Image processing Books

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Book SynopsisBrimming with top articles from experts in signal processing and biomedical engineering, Time Frequency and Wavelets in Biomedical Signal Processing introduces time--frequency, time--scale, wavelet transform methods, and their applications in biomedical signal processing.Table of ContentsList of Contributors. Preface. TIME-FREQUENCY ANALYSIS METHODS WITH BIOMEDICAL APPLICATIONS. Recent Advances in Time-Frequency Representations: SomeTheoretical Foundation (W. Williams). Biological Applications and Interpretations of Time-Frequency Signal Analysis (W. Williams). The Application of Advanced Time-Frequency Analysis Techniques to Doppler Ultrasound (S. Marple, et al.). Analysis of ECG Late Potentials Using Time-Frequency Methods (H. Dickhaus & H. Heinrich). Time-Frequency Distributions Applied to Uterine EMG: Characterization and Assessment (J. Duchene & D. Devedeux). Time-Frequency Analyses of the Electrogastrogram (Z. Lin and J. Chen). Recent Advances in Time-Frequency and Time-Scale Methods (C. Mello & M. Akay). WAVELETS, WAVELET PACKETS, AND MATCHING PURSUITS WITH BIOMEDICAL APPLICATIONS. Fast Algorithms for Wavelet Transform Computation (O. Rioul & P. Duhamel). Analysis of Cellular Vibrations in the Living Cochlea Using the Continuous Wavelet Transform and the Short-Time Fourier Transform (M. Teich, et al.). Alterative Processing Method Using Gabor Wavelets and the Wavelet Transform for the Analysis of Phonocardiogram Signals (M. Matalgah, et al.). Wavelet Feature Extraction from Neurophysiological Signals (M. Sun & R. Sclabassi). Experiments with Adapted Wavelet De-Noising for Medical Signals and Images (R. Coifman & M. Wickerhauser). Speech Enhancement for Hearing Aids (J. Rutledge). From Continuous Wavelet Transform to Wavelet Packets: Application to the Estimation of Pulmonary Microvascular Pressure (M. Karrakchou & M. Kunt). In Pursuit of Time-Frequency Representation of Brain Signals (P. Durka & K. Blinowska). EEG Spike Directors Based on Different Decompositions: A Comparative Study (L. Senhadji, et al.). WAVELETS AND MEDICAL IMAGING. A Discrete Dyadic Wavelet Transform for Multidimensional Feature Analysis (I. Koren & A. Laine). Hexagonal QMF Banks and Wavelets (S. Schuler & A. Laine). Inversion of the Radon Transform under Wavelet Constraints (B. Sahiner & A. Yagle). Wavelets Applied to Mammograms (W. Richardson). Hybrid Wavelet Transform for Image Enhancement forComputer-Assisted Diagnosis and Telemedicine Applications (L. Clarke, et al.). Medical Image Enhancement Using Wavelet Transform and Arithmetic Coding (P. Saipetch, et al.). Adapted Wavelet Encoding in Functional Magnetic Resonance Imaging (D. Healy, et al.). A Tutorial Overview of a Stabilization Algorithm for Limited-Angle Tomography (T. Olson). Wavelet Compression of Medical Images (A. Manduca). WAVELETS, NEURAL NETWORKS, AND FRACTALS. Single Side Scaling Wavelet Frame and Neural Network (Q. Zhang). Analysis of Evoked Potentials Using Wavelet Networks (H. Heinrich & H. Dickhaus). Self-Organizing Wavelet-Based Neural Networks (K. Kobayashi). On Wavelets and Fractal Processes (P. Flandrin). Fractal Analysis of Heart Rate Variability (R. Fischer & M. Akay). Index. Editor's Biography.

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Book SynopsisPrinciples of Magnetic Resonance Imaging Biomedical/Electrical Engineering Principles of Magnetic Resonance Imaging A Signal Processing Perspective A volume in the IEEE Press Series in Biomedical EngineeringMetin Akay. Series Editor Since its inception in 1971. MRI has developed into a premier tool for anatomical and runaional imaging. Prin??ples ofMagne??c Resonance Imaging provides a clear and comprehensive treatment of MR image formation principles from a signal processing perspective. You will find discussion of these essential topics: Mathematical fundamentals Signal generation and detection principles Signal characteristics Signal localization principles Image reconstruction techniques Image contrast mechanisms Image resolution. noise, and artifacts Fast-scan imaging Constrained reconstruction Spatial information encoding Table of ContentsPreface. Acknowledgments. Introduction. Mathematical Fundamentals. Signal Generation and Detection. Signal Characteristics. Signal Localization. Image Reconstruction. Image Contrast. Image Resolution, Noise, and Artifacts. Fast-Scan Imaging. Constrained Reconstruction. Appendix A: Mathematical Formulas. Appendix B: Glossary. Appendix C: Abbreviations. Appendix D: Mathematical Symbols. Appendix E: Physical Constants. Bibliography. Index. About the Authors.

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Book SynopsisTaking a critical look at the realities that have shaped the first stage of Barack Obama's presidency, Morton Keller offers a history-focused examination of Obama's developing style of governing, with particular attention to his signature policies of the stimulus, financial, and health care reforms.Table of Contents Foreword Acknowledgments Introduction Chapter One: Governing Chapter Two: Fixing the Economy Chapter Three: Into the Maze: Health Care Chapter Four: Contexts: Analogy and Ideology Chapter Five: Unfinished Business: Policy and Politics Notes About the Author Index

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Book SynopsisAn exploration of random processes for image and signal processing. It seeks to reflect the author's increasing appreciation of the profound differences between deterministic and probabilistic scientific epistemology. Topics include canonical representation and transform coding.

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Book SynopsisThis bible of a whole generation of communications engineers was originally published in 1958. The focus is on the statistical theory underlying the study of signals and noises in communications systems, emphasizing techniques as well s results. End of chapter problems are provided. Sponsored by: IEEE Communications SocietyTable of ContentsPreface to the IEEE Press Edition. Preface. Errata. Introduction. Probability. Random Variables and Probability Distributions. Averages. Sampling. Spectral Analysis. Shot Noise. The Gaussian Process. Linear Systems. Noise Figures. Optimum Linear Systems. Nonlinear Devices: The Direct Method. Nonlinear Devices: The Transform Method. Statistical Detection Signals. Appendix 1: The Impulse Function. Appendix 2: Integral Equations. Bibliography. Index.

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Book SynopsisBrings the reader up-to-date on all aspects concerning ECCM at the antenna level. It is a reference tool for professionals seeking quick answers to on-the-job problems. This text delivers an accurate description of working principles, processing schemes and performance evaluation techniques.Table of ContentsIntroduction to ECM and ECCM techniques for radar systems; low sidelobe antennas; sidelobe blanking system; sidelobe canceller (SLC) system; adaptive arrays.

