This volume brings together many of the world's leading experts in the development of new imaging methodologies to detect, identify, and counter security threats to society. It covers three broadly defined but interrelated areas: the mathematics and computer science of automatic detection and identification; image processing techniques for radar and sonar; and detection of anomalies in biomedical and chemical images.

This thesis proposes machine learning methods for understanding scenes via behaviour analysis and online anomaly detection in video. The book introduces novel Bayesian topic models for detection of events that are different from typical activities and a novel framework for change point detection for identifying sudden behavioural changes. Behaviour analysis and anomaly detection are key components of intelligent vision systems. Anomaly detection can be considered from two perspectives: abnormal events can be defined as those that violate typical activities or as a sudden change in behaviour. Topic modelling and change-point detection methodologies, respectively, are employed to achieve these objectives. The thesis starts with the development of learning algorithms for a dynamic topic model, which extract topics that represent typical activities of a scene. These typical activities are used in a normality measure in anomaly detection decision-making. The book also proposes a novel anomaly localisation procedure. In the first topic model presented, a number of topics should be specified in advance. A novel dynamic nonparametric hierarchical Dirichlet process topic model is then developed where the number of topics is determined from data. Batch and online inference algorithms are developed. The latter part of the thesis considers behaviour analysis and anomaly detection within the change-point detection methodology. A novel general framework for change-point detection is introduced. Gaussian process time series data is considered. Statistical hypothesis tests are proposed for both offline and online data processing and multiple change point detection are proposed and theoretical properties of the tests are derived. The thesis is accompanied by open-source toolboxes that can be used by researchers and engineers.

First Published in 1997. Routledge is an imprint of Taylor & Francis, an informa company.

Random Signals, Noise and Filtering develops the theory of random processes and its application to the study of systems and analysis of random data. The text covers three important areas: (1) fundamentals and examples of random process models, (2) applications of probabilistic models: signal detection, and filtering, and (3) statistical estimation--measurement and analysis of random data to determine the structure and parameter values of probabilistic models. This volume by Breipohl and Shanmugan offers the only one-volume treatment of the fundamentals of random process models, their applications, and data analysis.

Dermoscopy is a noninvasive skin imaging technique that uses optical magnification and either liquid immersion or cross-polarized lighting to make subsurface structures more easily visible when compared to conventional clinical images. It allows for the identification of dozens of morphological features that are particularly important in identifying malignant melanoma. Dermoscopy Image Analysis summarizes the state of the art of the computerized analysis of dermoscopy images. The book begins by discussing the influence of color normalization on classification accuracy and then: Investigates gray-world, max-RGB, and shades-of-gray color constancy algorithms, showing significant gains in sensitivity and specificity on a heterogeneous set of images Proposes a new color space that highlights the distribution of underlying melanin and hemoglobin color pigments, leading to more accurate classification and border detection results Determines that the latest border detection algorithms can achieve a level of agreement that is only slightly lower than the level of agreement among experienced dermatologists Provides a comprehensive review of various methods for border detection, pigment network extraction, global pattern extraction, streak detection, and perceptually significant color detection Details a computer-aided diagnosis (CAD) system for melanomas that features an inexpensive acquisition tool, clinically meaningful features, and interpretable classification feedback Presents a highly scalable CAD system implemented in the MapReduce framework, a novel CAD system for melanomas, and an overview of dermatological image databases Describes projects that made use of a publicly available database of dermoscopy images, which contains 200 high-quality images along with their medical annotations Dermoscopy Image Analysis not only showcases recent advances but also explores future directions for this exciting subfield of medical image analysis, covering dermoscopy image analysis from preprocessing to classification.

This book describes the methods and algorithms for image pre-processing and recognition. These methods are based on a parallel shift technology of the imaging copy, as well as simple mathematical operations to allow the generation of a minimum set of features to describe and recognize the image. This book also describes the theoretical foundations of parallel shift technology and pattern recognition. Based on these methods and theories, this book is intended to help researchers with artificial intelligence systems design, robotics, and developing software and hardware applications.

Based on the experiences of the Department of Information Engineering of the University of Pisa and the Radar and Surveillance System (RaSS) national laboratory of the National Interuniversity Consortium of Telecommunication (CNIT), Radar Imaging for Maritime Observation presents the most recent results in radar imaging for maritime observation. The book explores both the areas of sea surface remote sensing and maritime surveillance providing key theoretical concepts of SAR and ISAR imaging and more advanced and ad-hoc techniques for applications in maritime scenarios. The book is organized in two sections. The first section discusses the fundamentals of standard SAR/ISAR processing and novel imaging techniques, such as Bistatic, Passive, and, 3D Interferometric ISAR. The second section focuses on the applications and results obtained by processing real data from maritime observations like SAR image processing for oil spill, detection in SAR images and fractal analysis. Useful to both beginners and experts in maritime observation, this book provides several examples of (mainly space-borne) radar imaging of maritime targets. Nevertheless, the same principles and techniques apply to the case of manned or unmanned carriers and to ground and air moving targets.

