Background modeling and foreground detection are important steps in video processing used to detect robustly moving objects in challenging environments. This requires effective methods for dealing with dynamic backgrounds and illumination changes as well as algorithms that must meet real-time and low memory requirements. Incorporating both established and new ideas, Background Modeling and Foreground Detection for Video Surveillance provides a complete overview of the concepts, algorithms, and applications related to background modeling and foreground detection. Leaders in the field address a wide range of challenges, including camera jitter and background subtraction. The book presents the top methods and algorithms for detecting moving objects in video surveillance. It covers statistical models, clustering models, neural networks, and fuzzy models. It also addresses sensors, hardware, and implementation issues and discusses the resources and datasets required for evaluating and comparing background subtraction algorithms. The datasets and codes used in the text, along with links to software demonstrations, are available on the book's website. A one-stop resource on up-to-date models, algorithms, implementations, and benchmarking techniques, this book helps researchers and industry developers understand how to apply background models and foreground detection methods to video surveillance and related areas, such as optical motion capture, multimedia applications, teleconferencing, video editing, and human-computer interfaces. It can also be used in graduate courses on computer vision, image processing, real-time architecture, machine learning, or data mining.

Broad in scope, Semantic Multimedia Analysis and Processing provides a complete reference of techniques, algorithms, and solutions for the design and the implementation of contemporary multimedia systems. Offering a balanced, global look at the latest advances in semantic indexing, retrieval, analysis, and processing of multimedia, the book features the contributions of renowned researchers from around the world. Its contents are based on four fundamental thematic pillars: 1) information and content retrieval, 2) semantic knowledge exploitation paradigms, 3) multimedia personalization, and 4) human-computer affective multimedia interaction. Its 15 chapters cover key topics such as content creation, annotation and modeling for the semantic web, multimedia content understanding, and efficiency and scalability. Fostering a deeper understanding of a popular area of research, the text: Describes state-of-the-art schemes and applications Supplies authoritative guidance on research and deployment issues Presents novel methods and applications in an informative and reproducible way Contains numerous examples, illustrations, and tables summarizing results from quantitative studies Considers ongoing trends and designates future challenges and research perspectives Includes bibliographic links for further exploration Uses both SI and US units Ideal for engineers and scientists specializing in the design of multimedia systems, software applications, and image/video analysis and processing technologies, Semantic Multimedia Analysis and Processing aids researchers, practitioners, and developers in finding innovative solutions to existing problems, opening up new avenues of research in uncharted waters.

Synthetic aperture radar provides broad-area imaging at high resolutions, which is used in applications such as environmental monitoring, earth-resource mapping, and military systems.
This book presents the tools required for the digital processing of synthetic aperture radar images. They are of three types: (a) the elements of physics, (b) mathematical models and (c) image processing methods adapted to particular applications.

This book provides a full representation of Inverse Synthetic Aperture Radar (ISAR) imagery, which is a popular and important radar signal processing tool. The book covers all possible aspects of ISAR imaging. The book offers a fair amount of signal processing techniques and radar basics before introducing the inverse problem of ISAR and the forward problem of Synthetic Aperture Radar (SAR). Important concepts of SAR such as resolution, pulse compression and image formation are given together with associated MATLAB codes.

After providing the fundamentals for ISAR imaging, the book gives the detailed imaging procedures for ISAR imaging with associated MATLAB functions and codes. To enhance the image quality in ISAR imaging, several imaging tricks and fine-tuning procedures such as zero-padding and windowing are also presented. Finally, various real applications of ISAR imagery, like imaging the antenna-platform scattering, are given in a separate chapter. For all these algorithms, MATLAB codes and figures are included. The final chapter considers advanced concepts and trends in ISAR imaging.