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Book SynopsisProvides information on electronic intelligence (ELINT) analysis techniques, with coverage of their applications, strengths and limitations. Now refined and updated, this second edition presents new concepts and techniques.Table of ContentsSignal-to-Noise-Ratio Considerations for Analog and Digital Systems. Signal Power. Polarization. Beam Analysis. Antenna Scan Analysis. Intrapulse Analysis. Pulse Repetition Interval (PRI) Analysis. Radio Frequency (RF) Analysis. Deinterleaving Pulse Trains. Determining ELINT Parameter Limits. ELINT Data Files.

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Book SynopsisThis book introduces students to projective geometry from an analytic perspective, mixing recent results from the past 100 years with the history of the field in one of the most comprehensive surveys of the subject. The subject is taught conceptually, with worked examples and diagrams to aid in understanding.Trade Review'This book provides a lively and lovely perspective on real projective spaces, combining art, history, groups and elegant proofs.' William M. Kantor'This book is a celebration of the projective viewpoint of geometry. It gradually introduces the reader to the subject, and the arguments are presented in a way that highlights the power of projective thinking in geometry. The reader surprisingly discovers not only that Euclidean and related theorems can be realized as derivatives of projective results, but there are also unnoticed connections between results from ancient times. The treatise also contains a large number of exercises and is dotted with worked examples, which help the reader to appreciate and deeply understand the arguments they refer to. In my opinion this is a book that will definitely change the way we look at the Euclidean and projective analytic geometry.' Alessandro Siciliano, Università degli Studi della BasilicataTable of ContentsPreface; Part I. The Real Projective Plane: 1. Fundamental aspects of the real projective plane; 2. Collineations; 3. Polarities and conics; 4. Cross-ratio; 5. The group of the conic; 6. Involution; 7. Affine plane geometry viewed projectively; 8. Euclidean plane geometry viewed projectively; 9. Transformation geometry: Klein's point of view; 10. The power of projective thinking; 11. From perspective to projective; 12. Remarks on the history of projective geometry; Part II. Two Real Projective 3-Space: 13. Fundamental aspects of real projective space; 14. Triangles and tetrahedra; 15. Reguli and quadrics; 16. Line geometry; 17. Projections; 18. A glance at inversive geometry; Part III. Higher Dimensions: 19. Generalising to higher dimensions; 20. The Klein quadric and Veronese surface; Appendix: Group actions; References; Index.

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Book SynopsisUnmanned aircraft systems (UAS) are rapidly emerging as flexible platforms for capturing imagery and other data across the sciences. Many colleges and universities are developing courses on UAS-based data acquisition. Fundamentals of Capturing and Processing Drone Imagery and Data is a comprehensive, introductory text on how to use unmanned aircraft systems for data capture and analysis. It provides best practices for planning data capture missions and hands-on learning modules geared toward UAS data collection, processing, and applications.FEATURES Lays out a step-by-step approach to identify relevant tools and methods for UAS data/image acquisition and processing. Provides practical hands-on knowledge with visual interpretation, well-organized and designed for a typical 16-week UAS course offered on college and university campuses. Suitable for all levels of readers and does not require prior knowTable of ContentsPart I: Getting Started with Drone Imagery and Data 1. Introduction to Capturing and Processing Drone Imagery and Data 2. An Introduction to Drone Remote Sensing and Photogrammetry 3. Choosing a Sensor for UAS Imagery Collection 4. Mission Planning for Capturing UAS Imagery 5. Drone Regulations: What You Need to Know before You Fly 6. Structure from Motion (SfM) Workflow for Processing Drone Imagery 7. Aerial Cinematography with UAS Part II: Hands-On Applications Using Drone Imagery and Data 8. Planning Unoccupied Aircraft Systems (UAS) Missions 9. Aligning and Stitching Drone-Captured Images 10. Counting Wildlife from Drone-Captured Imagery Using Visual and Semi-Automated Techniques 11. Terrain and Surface Modeling of Vegetation Height Using Simple Linear Regression 12. Assessing the Accuracy of Digital Surface Models of an Earthen Dam Derived from SfM Techniques 13. Estimating Forage Mass from Unmanned Aircraft Systems in Rangelands 14. Applications of UAS-Derived Terrain Data for Hydrology and Flood Hazard Modeling 15. Comparing UAS and Terrestrial Laser Scanning Methods for Change Detection in Coastal Landscapes 16. Digital Preservation of Historical Heritage Using 3D Models and Augmented Reality 17. Identifying Burial Mounds and Enclosures Using RGB and Multispectral Indices Derived from UAS Imagery 18. Detecting Scales of Drone-Based Atmospheric Measurements Using Semivariograms 19. Assessing the Greenhouse Gas Carbon Dioxide in the Atmospheric Boundary Layer

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Book SynopsisComputer Vision and Image Analysis, focuses on techniques and methods for image analysis and their use in the development of computer vison applications. The field is advancing at an ever increasing pace, with applications ranging from medical diagnostics to space exploration. The diversity of applications is one of the driving forces that make it such an exciting field to be involved in for the 21st century. This book presents a unique engineering approach to the practice of computer vision and image analysis, which starts by presenting a global model to help gain an understanding of the overall process, followed by a breakdown and explanation of each individual topic. Topics are presented as they become necessary for understanding the practical imaging model under study, which provides the reader with the motivation to learn about and use the tools and methods being explored.The book includes chapters on image systems and software, image analysis, eTable of Contents1. Digital Image Processing and Analysis. 2. Computer Vision Development Tools. 3. Image Analysis and Computer Vision. 4. Edge, Line and Shape Detection. 5. Segmentation. 6 Feature Extraction and Analysis. 7. Pattern Classification. 8. Application Development Tools

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Book SynopsisHybrid Computational Intelligent Systems Modeling, Simulation and Optimization unearths the latest advances in evolving hybrid intelligent modeling and simulation of human-centric data-intensive applications optimized for real-time use, thereby enabling researchers to come up with novel breakthroughs in this ever-growing field.Salient features include the fundamentals of modeling and simulation with recourse to knowledge-based simulation, interaction paradigms, and human factors, along with the enhancement of the existing state of art in a high-performance computing setup. In addition, this book presents optimization strategies to evolve robust and failsafe intelligent system modeling and simulation.The volume also highlights novel applications for different engineering problems including signal and data processing, speech, image, sensor data processing, innovative intelligent systems, and swarm intelligent manufacturing systems.Features:A Table of ContentsChapter 1 Creating ratings of agricultural universities based on their digital footprint Chapter 2 Mechatronic Complex’s Fuzzy System for Fixating Moving Objects Chapter 3 Quad Sensor-based Soil-Moisture Prediction using Machine Learning Chapter 4 Stability Analysis for a Diffusive Ratio-dependent Predator-prey Model involving two Delays Chapter 5 Analysis and Prediction of Physical Fitness Test Data of College Students Based on Grey Model Chapter 6 Analysis and Research on Book Borrowing Tendency Based on Apriori Algorithm Chapter 7 Performance Evaluation of Cargo Inspection Systems with the Function of Materials Recognition Chapter 8 Automated Medical Report Generation on Chest X-Ray Images using Co-Attention mechanism Chapter 9 An Energy Efficient Secured Arduino based Home Automation using Android Interface Chapter 10 A Multithreaded Android App to Notify Available `CoWIN’ Vaccination Slots to Multiple Recipients Chapter 11 Binary MMBAIS for Feature Selection Problem Chapter 12 Audio to Indian Sign Language Interpreter (AISLI) using Machine Translation and NLP Techniques Chapter 13 Fragile Medical Image Watermarking using Auto-generated Adaptive Key based Encryption Chapter 14 Designing of a Solution Model for Global Warming and Climate Change using Machine Learning and Data Engineering Techniques Chapter 15 Human Age Estimation using sit-to-stand exercise Data-driven Decision Making by Neural Network Chapter 16 Feature Based Suicide Ideation Detection from Twitter Data Using Machine Learning Techniques Chapter 17 Analyzing the role of Indian Media during the second wave of COVID using Topic Modeling Chapter 18 Hardware Efficient FIR Filter Design using Fast Converging Flower Pollination Algorithm - A Case Study of denoising PCG Signal Chapter 19 Voice Recognition System Using Deep Learning Chapter 20 Modified Harris Hawk Optimization Algorithm for Multi-level Image Thresholding Chapter 21 An automatic probabilistic framework for detection and segmentation of tumor in brain MRI images Chapter 22 Comparative Study of Generative Adversarial Networks for Sensor Data Generation based Remaining Useful Life Classification Chapter 23 Towards a Framework for Implementation of Quantum-Inspired Evolutionary Algorithm on Noisy Intermediate Scale Quantum Devices (IBMQ) for Solving Knapsack Problems