Sea Ice Image Processing with MATLAB addresses the topic of image processing for the extraction of key sea ice characteristics from digital photography, which is of great relevance for Artic remote sensing and marine operations. This valuable guide provides tools for quantifying the ice environment that needs to be identified and reproduced for such testing. This includes fit-for-purpose studies of existing vessels, new-build conceptual design and detailed engineering design studies for new developments, and studies of demanding marine operations involving multiple vessels and operational scenarios in sea ice. A major contribution of this work is the development of automated computer algorithms for efficient image analysis. These are used to process individual sea-ice images and video streams of images to extract parameters such as ice floe size distribution, and ice types. Readers are supplied with Matlab source codes of the algorithms for the image processing methods discussed in the book made available as online material. Features Presents the first systematic work using image processing techniques to identify ice floe size distribution from aerial images Helps identify individual ice floe and obtain floe size distributions for Arctic offshore operations and transportation Explains specific algorithms that can be combined to solve various problems during polar sea ice investigations Includes MATLAB (R) codes useful not only for academics, but for ice engineers and scientists to develop tools applicable in different areas such as sustainable arctic marine and coastal technology research Provides image processing techniques applicable to other fields like biomedicine, material science, etc

Case-based reasoning in design is becoming an important approach to computer-support for design as well as an important component in understanding the design process. Design has become a major focus for problem solving paradigms due to its complexity and open-ended nature. This book presents a clear description of how case-based reasoning can be applied to design problems, including the representation of design cases, indexing and retrieving design cases, and the range of paradigms for adapting design cases. With a focus on design, this book differs from others that provide a generalist view of case-based reasoning.
This volume provides two important contributions to the area:
* a general description of the issues and alternatives in applying case-based reasoning to design, and
* a description of specific implementations of case-based design.
Through this combination, the reader will learn about both the general issues and the practical problems in supporting design through case-based reasoning. This book was prepared to fill a gap in the literature on the unique problems that design introduces to computational paradigms developed in computer science. It also addresses the needs of computational support for design problem solving from both theoretical and practical perspectives.

An up-to-date, expert guide to modern digital image databases

This volume presents the state of the art in digital image database design, with a concentration on storage and retrieval techniques, and includes a set of selected application case studies.

Chapters by experts from around the world explore a variety of techniques for accessing images based on color, texture, shape, and semantic descriptions. Underlying principles are stressed, including compression, indexing, storage organization, and transmission.

Image Databases also features detailed coverage of these important issues:

• Hierarchical storage management
• Database support
• Search at multiple abstraction levels
• Content extraction from compressed imagery
• Standards for representation and search

Case studies cover important application areas including:

• Photographic images
• Satellite imagery
• Images in the oil industry
• Medical imagery

A wide range of introductory material and an extensive bibliography makes Image Databases an excellent text for graduate-level students. It also serves as a valuable reference for developers and researchers in the field, and as a guide for helping IT professionals more fully understand the discipline.

Providing a wealth of information on fundamental topics in the areas of linear air and underwater acoustics, as well as space-time signal processing, this book provides real-world design and analysis equations. As a consequence of the interdisciplinary nature of air and underwater acoustics, the book is divided into two parts: Acoustic Field Theory and Space-Time Signal Processing. It covers the fundamentals of acoustic wave propagation as well as the fundamentals of aperture theory, array theory, and signal processing. Starting with principles and using a consistent, mainly standard notation, this book develops, in detail, basic results that are useful in a variety of air and underwater acoustic applications. Numerous figures, examples, and problems are included.

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.

Fuzzy sets, near sets, and rough sets are useful and important stepping stones in a variety of approaches to image analysis. These three types of sets and their various hybridizations provide powerful frameworks for image analysis. Emphasizing the utility of fuzzy, near, and rough sets in image analysis, Rough Fuzzy Image Analysis: Foundations and Methodologies introduces the fundamentals and applications in the state of the art of rough fuzzy image analysis. In the first chapter, the distinguished editors explain how fuzzy, near, and rough sets provide the basis for the stages of pictorial pattern recognition: image transformation, feature extraction, and classification. The text then discusses hybrid approaches that combine fuzzy sets and rough sets in image analysis, illustrates how to perform image analysis using only rough sets, and describes tolerance spaces and a perceptual systems approach to image analysis. It also presents a free, downloadable implementation of near sets using the Near Set Evaluation and Recognition (NEAR) system, which visualizes concepts from near set theory. In addition, the book covers an array of applications, particularly in medical imaging involving breast cancer diagnosis, laryngeal pathology diagnosis, and brain MR segmentation. Edited by two leading researchers and with contributions from some of the best in the field, this volume fully reflects the diversity and richness of rough fuzzy image analysis. It deftly examines the underlying set theories as well as the diverse methods and applications.