In the last few years, biometric techniques have proven their ability to provide secure access to shared resources in various domains. Furthermore, software agents and multi-agent systems (MAS) have shown their efficiency in resolving critical network problems. Iris Biometric Model for Secured Network Access proposes a new model, the IrisCryptoAgentSystem (ICAS), which is based on a biometric method for authentication using the iris of the eyes and an asymmetric cryptography method using "Rivest-Shamir-Adleman" (RSA) in an agent-based architecture. It focuses on the development of new methods in biometric authentication in order to provide greater efficiency in the ICAS model. It also covers the pretopological aspects in the development of the indexed hierarchy to classify DRVA iris templates. The book introduces biometric systems, cryptography, and multi-agent systems (MAS) and explains how they can be used to solve security problems in complex systems. Examining the growing interest to exploit MAS across a range of fields through the integration of various features of agents, it also explains how the intersection of biometric systems, cryptography, and MAS can apply to iris recognition for secure network access. The book presents the various conventional methods for the localization of external and internal edges of the iris of the eye based on five simulations and details the effectiveness of each. It also improves upon existing methods for the localization of the external and internal edges of the iris and for removing the intrusive effects of the eyelids.

This book is devoted to the issue of image super-resolution-obtaining high-resolution images from single or multiple low-resolution images. Although there are numerous algorithms available for image interpolation and super-resolution, there's been a need for a book that establishes a common thread between the two processes. Filling this need, Image Super-Resolution and Applications presents image interpolation as a building block in the super-resolution reconstruction process. Instead of approaching image interpolation as either a polynomial-based problem or an inverse problem, this book breaks the mold and compares and contrasts the two approaches. It presents two directions for image super-resolution: super-resolution with a priori information and blind super-resolution reconstruction of images. It also devotes chapters to the two complementary steps used to obtain high-resolution images: image registration and image fusion. Details techniques for color image interpolation and interpolation for pattern recognition Analyzes image interpolation as an inverse problem Presents image registration methodologies Considers image fusion and its application in image super resolution Includes simulation experiments along with the required MATLAB (R) code Supplying complete coverage of image-super resolution and its applications, the book illustrates applications for image interpolation and super-resolution in medical and satellite image processing. It uses MATLAB (R) programs to present various techniques, including polynomial image interpolation and adaptive polynomial image interpolation. MATLAB codes for most of the simulation experiments supplied in the book are included in the appendix.

Visual perception is a complex process requiring interaction between the receptors in the eye that sense the stimulus and the neural system and the brain that are responsible for communicating and interpreting the sensed visual information. This process involves several physical, neural, and cognitive phenomena whose understanding is essential to design effective and computationally efficient imaging solutions. Building on advances in computer vision, image and video processing, neuroscience, and information engineering, perceptual digital imaging greatly enhances the capabilities of traditional imaging methods. Filling a gap in the literature, Perceptual Digital Imaging: Methods and Applications comprehensively covers the system design, implementation, and application aspects of this emerging specialized area. It gives readers a strong, fundamental understanding of theory and methods, providing a foundation on which solutions for many of the most interesting and challenging imaging problems can be built. The book features contributions by renowned experts who present the state of the art and recent trends in image acquisition, processing, storage, display, and visual quality evaluation. They detail advances in the field and explore human visual system-driven approaches across a broad spectrum of applications, including: Image quality and aesthetics assessment Digital camera imaging White balancing and color enhancement Thumbnail generation Image restoration Super-resolution imaging Digital halftoning and dithering Color feature extraction Semantic multimedia analysis and processing Video shot characterization Image and video encryption Display quality enhancement This is a valuable resource for readers who want to design and implement more effective solutions for cutting-edge digital imaging, computer vision, and multimedia applications. Suitable as a graduate-level textbook or stand-alone reference for researchers and practitioners, it provides a unique overview of an important and rapidly developing research field.