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Book SynopsisThis Lab Manual is a companion to the textbook Remote Sensing and Digital Image Processing with R. It covers examples of natural resource data analysis applications including numerous, practical problem-solving exercises, and case studies that use the free and open-source platform R. The intuitive, structural workflow helps students better understand a scientific approach to each case study in the book and learn how to replicate, transplant, and expand the workflow for further exploration with new data, models, and areas of interest. Features Aims to expand theoretical approaches of remote sensing and digital image processing through multidisciplinary applications using R and R packages. Engages students in learning theory through hands-on real-life projects. All chapters are structured with solved exercises and homework and encourage readers to understand the potential and the limitations of the environments. CoversTable of Contents1. Principles of R Language in Remote Sensing and Digital Image Processing 2. Introduction to Remote Sensing and Digital Image Processing with R 3. Remote Sensing of Electromagnetic Radiation 4. Remote Sensing Sensors and Satellite Systems 5. Remote Sensing of Vegetation 6. Remote Sensing of Water 7. Remote Sensing of Soils, Rocks, and Geomorphology 8. Remote Sensing of the Atmosphere 9. Scientific Applications of Remote Sensing and Digital Image Processing for Project Design 10. Visual Interpretation and Enhancement of Remote Sensing Images 11. Unsupervised Classification of Remote Sensing Images 12. Supervised Classification of Remote Sensing Images 13. Uncertainty and Accuracy Analysis in Remote Sensing and Digital Image Processing 14. Scientific Applications of Remote Sensing and Digital Image Processing to Elaborate Articles

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Book SynopsisThis book presents essential principles, technical information, and expert insights on multimedia security technology. Illustrating the need for improved content security as the Internet and digital multimedia applications rapidly evolve, it presents a wealth of everyday protection application examples in fields including . Giving readers an in-depth introduction to different aspects of information security mechanisms and methods, it also serves as an instructional tool on the fundamental theoretical framework required for the development of advanced techniques. Table of ContentsPart 1: Information Security Basics. 1. Encryption Techniques. 2. Key Distribution Techniques. 3. Authentication and Integrity Techniques. Part 2: Image and Video Security Techniques. 4. Image and Video Encryption Techniques. 5. Image and Video Watermarking Techniques. 6. Image and Video Steganography Techniques. 7. Image and Video Forensics. Part 3: Applications. 8. Applications in Medical Imaging. 9. Applications in Industrial Automation. 10. Applications in Sports and Entertainment. 11. Applications in Privacy Preservation. 12. Applications in Copyrights and Ownership Rights of Video. 13. Applications in Cloud-Based Applications.

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Book Synopsis''Phase-only Fresnel holograms,'' which can be displayed on a single SLM without the need for lenses or complicated optical accessories, substantially simplifies 3-D holographic display systems. Exploring essential concepts, theories, and formulations of these phase-only Fresnel holograms, this book provides comprehensive coverage of modern methods for generating such holograms, which pave the way for commercial products such as compact holographic projectors, heads-up displays, and data security enhancement. Relevant MATLAB codes are provided for readers to implement and evaluate the theories and formulations of different methods, and can be used as a quick start framework for further research and development. This is a crucial and up-to-date treatment of phase-only Fresnel holograms for students and researchers in electrical and electronic engineering, computer science/engineering, applied physics, information technology, and multimedia technology, as well as engineers and scientistTrade Review'MATLAB programs, scattered throughout the book, might be the starting point for further research and be used as an educational tool (there are exercises at the end of each chapter). References are adequate, useful and up-to-date, while the index improves readability. The book is specialized, and I recommend it to those who actively use SLMs for holographic manipulation of light, but it can be useful to a more general community dealing with digital holography.' Dejan Pantelić, Optics & Photonics NewsTable of ContentsPreface; 1. Introduction to Digital Holography; 2. Fast Methods for Computer Generated Holography; 3. Generation of Phase-Only Fresnel Hologram; 4. Conversion of Complex-Valued Holograms to Phase-Only Holograms; 5. Applications of Phase-Only Hologram in Display, Holographic Encryption and Steganography.

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Book SynopsisThis text provides an exceptional introduction to the multidisciplinary field of mobile robotics using hands-on examples in ROS 2 enabling students to explore concepts either in a simulation or using their own robot hardware. The new edition includes coverage of HRI, robot ethics, and AI techniques for end-to-end robot control.Trade Review'This book is an indispensable tool for any - both pre-university and university - course on mobile robotics. In relation to the first edition, this current one has been sufficiently updated. I recommend this book to researchers - particularly those who study localization or mapping - and doctoral students who are interested in investigating the latest approaches and techniques in the mobile robotics field.' Ramon Gonzalez Sanchez, Computing Reviews'… a great resource for an intermediate or advanced course on mobile robotics.' R. S. Stansbury, ChoiceTable of ContentsAcknowledgments; Preface; 1. Overview and motivation; 2. Fundamental problems; Part I. Locomotion and Perception: 3. Mobile robot hardware; 4. Non-visual sensors and algorithms; 5. Visual sensors and algorithms; Part II. Representation and Planning: 6. Deep learning for robots; 7. Planning in, representing and reasoning about space; 8. System control; 9. Pose maintenance and localization; 10. Mapping and related tasks; 11. Robot collectives; 12. Human-robot interaction; 13. Robot ethics; 14. Robots in practice; 15. The future of mobile robotics; Appendix A. Fictional robots; Appendix B. Probability and statistics; Appendix C. Linear systems, matrices and filtering; Appendix D. Markov models; Bibliography; Index.