Presenting encryption algorithms with diverse characteristics, Image Encryption: A Communication Perspective examines image encryption algorithms for the purpose of secure wireless communication. It considers two directions for image encryption: permutation-based approaches and substitution-based approaches. Covering the spectrum of image encryption principles and techniques, the book compares image encryption with permutation- and diffusion-based approaches. It explores number theory-based encryption algorithms such as the Data Encryption Standard, the Advanced Encryption Standard, and the RC6 algorithms. It not only details the strength of various encryption algorithms, but also describes their ability to work within the limitations of wireless communication systems. Since some ciphers were not designed for image encryption, the book explains how to modify these ciphers to work for image encryption. It also provides instruction on how to search for other approaches suitable for this task. To make this work comprehensive, the authors explore communication concepts concentrating on the orthogonal frequency division multiplexing (OFDM) system and present a simplified model for the OFDM communication system with its different implementations. Complete with simulation experiments and MATLAB (R) codes for most of the simulation experiments, this book will help you gain the understanding required to select the encryption method that best fulfills your application requirements.

This unique reference presents in-depth coverage of the latest methods and applications of digital image processing describing various computer architectures ideal for satisfying specific image processing demands.

Signals and Images: Advances and Results in Speech, Estimation, Compression, Recognition, Filtering, and Processing cohesively combines contributions from field experts to deliver a comprehensive account of the latest developments in signal processing. These experts detail the results of their research related to audio and speech enhancement, acoustic image estimation, video compression, biometric recognition, hyperspectral image analysis, tensor decomposition with applications in communications, adaptive sparse-interpolated filtering, signal processing for power line communications, bio-inspired signal processing, seismic data processing, arithmetic transforms for spectrum computation, particle filtering in cooperative networks, three-dimensional television, and more. This book not only shows how signal processing theory is applied in current and emerging technologies, but also demonstrates how to tackle key problems such as how to enhance speech in the time domain, improve audio quality, and meet the desired electrical consumption target for controlling carbon emissions. Signals and Images: Advances and Results in Speech, Estimation, Compression, Recognition, Filtering, and Processing serves as a guide to the next generation of signal processing solutions for speech and video coding, hearing aid devices, big data processing, smartphones, smart digital communications, acoustic sensors, and beyond.

Corona SDK is one of the most powerful tools used to create games and apps for mobile devices. The market requires speed; new developers need to operate quickly and efficiently. Create 2D Mobile Games with Corona SDK gives you the tools needed to master Corona - even within the framework of professional constraints. A must-read guide, this book gives you fast, accurate tips to learn the programming language necessary to create games. Read it sequentially or as an FAQ and you will have the tools you need to create any base game before moving on to advanced topics. The tutorial-based format: Contains step-by-step directions complete with coding and screenshots Is filled with tutorials, tips, and links to useful online resources Includes a comprehensive companion website featuring online exercise files to practice coding, full build samples from the text, additional book details, and more!

Electron Microscopy and Analysis deals with several sophisticated techniques for magnifying images of very small objects by large amounts - especially in a physical science context. It has been ten years since the last edition of Electron Microscopy and Analysis was published and there have been rapid changes in this field since then. The authors have vastly updated their very successful second edition, which is already established as an essential laboratory manual worldwide, and they have incorporated questions and answers in each chapter for ease of learning. Equally as relevant for material scientists and bioscientists, this third edition is an essential textbook.

Optimal and Adaptive Signal Processing covers the theory of optimal and adaptive signal processing using examples and computer simulations drawn from a wide range of applications, including speech and audio, communications, reflection seismology and sonar systems. The material is presented without a heavy reliance on mathematics and focuses on one-dimensional and array processing results, as well as a wide range of adaptive filter algorithms and implementations. Topics discussed include random signals and optimal processing, adaptive signal processing with the LMS algorithm, applications of adaptive filtering, algorithms and structures for adaptive filtering, spectral analysis, and array signal processing.

Optimal and Adaptive Signal Processing is a valuable guide for scientists and engineers, as well as an excellent text for senior undergraduate/graduate level students in electrical engineering.