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

An uncoded multimedia transmission (UMT) system is one that skips quantization and entropy coding in compression and all subsequent binary operations, including channel coding and bit-to-symbol mapping of modulation. By directly transmitting non-binary symbols with amplitude modulation, the uncoded system avoids the annoying cliff effect observed in the coded transmission system. This advantage makes uncoded transmission more suited to both unicast in varying channel conditions and multicast to heterogeneous users. Particularly, in the first part of Uncoded Multimedia Transmission, we consider how to improve the efficiency of uncoded transmission and make it on par with coded transmission. We then address issues and challenges regarding how to better utilize temporal and spatial correlation of images and video in the uncoded transmission, to achieve the optimal transmission performance. Next, we investigate the resource allocation problem for uncoded transmission, including subchannel, bandwidth and power allocation. By properly allocating these resources, uncoded transmission can achieve higher efficiency and more robust performance. Subsequently, we consider the image and video delivery in MIMO broadcasting networks with diverse channel quality and varying numbers of antennas across receivers. Finally, we investigate the cases where uncoded transmission can be used in conjunction with digital transmission for a balanced efficiency and adaptation capability. This book is the very first monograph in the general area of uncoded multimedia transmission written in a self-contained format. It addresses both the fundamentals and the applications of uncoded transmission. It gives a systematic introduction to the fundamental theory and concepts in this field, and at the same time, also presents specific applications that reveal the great potential and impacts for the technologies generated from the research in this field. By concentrating several important studies and developments currently taking place in the field of uncoded transmission in a single source, this book can reduce the time and cost required to learn and improve skills and knowledge in the field. The authors have been actively working in this field for years, and this book is the final essence of their years of long research in this field. The book may be used as a collection of research notes for researchers in this field, a reference book for practitioners or engineers, as well as a textbook for a graduate advanced seminar in this field or any related fields. The references collected in this book may be used as further reading lists or references for the readers.

This book specifically addresses video shot boundary detection, which provides base for all video abstraction and high-level video segmentation approaches. Moreover, the other research areas which can benefit considerably from successful automation of shot boundary detection processes are distance learning, telemedicine, interactive television, digital libraries, multimedia news, video restoration and geographical information system. Despite all the research activity in shot boundary detection, there are some issues which have not been adequately addressed and need to be resolved. We discuss these major challenges in shot boundary detection and propose algorithms that can be adopted to find shot boundaries effectively. The monograph is intended to target a wide audience, both in academia and industrial research. It can also be used as research material for advanced courses in senior undergraduate and graduate programs. In this monograph we explore various major issues related to shot boundary detection which will be of tremendous importance in developing future search engines, multimedia and communication technologies. Besides covering effective algorithms, the monograph also provides a detail literature survey and describes major metrics used for shot boundary detection, thereby making it self contained. Technical topics discussed in the monograph include: 1) Effective algorithm for detecting various wipe patterns 2) Shot boundary detection in the presence of flashlight 3) Shot boundary detection in the presence of fire flicker and explosion 4) Shot boundary detection in the presence of illumination variation and motion

This book presents a thorough and detailed guide to image registration, outlining the principles and reviewing state-of-the-art tools and methods. The book begins by identifying the components of a general image registration system, and then describes the design of each component using various image analysis tools. The text reviews a vast array of tools and methods, not only describing the principles behind each tool and method, but also measuring and comparing their performances using synthetic and real data. Features: discusses similarity/dissimilarity measures, point detectors, feature extraction/selection and homogeneous/heterogeneous descriptors; examines robust estimators, point pattern matching algorithms, transformation functions, and image resampling and blending; covers principal axes methods, hierarchical methods, optimization-based methods, edge-based methods, model-based methods, and adaptive methods; includes a glossary, an extensive list of references, and an appendix on PCA.