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Book SynopsisData registration refers to a series of techniques for matching or bringing similar objects or datasets together into alignment.Table of ContentsPreface xi Acknowledgements xiii 1 Introduction 1 1.1 The History of Image Registration 1 1.2 Definition of Registration 2 1.3 What is Motion Estimation 3 1.4 Video Quality Assessment 5 1.5 Applications 5 1.5.1 Video Processing 5 1.5.2 Medical Applications 7 1.5.3 Security Applications 8 1.5.4 Military and Satellite Applications 10 1.5.5 Reconstruction Applications 11 1.6 Organization of the Book 12 References 13 2 Registration for Video Coding 15 2.1 Introduction 15 2.2 Motion Estimation Technique 16 2.2.1 Block-Based Motion Estimation Techniques 16 2.3 Registration and Standards for Video Coding 30 2.3.1 H.264 30 2.3.2 H.265 34 2.4 Evaluation Criteria 35 2.4.1 Dataset 35 2.4.2 Motion-Compensated Prediction Error (MCPE) in dB 38 2.4.3 Entropy in bpp 39 2.4.4 Angular Error in Degrees 40 2.5 Objective Quality Assessment 41 2.5.1 Full-Reference Quality Assessment 41 2.5.2 No-Reference and Reduced-Reference Quality Metrics 44 2.5.3 Temporal Masking in Video Quality Assessment 46 2.6 Conclusion 48 2.7 Exercises 49 References 49 3 Registration for Motion Estimation and Object Tracking 53 3.1 Introduction 53 3.1.1 Mathematical Notation 54 3.2 Optical Flow 55 3.2.1 Horn–Schunk Method 56 3.2.2 Lukas–Kanade Method 56 3.2.3 Applications of Optical Flow for Motion Estimation 57 3.3 Efficient Discriminative Features for Motion Estimation 61 3.3.1 Invariant Features 62 3.3.2 Optimization Stage 64 3.4 Object Tracking 64 3.4.1 KLT Tracking 64 3.4.2 Motion Filtering 66 3.4.3 Multiple Object Tracking 67 3.5 Evaluating Motion Estimation and Tracking 68 3.5.1 Metrics for Motion Detection 68 3.5.2 Metrics for Motion Tracking 69 3.5.3 Metrics for Efficiency 70 3.5.4 Datasets 70 3.6 Conclusion 70 3.7 Exercise 75 References 75 4 Face Alignment and Recognition Using Registration 79 4.1 Introduction 79 4.2 Unsupervised Alignment Methods 80 4.2.1 Natural Features: Gradient Features 81 4.2.2 Dense Grids: Non-rigid Non-affine Transformations 81 4.3 Supervised Alignment Methods 83 4.3.1 Generative Models 84 4.3.2 Discriminative Approaches 86 4.4 3D Alignment 88 4.4.1 Hausdorff Distance Matching 88 4.4.2 Iterative Closest Point (ICP) 89 4.4.3 Multistage Alignment 89 4.5 Metrics for Evaluation 90 4.5.1 Evaluating Face Recognition 90 4.5.2 Evaluating Face Alignment 90 4.5.3 Testing Protocols and Benchmarks 91 4.5.4 Datasets 92 4.6 Conclusion 94 4.7 Exercise 94 References 94 5 Remote Sensing Image Registration in the Frequency Domain 97 5.1 Introduction 97 5.2 Challenges in Remote Sensing Imaging 100 5.3 Satellite Image Registration in the Fourier Domain 102 5.3.1 Translation Estimation Using Correlation 102 5.4 Correlation Methods 103 5.5 Subpixel Shift Estimation in the Fourier Domain 107 5.6 FFT-Based Scale-Invariant Image Registration 111 5.7 Motion Estimation in the Frequency Domain for Remote Sensing Image Sequences 115 5.7.1 Quad-Tree Phase Correlation 116 5.7.2 Shape Adaptive Motion Estimation in the Frequency Domain 119 5.7.3 Optical Flow in the Fourier Domain 120 5.8 Evaluation Process and Related Datasets 122 5.8.1 Remote Sensing Image Datasets 123 5.9 Conclusion 123 5.10 Exercise – Practice 124 References 124 6 Structure from Motion 129 6.1 Introduction 129 6.2 Pinhole Model 131 6.3 Camera Calibration 133 6.4 Correspondence Problem 135 6.5 Epipolar Geometry 136 6.6 Projection Matrix Recovery 140 6.6.1 Triangulation 141 6.7 Feature Detection and Registration 141 6.7.1 Auto-correlation 143 6.7.2 Harris Detector 143 6.7.3 SIFT Feature Detector 146 6.8 Reconstruction of 3D Structure and Motion 148 6.8.1 Simultaneous Localization and Mapping 149 6.8.2 Registration for Panoramic View 150 6.9 Metrics and Datasets 152 6.9.1 Datasets for Performance Evaluation 154 6.10 Conclusion 155 6.11 Exercise – Practice 155 References 155 7 Medical Image Registration Measures 162 7.1 Introduction 162 7.2 Feature-Based Registration 163 7.2.1 Generalized Iterative Closest Point Algorithm 164 7.2.2 Hierarchical Maximization 165 7.3 Intensity-Based Registration 165 7.3.1 Voxels as Features 166 7.3.2 Special Case: Spatially Determined Correspondences 168 7.3.3 Intensity Difference Measures 169 7.3.4 Correlation Coefficient 170 7.3.5 Pseudo-likelihood Measures 171 7.3.6 General Implementation Using Joint Histograms 181 7.4 Transformation Spaces and Optimization 184 7.4.1 Rigid Transformations 185 7.4.2 Similarity Transformations 186 7.4.3 Affine Transformations 186 7.4.4 Projective Transformations 187 7.4.5 Polyaffine Transformations 187 7.4.6 Free-Form Transformations: ‘Small Deformation’ Model 188 7.4.7 Free-Form Transformations: ‘Large Deformation’ Models 189 7.5 Conclusion 193 7.6 Exercise 193 7.6.1 Implementation Guidelines 195 References 196 8 Video Restoration Using Motion Information 201 8.1 Introduction 201 8.2 History of Video and Film Restoration 203 8.3 Restoration of Video Noise and Grain 206 8.4 Restoration Algorithms for Video Noise 208 8.5 Instability Correction Using Registration 211 8.6 Estimating and Removing Flickering 214 8.7 Dirt Removal in Video Sequences 217 8.8 Metrics in Video Restoration 221 8.9 Conclusions 225 8.10 Exercise – Practice 225 References 225 Index 229