Presents the statistical analysis of morphological filters and their automatic optical design, the development of morphological features for image signatures, and the design of efficient morphological algorithms. Extends the morphological paradigm to include other branches of science and mathematics.;This book is designed to be of interest to optical, electrical and electronics, and electro-optic engineers, including image processing, signal processing, machine vision, and computer vision engineers, applied mathematicians, image analysts and scientists and graduate-level students in image processing and mathematical morphology courses.

In the development of digital multimedia, the importance and impact of image processing and mathematical morphology are well documented in areas ranging from automated vision detection and inspection to object recognition, image analysis and pattern recognition. Those working in these ever-evolving fields require a solid grasp of basic fundamentals, theory, and related applications-and few books can provide the unique tools for learning contained in this text. Image Processing and Mathematical Morphology: Fundamentals and Applications is a comprehensive, wide-ranging overview of morphological mechanisms and techniques and their relation to image processing. More than merely a tutorial on vital technical information, the book places this knowledge into a theoretical framework. This helps readers analyze key principles and architectures and then use the author's novel ideas on implementation of advanced algorithms to formulate a practical and detailed plan to develop and foster their own ideas. The book: Presents the history and state-of-the-art techniques related to image morphological processing, with numerous practical examples Gives readers a clear tutorial on complex technology and other tools that rely on their intuition for a clear understanding of the subject Includes an updated bibliography and useful graphs and illustrations Examines several new algorithms in great detail so that readers can adapt them to derive their own solution approaches This invaluable reference helps readers assess and simplify problems and their essential requirements and complexities, giving them all the necessary data and methodology to master current theoretical developments and applications, as well as create new ones.

This book introduces advanced and hybrid compression techniques specifically used for medical images. The book discusses conventional compression and compressive sensing (CS) theory based approaches that are designed and implemented using various image transforms, such as: Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and Singular Value Decomposition (SVD) and greedy based recovery algorithm. The authors show how these techniques provide simulation results of various compression techniques for different types of medical images, such as MRI, CT, US, and x-ray images. Future research directions are provided for medical imaging science. The book will be a welcomed reference for engineers, clinicians, and research students working with medical image compression in the biomedical imaging field. Covers various algorithms for data compression and medical image compression; Provides simulation results of compression algorithms for different types of medical images; Provides study of compressive sensing theory for compression of medical images.

Presents basic theories, techniques, and procedures used to analyze, design, and implement two-dimensional filters; and surveys a number of applications in image and seismic data processing that demonstrate their use in real-world signal processing. For graduate students in electrical and computer e

This volume on virtual and augmented reality (VR/AR) and gamification for cultural heritage offers an insightful introduction to the theories, development, recent applications and trends of the enabling technologies for mixed reality and gamified interaction in cultural heritage and creative industries in general. It has two main goals: serving as an introductory textbook to train beginning and experienced researchers in the field of interactive digital cultural heritage, and offering a novel platform for researchers in and across the culturally-related disciplines. To this end, it is divided into two sections following a pedagogical model developed by the focus group of the first EU Marie S. Curie Fellowship Initial Training Network on Digital Cultural Heritage (ITN-DCH): Section I describes recent advances in mixed reality enabling technologies, while section II presents the latest findings on interaction with 3D tangible and intangible digital cultural heritage. The sections include selected contributions from some of the most respected scholars, researchers and professionals in the fields of VR/AR, gamification, and digital heritage. This book is intended for all heritage professionals, researchers, lecturers and students who wish to explore the latest mixed reality and gamification technologies in the context of cultural heritage and creative industries. It pursues a pedagogic approach based on trainings, conferences, workshops and summer schools that the ITN-DCH fellows have been following in order to learn how to design next-generation virtual heritage applications, systems and services.

This book presents the state of the art in online visual tracking, including the motivations, practical algorithms, and experimental evaluations. Visual tracking remains a highly active area of research in Computer Vision and the performance under complex scenarios has substantially improved, driven by the high demand in connection with real-world applications and the recent advances in machine learning. A large variety of new algorithms have been proposed in the literature over the last two decades, with mixed success. Chapters 1 to 6 introduce readers to tracking methods based on online learning algorithms, including sparse representation, dictionary learning, hashing codes, local model, and model fusion. In Chapter 7, visual tracking is formulated as a foreground/background segmentation problem, and tracking methods based on superpixels and end-to-end deep networks are presented. In turn, Chapters 8 and 9 introduce the cutting-edge tracking methods based on correlation filter and deep learning. Chapter 10 summarizes the book and points out potential future research directions for visual tracking. The book is self-contained and suited for all researchers, professionals and postgraduate students working in the fields of computer vision, pattern recognition, and machine learning. It will help these readers grasp the insights provided by cutting-edge research, and benefit from the practical techniques available for designing effective visual tracking algorithms. Further, the source codes or results of most algorithms in the book are provided at an accompanying website.