The digital revolution over the past several decades has advanced every facet of evidence detection, photography, optimization, and interpretation. Forensic scientists and practitioners have benefited tremendously from the move from film to digital. With proper procedures in place, digital images and casework capabilities have increased tremendously in both complexity and range due to a vast array of tools to enhance evidence and photography. Forensic Digital Image Processing: Optimization of Impression Evidence provides the forensic investigator with the tools and understanding to extract, optimize, and interpret the maximum evidence possible from crime scenes to increase identifications. The book begins by examining the emergence of forensic digital image processing, and the gradual improvement and acceptance of the science over the past four decades. Coverage includes looking at the issues of image integrity and authentication including forensic image optimization and the manipulation of images. Chapters explore techniques exploiting color theory, modes, and channels to optimize signal-to-noise ratio in images. One of the greatest assets of digital image technology is the ability to combine multiple images of the same subject to create a final, blended image: one that displays the desired evidence and is especially useful for fingerprint or footwear impression. Later chapters demonstrate image subtraction, focus stacking, and high dynamic range, utilizing images in optimum focus and with substrate interference diminished or removed entirely. The authors look at fast Fourier transform as an optimal tool for noise removal, addressing basic theory and diagnosis of the noise signatures. The book discusses the history of digital imaging techniques and their treatment within the court system. Forensic Digital Image Processing: Optimization of Impression Evidence serves as an invaluable resource and tool for practicing professionals-as well as those new to the field-to look at best practices, the latest technology, and advances in utilizing the increasing array of tools of the trade.

The field of medical imaging seen rapid development over the last two decades and has consequently revolutionized the way in which modern medicine is practiced. Diseases and their symptoms are constantly changing therefore continuous updating is necessary for the data to be relevant. Diseases fall into different categories, even a small difference in symptoms may result in categorising it in a different group altogether. Thus analysing data accurately is of critical importance. This book concentrates on diagnosing diseases like cancer or tumor from different modalities of images. This book is divided into the following domains: Importance of big data in medical imaging, pre-processing, image registration, feature extraction, classification and retrieval. It is further supplemented by the medical analyst for a continuous treatment process. The book provides an automated system that could retrieve images based on user's interest to a point of providing decision support. It will help medical analysts to take informed decisions before planning treatment and surgery. It will also be useful to researchers who are working in problems involved in medical imaging.

Computational photography refers broadly to imaging techniques that enhance or extend the capabilities of digital photography. This new and rapidly developing research field has evolved from computer vision, image processing, computer graphics and applied optics-and numerous commercial products capitalizing on its principles have already appeared in diverse market applications, due to the gradual migration of computational algorithms from computers to imaging devices and software. Computational Photography: Methods and Applications provides a strong, fundamental understanding of theory and methods, and a foundation upon which to build solutions for many of today's most interesting and challenging computational imaging problems. Elucidating cutting-edge advances and applications in digital imaging, camera image processing, and computational photography, with a focus on related research challenges, this book: Describes single capture image fusion technology for consumer digital cameras Discusses the steps in a camera image processing pipeline, such as visual data compression, color correction and enhancement, denoising, demosaicking, super-resolution reconstruction, deblurring, and high dynamic range imaging Covers shadow detection for surveillance applications, camera-driven document rectification, bilateral filtering and its applications, and painterly rendering of digital images Presents machine-learning methods for automatic image colorization and digital face beautification Explores light field acquisition and processing, space-time light field rendering, and dynamic view synthesis with an array of cameras Because of the urgent challenges associated with emerging digital camera applications, image processing methods for computational photography are of paramount importance to research and development in the imaging community. Presenting the work of leading experts, and edited by a renowned authority in digital color imaging and camera image processing, this book considers the rapid developments in this area and addresses very particular research and application problems. It is ideal as a stand-alone professional reference for design and implementation of digital image and video processing tasks, and it can also be used to support graduate courses in computer vision, digital imaging, visual data processing, and computer graphics, among others.

Illustrating essential aspects of adaptive image processing from a computational intelligence viewpoint, the second edition of Adaptive Image Processing: A Computational Intelligence Perspective provides an authoritative and detailed account of computational intelligence (CI) methods and algorithms for adaptive image processing in regularization, edge detection, and early vision.

With three new chapters and updated information throughout, the new edition of this popular reference includes substantial new material that focuses on applications of advanced CI techniques in image processing applications. It introduces new concepts and frameworks that demonstrate how neural networks, support vector machines, fuzzy logic, and evolutionary algorithms can be used to address new challenges in image processing, including low-level image processing, visual content analysis, feature extraction, and pattern recognition.

Emphasizing developments in state-of-the-art CI techniques, such as content-based image retrieval, this book continues to provide educators, students, researchers, engineers, and technical managers in visual information processing with the up-to-date understanding required to address contemporary challenges in image content processing and analysis.