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Book SynopsisComputer Vision and Imaging in Intelligent Transportation Systems Robert P.Table of ContentsList of Contributors xiii Preface xvii Acknowledgments xxi About the Companion Website xxiii 1 Introduction 1 Raja Bala and Robert P. Loce 1.1 Law Enforcement and Security 1 1.2 Efficiency 4 1.3 Driver Safety and Comfort 5 1.4 A Computer Vision Framework for Transportation Applications 7 1.4.1 Image and Video Capture 8 1.4.2 Data Preprocessing 8 1.4.3 Feature Extraction 9 1.4.4 Inference Engine 10 1.4.5 Data Presentation and Feedback 11 Part I Imaging from the Roadway Infrastructure 15 2 Automated License Plate Recognition 17 Aaron Burry and Vladimir Kozitsky 2.1 Introduction 17 2.2 Core ALPR Technologies 18 2.2.1 License Plate Localization 19 2.2.2 Character Segmentation 24 2.2.3 Character Recognition 28 2.2.4 State Identification 38 3 Vehicle Classification 47 Shashank Deshpande, Wiktor Muron and Yang Cai 3.1 Introduction 47 3.2 Overview of the Algorithms 48 3.3 Existing AVC Methods 48 3.4 LiDAR Imaging-Based 49 3.4.1 LiDAR Sensors 49 3.4.2 Fusion of LiDAR and Vision Sensors 50 3.5 Thermal Imaging-Based 53 3.5.1 Thermal Signatures 53 3.5.2 Intensity Shape-Based 56 3.6 Shape- and Profile-Based 58 3.6.1 Silhouette Measurements 60 3.6.2 Edge-Based Classification 65 3.6.3 Histogram of Oriented Gradients 67 3.6.4 Haar Features 68 3.6.5 Principal Component Analysis 69 3.7 Intrinsic Proportion Model 72 3.8 3D Model-Based Classification 74 3.9 SIFT-Based Classification 74 3.10 Summary 75 4 Detection of Passenger Compartment Violations 81 Orhan Bulan, Beilei Xu, Robert P. Loce and Peter Paul 4.1 Introduction 81 4.2 Sensing within the Passenger Compartment 82 4.2.1 Seat Belt Usage Detection 82 4.2.2 Cell Phone Usage Detection 83 4.2.3 Occupancy Detection 83 4.3 Roadside Imaging 84 4.3.1 Image Acquisition Setup 84 4.3.2 Image Classification Methods 85 4.3.3 Detection-Based Methods 94 5 Detection of Moving Violations 101 Wencheng Wu, Orhan Bulan, Edgar A. Bernal and Robert P. Loce 5.1 Introduction 101 5.2 Detection of Speed Violations 101 5.2.1 Speed Estimation from Monocular Cameras 102 5.2.2 Speed Estimation from Stereo Cameras 108 5.2.3 Discussion 115 5.3 Stop Violations 115 5.3.1 Red Light Cameras 115 5.4 Other Violations 125 5.4.1 Wrong-Way Driver Detection 125 5.4.2 Crossing Solid Lines 126 6 Traffic Flow Analysis 131 Rodrigo Fernandez, Muhammad Haroon Yousaf, Timothy J. Ellis, Zezhi Chen and Sergio A. Velastin 6.1 What is Traffic Flow Analysis? 131 6.1.1 Traffic Conflicts and Traffic Analysis 131 6.1.2 Time Observation 132 6.1.3 Space Observation 133 6.1.4 The Fundamental Equation 133 6.1.5 The Fundamental Diagram 133 6.1.6 Measuring Traffic Variables 134 6.1.7 Road Counts 135 6.1.8 Junction Counts 135 6.1.9 Passenger Counts 136 6.1.10 Pedestrian Counts 136 6.1.11 Speed Measurement 136 6.2 The Use of Video Analysis in Intelligent Transportation Systems 137 6.2.1 Introduction 137 6.2.2 General Framework for Traffic Flow Analysis 137 6.2.3 Application Domains 143 6.3 Measuring Traffic Flow from Roadside CCTV Video 144 6.3.1 Video Analysis Framework 144 6.3.2 Vehicle Detection 146 6.3.3 Background Model 146 6.3.4 Counting Vehicles 149 6.3.5 Tracking 150 6.3.6 Camera Calibration 150 6.3.7 Feature Extraction and Vehicle Classification 152 6.3.8 Lane Detection 153 6.3.9 Results 155 6.4 Some Challenges 156 7 Intersection Monitoring Using Computer Vision Techniques for Capacity, Delay, and Safety Analysis 163 Brendan Tran Morris and Mohammad Shokrolah Shirazi 7.1 Vision-Based Intersection Analysis: Capacity, Delay, and Safety 163 7.1.1 Intersection Monitoring 163 7.1.2 Computer Vision Application 164 7.2 System Overview 165 7.2.1 Tracking Road Users 166 7.2.2 Camera Calibration 169 7.3 Count Analysis 171 7.3.1 Vehicular Counts 171 7.3.2 Nonvehicular Counts 173 7.4 Queue Length Estimation 173 7.4.1 Detection-Based Methods 174 7.4.2 Tracking-Based Methods 175 7.5 Safety Analysis 177 7.5.1 Behaviors 178 7.5.2 Accidents 182 7.5.3 Conflicts 185 7.6 Challenging Problems and Perspectives 187 7.6.1 Robust Detection and Tracking 187 7.6.2 Validity of Prediction Models for Conflict and Collisions 188 7.6.3 Cooperating Sensing Modalities 189 7.6.4 Networked Traffic Monitoring Systems 189 7.7 Conclusion 189 8 Video-Based Parking Management 195 Oliver Sidla and Yuriy Lipetski 8.1 Introduction 195 8.2 Overview of Parking Sensors 197 8.3 Introduction to Vehicle Occupancy Detection Methods 200 8.4 Monocular Vehicle Detection 200 8.4.1 Advantages of Simple 2D Vehicle Detection 200 8.4.2 Background Model–Based Approaches 200 8.4.3 Vehicle Detection Using Local Feature Descriptors 202 8.4.4 Appearance-Based Vehicle Detection 203 8.4.5 Histograms of Oriented Gradients 204 8.4.6 LBP Features and LBP Histograms 207 8.4.7 Combining Detectors into Cascades and Complex Descriptors 208 8.4.8 Case Study: Parking Space Monitoring Using a Combined Feature Detector 208 8.4.9 Detection Using Artificial Neural Networks 211 8.5 Introduction to Vehicle Detection with 3D Methods 213 8.6 Stereo Vision Methods 215 8.6.1 Introduction to Stereo Methods 215 8.6.2 Limits on the Accuracy of Stereo Reconstruction 216 8.6.3 Computing the Stereo Correspondence 217 8.6.4 Simple Stereo for Volume Occupation Measurement 218 8.6.5 A Practical System for Parking Space Monitoring Using a Stereo System 218 8.6.6 Detection Methods Using Sparse 3D Reconstruction 220 9 Video Anomaly Detection 227 Raja Bala and Vishal Monga 9.1 Introduction 227 9.2 Event Encoding 228 9.2.1 Trajectory Descriptors 229 9.2.2 Spatiotemporal Descriptors 231 9.3 Anomaly Detection Models 233 9.3.1 Classification Methods 233 9.3.2 Hidden Markov Models 234 9.3.3 Contextual Methods 234 9.4 Sparse Representation Methods for Robust Video Anomaly Detection 236 9.4.1 Structured Anomaly Detection 237 9.4.2 Unstructured Video Anomaly Detection 243 9.4.3 Experimental Setup and Results 245 9.5 Conclusion and Future Research 253 Part II Imaging from and within the Vehicle 257 10 Pedestrian Detection 259 Shashank Deshpande and Yang Cai 10.1 Introduction 259 10.2 Overview of the Algorithms 259 10.3 Thermal Imaging 260 10.4 Background Subtraction Methods 261 10.4.1 Frame Subtraction 261 10.4.2 Approximate Median 262 10.4.3 Gaussian Mixture Model 263 10.5 Polar Coordinate Profile 263 10.6 Image-Based Features 265 10.6.1 Histogram of Oriented Gradients 265 10.6.2 Deformable Parts Model 266 10.6.3 LiDAR and Camera Fusion–Based Detection 266 10.7 LiDAR Features 268 10.7.1 Preprocessing Module 268 10.7.2 Feature Extraction Module 268 10.7.3 Fusion Module 268 10.7.4 LIPD Dataset 270 10.7.5 Overview of the Algorithm 270 10.7.6 LiDAR Module 272 10.7.7 Vision Module 275 10.7.8 Results and Discussion 276 10.7.8.1 LiDAR Module 276 10.7.8.2 Vision Module 276 10.8 Summary 280 11 Lane Detection and Tracking Problems in Lane Departure Warning Systems 283 Gianni Cario, Alessandro Casavola and Marco Lupia 11.1 Introduction 283 11.2 LD: Algorithms for a Single Frame 285 11.2.1 Image Preprocessing 285 11.2.2 Edge Extraction 287 11.2.3 Stripe Identification 291 11.2.4 Line Fitting 294 11.3 LT Algorithms 297 11.3.1 Recursive Filters on Subsequent N frames 298 11.3.2 Kalman Filter 298 11.4 Implementation of an LD and LT Algorithm 299 11.4.1 Simulations 300 11.4.2 Test Driving Scenario 300 11.4.3 Driving Scenario: Lane Departures at Increasing Longitudinal Speed 300 11.4.4 The Proposed Algorithm 302 11.4.5 Conclusions 303 12 Vision-Based Integrated Techniques for Collision Avoidance Systems 305 Ravi Satzoda and Mohan Trivedi 12.1 Introduction 305 12.2 Related Work 307 12.3 Context Definition for Integrated Approach 307 12.4 ELVIS: Proposed Integrated Approach 308 12.4.1 Vehicle Detection Using Lane Information 309 12.4.2 Improving Lane Detection using On-Road Vehicle Information 312 12.5 Performance Evaluation 313 12.5.1 Vehicle Detection in ELVIS 313 12.5.2 Lane Detection in ELVIS 316 12.6 Concluding Remarks 319 13 Driver Monitoring 321 Raja Bala and Edgar A. Bernal 13.1 Introduction 321 13.2 Video Acquisition 322 13.3 Face Detection and Alignment 323 13.4 Eye Detection and Analysis 325 13.5 Head Pose and Gaze Estimation 326 13.5.1 Head Pose Estimation 326 13.5.2 Gaze Estimation 328 13.6 Facial Expression Analysis 332 13.7 Multimodal Sensing and Fusion 334 13.8 Conclusions and Future Directions 336 14 Traffic Sign Detection and Recognition 343 Hasan Fleyeh 14.1 Introduction 343 14.2 Traffic Signs 344 14.2.1 The European Road and Traffic Signs 344 14.2.2 The American Road and Traffic Signs 347 14.3 Traffic Sign Recognition 347 14.4 Traffic Sign Recognition Applications 348 14.5 Potential Challenges 349 14.6 Traffic Sign Recognition System Design 349 14.6.1 Traffic Signs Datasets 352 14.6.2 Colour Segmentation 354 14.6.3 Traffic Sign's Rim Analysis 359 14.6.4 Pictogram Extraction 364 14.6.5 Pictogram Classification Using Features 365 14.7 Working Systems 369 15 Road Condition Monitoring 375 Matti Kutila, Pasi Pyykonen, Johan Casselgren and Patrik Jonsson 15.1 Introduction 375 15.2 Measurement Principles 376 15.3 Sensor Solutions 377 15.3.1 Camera-Based Friction Estimation Systems 377 15.3.2 Pavement Sensors 379 15.3.3 Spectroscopy 380 15.3.4 Roadside Fog Sensing 382 15.3.5 In-Vehicle Sensors 383 15.4 Classification and Sensor Fusion 386 15.5 Field Studies 390 15.6 Cooperative Road Weather Services 394 15.7 Discussion and Future Work 395 Index 399

