to automatically index and catalogue extracted content for browsing and retrieval. The book analyzes the designs of two novel, working systems for content-based extraction and representation in the support of MPEG-4 and MPEG-7 video standards, respectively. Features of the book include: Overview of MPEG standards; A working system for automatic video object segmentation; A working system for video object query by shape; Novel technology for a wide range of recognition problems; Overview of neural network and vision technologies Video Object Extraction and Representation: Theory and Applications will be of interest to research scientists and practitioners working in fields related to the topic. It may also be used as an advanced-level graduate text.
The book describes a system for visual surveillance using intelligent cameras. The camera uses robust techniques for detecting and tracking moving objects. The real time capture of the objects is then stored in the database. The tracking data stored in the database is analysed to study the camera view, detect and track objects, and study object behavior. These set of models provide a robust framework for coordinating the tracking of objects between overlapping and non-overlapping cameras, and recording the activity of objects detected by the system.
Basics of Game Design is for anyone wanting to become a professional game designer. Focusing on creating the game mechanics for data-driven games, it covers role-playing, real-time strategy, first-person shooter, simulation, and other games. Written by a 25-year veteran of the game industry, the guide offers detailed explanations of how to design the data sets used to resolve game play for moving, combat, solving puzzles, interacting with NPCs, managing inventory, and much more. Advice on developing stories for games, building maps and levels, and designing the graphical user interface is also included.
Bayesian Approach to Image Interpretation will interest anyone working in image interpretation. It is complete in itself and includes background material. This makes it useful for a novice as well as for an expert. It reviews some of the existing probabilistic methods for image interpretation and presents some new results. Additionally, there is extensive bibliography covering references in varied areas. For a researcher in this field, the material on synergistic integration of segmentation and interpretation modules and the Bayesian approach to image interpretation will be beneficial. For a practicing engineer, the procedure for generating knowledge base, selecting initial temperature for the simulated annealing algorithm, and some implementation issues will be valuable. New ideas introduced in the book include: New approach to image interpretation using synergism between the segmentation and the interpretation modules. A new segmentation algorithm based on multiresolution analysis. Novel use of the Bayesian networks (causal networks) for image interpretation. Emphasis on making the interpretation approach less dependent on the knowledge base and hence more reliable by modeling the knowledge base in a probabilistic framework. Useful in both the academic and industrial research worlds, Bayesian Approach to Image Interpretation may also be used as a textbook for a semester course in computer vision or pattern recognition. |
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