This book first details a proposed Stationary Bionic Wavelet Transform (SBWT) for use in speech processing. The author then details the proposed techniques based on SBWT. These techniques are relevant to speech enhancement, speech recognition, and ECG de-noising. The techniques are then evaluated by comparing them to a number of methods existing in literature. For evaluating the proposed techniques, results are applied to different speech and ECG signals and their performances are justified from the results obtained from using objective criterion such as SNR, SSNR, PSNR, PESQ , MAE, MSE and more.

This book offers a full history of a homeless movement in Tokyo that lasted nearly a decade. It shows how homeless people and their external supporters in the city combined their scarce resources to generate and sustain the movement. The study advocates a more nuanced analysis of movement gains to appreciate how poor people can benefit by acting collectively. It also draws attention to potential difficulties faced by lower-stratum movements aided by external allies. In particular, the study highlights how actions of the state can undermine the relations between aggrieved allies in such a way as to limit gains. The book is the first in English to detail homeless mobilization in Japan. It also addresses the origins of increased homelessness and development of homelessness policy in the country. Besides homelessness, it covers a number of current social issues, including economic globalization, social exclusion, and politics over space.

The International Scientific and Professional Conference on Geodesy, Cartography and Geoinformatics 2017 (GCG 2017) was organized under the auspices of the Faculty of Mining, Ecology, Process Control and Geotechnologies, Technical University of Kosice (SK), Pavol Jozef Safarik University in Kosice (SK), Faculty of Civil Engineering, STU Bratislava (SK), Faculty of Civil Engineering, CTU Prague (CZ), University of Technology, Kielce (PL), AGH University of Science and Technology, Krakow (PL), Upper Nitra Mines Prievidza, plc. (SK) and the Slovakian Mining Society (SK). The conference was held from October 10 - 13, 2017, in Low Tatras, Slovakia. The purpose of the conference was to provide a forum for prominent scientists, researchers and professionals from Slovakia, Poland and the Czech Republic to present novel and fundamental advances in the fields of geodesy, cartography and geoinformatics. Conference participants had the opportunity to exchange and share their experiences, research and results solved within scientific research projects with other colleagues. The conference focused on a wide spectrum of actual topics and subject areas in Surveying and Mine Surveying, Geodetic Control and Geodynamics, and Cartography and Geoinformatics and collected in this proceedings volume.

Computational intelligence based techniques have firmly established themselves as viable, alternate, mathematical tools for more than a decade. They have been extensively employed in many systems and application domains, among these signal processing, automatic control, industrial and consumer electronics, robotics, finance, manufacturing systems, electric power systems, and power electronics. Image processing is also an extremely potent area which has attracted the atten tion of many researchers who are interested in the development of new computational intelligence-based techniques and their suitable applications, in both research prob lems and in real-world problems. Part I of the book discusses several image preprocessing algorithms; Part II broadly covers image compression algorithms; Part III demonstrates how computational intelligence-based techniques can be effectively utilized for image analysis purposes; and Part IV shows how pattern recognition, classification and clustering-based techniques can be developed for the purpose of image inferencing. The book offers a unified view of the modern computational intelligence tech niques required to solve real-world problems and it is suitable as a reference for engineers, researchers and graduate students.

Image Processing with MATLAB (R): Applications in Medicine and Biology explains complex, theory-laden topics in image processing through examples and MATLAB (R) algorithms. It describes classical as well emerging areas in image processing and analysis. Providing many unique MATLAB codes and functions throughout, the book covers the theory of probability and statistics, two-dimensional fast Fourier transform, nonlinear diffusion filtering, and partial differential equation (PDE)-based image denoising techniques. It presents intensity-based image segmentation methods, including thresholding techniques as well as K-means and fuzzy C-means clustering techniques. The authors also explore Markov random field (MRF)-based image segmentation, boundary and curvature analysis methods, and parametric and geometric deformable models. The final chapters focus on three specific applications of image processing and analysis. Reducing the need for the trial-and-error way of solving problems, this book helps readers understand advanced concepts by applying algorithms to real-world problems in medicine and biology. A solutions manual is available for instructoes wishing to convert this reference to classroom use.