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Book SynopsisTable of ContentsIntroduction 1 About This Book 1 Conventions Used in This Book 2 Icons Used in This Book 3 How to Use This Book 3 Part 1: Getting Started with Photoshop CC 5 Chapter 1: An Overview of Photoshop 7 Exploring Adobe Photoshop 7 What Photoshop is designed to do 8 Other things you can do with Photoshop 9 Viewing Photoshop’s Parts and Processes 10 Reviewing basic computer operations 10 Photoshop’s incredible selective Undo 12 Installing Photoshop: Need to know 14 Chapter 2: Knowing Just Enough about Digital Images 17 What Exactly is a Digital Image? 18 The True Nature of Pixels 18 How Many Pixels Can Dance on the Head of a Pin? 21 Resolution revelations 21 Resolving image resolution 22 File Formats: Which Do You Need? 30 Formats for digital photos 31 Formats for web graphics 33 Formats for commercial printing 34 Formats for PowerPoint and Word 36 Chapter 3: Taking the Chef’s Tour of Your Photoshop Kitchen 37 Food for Thought: How Things Work 38 Ordering from the menus 39 Your platter full of panels 40 The tools of your trade 42 Get Cookin’ with Customization 44 Clearing the table: Custom workspaces 44 Spoons can’t chop: Creating tool presets 47 Season to Taste: The Photoshop Settings 48 Standing orders: Setting the Preferences 48 Ensuring consistency: Color Settings 55 When Good Programs Go Bad: Fixing Photoshop 57 Chapter 4: From Pics to Prints: Photoshop for Beginners 59 Bringing Images into Photoshop 59 Downloading from your digital camera 60 Scanning prints 61 Keeping Your Images Organized 66 Creating a folder structure 66 Using Adobe Bridge 67 Renaming image files easily 69 Printing Your Images 71 Cropping to a specific aspect ratio 71 Remembering resolution 73 Controlling color using File ➪ Print 74 Considering color management solutions 75 Printing alternatives 76 Sharing Your Images 77 Emailing and AirDropping your images 78 Creating PDFs and websites 78 Part 2: Easy Enhancements for Digital Images 79 Chapter 5: Making Tonality and Color Look Natural 81 Adjusting Tonality to Make Your Images Pop 82 Histograms Simplified 82 Using Photoshop’s Auto Corrections 84 Levels and Curves and You 85 Level-headed you! 86 Tonal corrections with the eyedroppers 89 Adjusting your curves without dieting 90 Grabbing Even More Control 92 Using Shadows/Highlights 93 Changing exposure after the fact 96 Using Photoshop’s toning tools 96 What is Color in Photoshop? 97 Which color mode should you choose? 98 Does a color model make a difference? 101 Why should you worry about color depth? 102 Making Color Adjustments in Photoshop 104 Choosing color adjustment commands 106 Manual corrections in individual channels 117 The People Factor: Flesh Tone Formulas 118 Chapter 6: The Adobe Camera Raw Plug-In 121 Understanding the Raw Facts 121 What’s the big deal about Raw? 123 Working in Raw 124 The Camera Raw Interface 126 Camera Raw’s Tools and buttons 126 The histogram 132 The preview area 132 Workflow Options and presets 133 Making Adjustments in Camera Raw’s Edit Panel 134 The Basic section 134 The Curve section 137 The Detail section 137 The Color Mixer section 138 The Color Grading section 138 The Optics and Geometry sections 140 The Effects section 141 The Calibration section 141 The Camera Raw Cancel, Done, and Open buttons 142 Chapter 7: Fine-Tuning Your Fixes 143 What is a Selection? 144 Feathering and Anti-aliasing 146 Making Your Selections with Tools 148 Marquee selection tools 148 Lasso selection tools 152 The Object Selection tool 153 The Quick Selection tool 153 The Magic Wand tool 154 Select and Mask 155 Your Selection Commands 156 The primary selection commands 157 The Color Range command 158 The Focus Area command 159 The Select ➪ Subject command 160 The Select ➪ Sky command 161 Selection modification commands 161 Transforming the shape of selections 161 Edit in Quick Mask mode 163 The mask-related selection commands 164 Masks: Not Just for Halloween Anymore 164 Saving and loading selections 165 Editing an alpha channel 165 Adding masks to layers and Smart Objects 167 Masking with vector paths 167 Adjustment Layers: Controlling Changes 168 Adding an adjustment layer 168 Limiting your adjustments 170 Chapter 8: Common Problems and Their Cures 173 Making People Prettier 174 Getting the red out digitally 174 The digital fountain of youth 175 Dieting digitally 176 De-glaring glasses 179 Whitening teeth 179 Reducing Noise in Your Images 179 Decreasing digital noise 180 Eliminating luminance noise 181 Fooling Around with Mother Nature 181 Removing the unwanted from photos 181 Eliminating the lean: Fixing perspective 185 Rotating images precisely 187 Adding a beautiful sky 188 Part 3: Creating “Art” in Photoshop 189 Chapter 9: Combining Images 191 Compositing Images: 1 + 1 = 1 192 Understanding layers 192 Why you should use Smart Objects 194 Using the basic blending modes 195 Opacity, transparency, and layer masks 198 Creating clipping groups 199 Making composited elements look natural 200 Making Complex Selections 201 Vanishing Point 204 Creating Panoramas with Photomerge 208 Chapter 10: Precision Edges with Vector Paths 211 Pixels, Paths, and You 212 Easy Vectors: Using Shapes 213 Your basic shape tools 214 The Custom Shape tool 216 More custom shapes — free! 217 Changing the appearance of the shape layer 219 Simulating a multicolor shape layer 220 Using Your Pen Tool to Create Paths 221 Understanding paths 222 Clicking and dragging your way down the path of knowledge 222 A closer look at the Paths panel 226 Customizing Any Path 229 Adding, deleting, and moving anchor points 230 Combining paths 232 Tweaking type for a custom font 233 Chapter 11: Dressing Up Images with Layer Styles 235 What Are Layer Styles? 235 Using the Styles Panel 237 Creating Custom Layer Styles 239 Exploring the Layer Style menu 239 Exploring the Layer Style dialog box 241 Layer effects basics 242 Opacity, fill, and advanced blending 251 Saving Your Layer Styles 254 Adding styles to the Styles panel 254 Preserving your layer styles 255 Chapter 12: Giving Your Images a Text Message 257 Making a Word Worth a Thousand Pixels 258 A type tool for every season, or reason 260 What are all those options? 262 Taking control of your text with panels 266 The panel menus — even more options 269 Working with Styles 271 Putting a picture in your text 272 Creating Paragraphs with Type Containers 274 Selecting alignment or justification 276 Ready, BREAK! Hyphenating your text 277 Shaping Up Your Language with Warp Text and Type on a Path 278 Applying the predefined warps 278 Customizing the course with paths 279 Chapter 13: Painting in Photoshop 283 Discovering Photoshop’s Painting Tools 284 Painting with the Brush tool 286 Adding color with the Pencil tool 289 Removing color with the Eraser tool 289 Working with Panels and Selecting Colors 290 An overview of options 290 Creating and saving custom brush tips 293 Picking a color 294 Fine Art Painting with Specialty Brush Tips and the Mixer Brush 297 Exploring erodible brush tips 297 Introducing airbrush and watercolor tips 297 Mixing things up with the Mixer Brush 298 Filling, Stroking, Dumping, and Blending Colors 300 Deleting and dumping to add color 300 Using gradients 301 Chapter 14: Filters: The Fun Side of Photoshop 305 Smart Filters: Your Creative Insurance Policy 306 The Filters You Really Need 307 Sharpening to focus the eye 308 Unsharp Mask 308 Smart Sharpen 310 Shake Reduction 311 Blurring images and selections 312 The other Blur filters 315 Correcting for the vagaries of lenses 316 Cleaning up with Reduce Noise 320 Getting Creative and Artistic 321 Photo to painting with the Oil Paint filter 321 Working with the Filter Gallery 322 Push, Pull, and Twist with Liquify 325 What Are Neural Filters? 327 The original Neural Filters 328 Neural Filters in public beta testing 329 Proposed Neural Filters 330 Do I Need Those Other Filters? 330 Adding drama with Lighting Effects 331 Maximum and Minimum 331 Bending and bubbling 332 Creating clouds 332 Part 4: Power Photoshop 333 Chapter 15: Streamlining Your Work in Photoshop 335 Ready, Set, Action! 336 Recording your own Actions 337 Working with the Batch command 342 Find It Fast with Discover 344 Creating Contact Sheets and Presentations 344 Creating a PDF presentation 345 Collecting thumbnails in a contact sheet 347 Scanning Multiple Photos in One Pass 349 Sticking to the Script 350 Chapter 16: Working with Video and Animation 353 Importing and Enhancing Video Clips 353 Getting video into Photoshop 354 Adjusting the length of video and audio clips 356 Adding adjustment layers and painting on video layers 357 Transitioning, titling, and adding special effects 358 Transforming video layers 361 Rendering and exporting video 361 Creating Animations in Photoshop 362 Building frame-based animations 362 Creating frame content 363 Tweening to create intermediary frames 365 Specifying frame rate 366 Optimizing and saving your animation 366 Part 5: The Part of Tens 367 Chapter 17: Ten Specialized Features of Photoshop CC 369 Using Smart Object Stack Modes 370 The Mean Stack Mode 372 Working with 3D Artwork 372 Creating 3D objects 373 Adding 3D objects 373 Rendering and saving 3D scenes 374 Measuring, Counting, and Analyzing Pixels 374 Measuring length, area, and more 374 Calculating with Vanishing Point 376 Counting crows or maybe avian flu 376 Viewing Your DICOM Medical Records 377 Ignoring MATLAB 378 Chapter 18: Ten Ways to Integrate Your iPad 379 Using Sidecar to Add an iPad to Your Screen 379 Sidecar System Requirements 380 Arranging Your iPad’s Screen 380 Mirroring the Screens 381 Maximizing the Screen Space 381 Making Use of Photoshop on the iPad 382 Using the Cloud with Photoshop on the iPad and Desktop 383 Using Other Adobe iPad Apps 384 Does the iPad Replace My Wacom Tablet? 384 Setting Wacom Tablet Preferences for Touch Keys and Touch Ring 385 Chapter 19: Ten Things to Know about HDR 387 Understanding HDR 387 Capturing for Merge to HDR Pro 389 Preparing Raw “Exposures” in Camera Raw 390 Working with Merge to HDR Pro 391 Saving 32-Bit HDR Images 394 HDR Toning 394 Painting and the Color Picker in 32-Bit 395 Filters and Adjustments in 32-Bit 396 Selections and Editing in 32-Bit 397 Printing HDR Images 397 Appendix: Photoshop CC’S Blending Modes 399 Index 403

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Book SynopsisMachine Learning Algorithms for Signal and Image Processing Enables readers to understand the fundamental concepts of machine and deep learning techniques with interactive, real-life applications within signal and image processing Machine Learning Algorithms for Signal and Image Processing aids the reader in designing and developing real-world applications using advances in machine learning to aid and enhance speech signal processing, image processing, computer vision, biomedical signal processing, adaptive filtering, and text processing. It includes signal processing techniques applied for pre-processing, feature extraction, source separation, or data decompositions to achieve machine learning tasks. Written by well-qualified authors and contributed to by a team of experts within the field, the work covers a wide range of important topics, such as: Speech recognition, image reconstruction, object classification and detection, and text processing Healthcare monitoring, biomedical systTable of ContentsSection-1 Machine & Deep Learning techniques for Image Processing 1.1 Image Features in Machine Learning 1.2 Image Segmentation and Classification using Deep Learning 1.3 Deep Learning based Synthetic Aperture Radar Image Classification 1.4 Design Perspectives of Multitask Deep Learning Models and Applications 1.5 Image Reconstruction using Deep Learning 1.6 Machine and Deep Learning Techniques for Image Super-Resolution Section-2 Machine & Deep Learning techniques for Text and Speech Processing 2.1 Machine and Deep Learning Techniques for Text and Speech Processing 2.2 Manipuri Handwritten Script Recognition using Machine and Deep Learning 2.3 Comparison of Different Text Extraction Techniques for Complex Color Images 2.4 Smart Text Reader System for Blind Person using Machine and Deep Learning 2.5 Machine Learning Techniques for Deaf People 2.6 Design and Development of Chatbot based on Reinforcement Learning 2.7 DNN based Speech Quality Enhancement and Multi-speaker Separation for Automatic Speech Recognition System 2.8 Design and Development of Real-Time Music Transcription using Digital Signal Processing Section-3 Applications of Signal and Image Processing with Machine & Deep learning techniques 3.1 Role of Machine Learning in Wrist Pulse Analysis 3.2 An Explainable Convolutional Neural Network based Method for Skin Lesion Classification from Dermoscopic Images 3.3 Future of Machine-Learning and Deep-Learning in Health-Care Monitoring System 3.4 Usage of AI & Wearable IoT Devices for Healthcare Data: A Study 3.5 Impact of IoT in Biomedical Applications using Machine and Deep Learning 3.6 Wireless Communications using Machine Learning and Deep Learning 3.7 Applications of Machine Learning and Deep Learning in Smart Agriculture 3.8 Structural Damage Prediction from Earthquakes using Deep Learning 3.9 Machine Learning and Deep Learning Techniques in Social Sciences 3.1O Green Energy using Machine and Deep Learning 3.11 Light Deep CNN Approach for Multi-Label Pathology Classification using Frontal Chest X-Ray Index