A Sampler of Useful Computational Tools for Applied Geometry, Computer Graphics, and Image Processing shows how to use a collection of mathematical techniques to solve important problems in applied mathematics and computer science areas. The book discusses fundamental tools in analytical geometry and linear algebra. It covers a wide range of topics, from matrix decomposition to curvature analysis and principal component analysis to dimensionality reduction. Written by a team of highly respected professors, the book can be used in a one-semester, intermediate-level course in computer science. It takes a practical problem-solving approach, avoiding detailed proofs and analysis. Suitable for readers without a deep academic background in mathematics, the text explains how to solve non-trivial geometric problems. It quickly gets readers up to speed on a variety of tools employed in visual computing and applied geometry.

Radar scattering and imaging of rough surfaces is an active interdisciplinary area of research with many practical applications in fields such as mineral and resource exploration, ocean and physical oceanography, military and national defense, planetary exploration, city planning and land use, environmental science, and many more. By focusing on the most advanced analytical and numerical modeling and describing both forward and inverse modeling, Radar Scattering and Imaging of Rough Surfaces: Modeling and Applications with MATLAB (R) connects the scattering process to imaging techniques by vivid examples through numerical and experimental demonstrations and provides computer codes and practical uses. This book is unique in its simultaneous treatment of radar scattering and imaging. Key Features Bridges physical modeling with simulation for resolving radar imaging problems (the first comprehensive work to do so) Provides excellent basic and advanced information for microwave remote-sensing professionals in various fields of science and engineering Covers most advanced analytical and numerical modeling for both backscattering and bistatic scattering Includes MATLAB (R) codes useful not only for academics but also for radar engineers and scientists to develop tools applicable in different areas of earth studies Covering both the theoretical and the practical, Radar Scattering and Imaging of Rough Surfaces: Modeling and Applications with MATLAB (R) is an invaluable resource for professionals and students using remote sensing to study and explain the Earth and its processes. University and research institutes, electrical and radar engineers, remote-sensing image users, application software developers, students, and academics alike will benefit from this book. The author, Kun-Shan Chen, is an internationally known and respected engineer and scientist and an expert in the field of electromagnetic modeling.

This book provides the reader with an understanding of what color is, where color comes from, and how color can be used correctly in many different applications. The authors first treat the physics of light and its interaction with matter at the atomic level, so that the origins of color can be appreciated. The intimate relationship between energy levels, orbital states, and electromagnetic waves helps to explain why diamonds shimmer, rubies are red, and the feathers of the Blue Jay are blue. Then, color theory is explained from its origin to the current state of the art, including image capture and display as well as the practical use of color in disciplines such as computer graphics, computer vision, photography, and film.

Edited and expanded to keep pace with the digital revolution, the new edition of this highly popular and critically acclaimed work provides a comprehensive exploration of imaging science. Brilliantly written and extensively illustrated, The Science of Imaging: An Introduction, Second Edition covers the fundamental laws of physics as well as the cutting-edge techniques defining current and future directions in the field. Improvements to this Edition Include: A new chapter on astronomical imaging A larger format with a wealth of illustrations Major revisions in the areas of digital imaging and modern technology Updated references with links to a wealth of online resources-including teaching material and expanded information This accessible introduction to the subject takes students on a grand tour of imaging. Starting with the fundamentals of light and basic cameras, the author journeys through television and holography to advanced scientific and medical imaging. He highlights essential formulas, while keeping the complex mathematics to a minimum. Copiously illustrated with a wealth of examples and a 16-page color insert, the text covers optics, imaging systems, materials, and image interpretation and creation in a manner that makes it easy to understand. Praise for the critically acclaimed First Edition: It's the best book I have read on the subject at this level.-Ron Graham, RPS Journal... every student should read it, every photographer should own it, and every lecturer and journalist should know its contents inside out.-Jon Tarrant, British Journal of Photography