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Book SynopsisDifferently oriented specialists and students involved in image processing and analysis need to have a firm grasp of concepts and methods used in this now widely utilized area. This book aims at being a single-source reference providing such foundations in the form of theoretical yet clear and easy to follow explanations of underlying generic concepts.Medical Image Processing, Reconstruction and Analysis Concepts and Methods explains the general principles and methods of image processing and analysis, focusing namely on applications used in medical imaging. The content of this book is divided into three parts: Part I Images as Multidimensional Signals provides the introduction to basic image processing theory, explaining it for both analogue and digital image representations. Part II Imaging Systems as Data Sources offers a non-traditional view on imaging modalities, explaining their prTable of ContentsPART I Images as Multidimensional Signals Chapter 1 Analogue (Continuous-Space) Image Representation Chapter 2 Digital Image Representation PART II Imaging Systems as Data Sources Chapter 3 Planar X-Ray Imaging Chapter 5 Magnetic Resonance Imaging Chapter 6 Nuclear Imaging Chapter 7 Ultrasonography Chapter 8 Other Modalities PART III Image Processing and Analysis Chapter 9 Reconstructing Tomographic Images Chapter 10 Image Fusion Chapter 11 Image Enhancement Chapter 12 Image Restoration Chapter 13 Lower-Level Image Analysis Chapter 14 Selected Higher-Level Image Analysis Methods Chapter 15 Medical Image Processing Environment

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Book SynopsisMathematical modelling is an important part of nuclear medicine. Therefore, several chapters of this book have been dedicated towards describing this topic. In these chapters, an emphasis has been put on describing the mathematical modelling of the radiation transport of photons and electrons, as well as on the transportation of radiopharmaceuticals between different organs and compartments. It also includes computer models of patient dosimetry. Two chapters of this book are devoted towards introducing the concept of biostatistics and radiobiology. These chapters are followed by chapters detailing dosimetry procedures commonly used in the context of diagnostic imaging, as well as patient-specific dosimetry for radiotherapy treatments. For safety reasons, many of the methods used in nuclear medicine and molecular imaging are tightly regulated. Therefore, this volume also highlights the basic principles for radiation protection. It discusses the process of how guidelines and reTable of ContentsContentsPreface...............................................................................................................................viiEditor..................................................................................................................................ixContributors.......................................................................................................................xiChapter 1 Introduction to Biostatistics..........................................................................1Johan Gustafsson and Markus NilssonChapter 2 Radiobiology....................................................................................................17Lidia Strigari and Marta CremonesiChapter 3 Diagnostic Dosimetry.............................................................................................33Lennart Johansson† and Martin AnderssonChapter 4 Time- activity Curves: Data, Models, Curve Fitting, and Model Selection..........................69Gerhard GlattingChapter 5 Tracer Kinetic Modelling and Its Use in PET Quantification..............................................83Mark Lubberink and Michel KooleChapter 6 Principles of Radiological Protection in Healthcare..........................................................101Soren MattssonChapter 7 Controversies in Nuclear Medicine Dosimetry..................................................................115Michael G. StabinChapter 8 Monte Carlo Simulation of Photon and Electron Transport in Matter..............................123Jose M. Fernandez-​VareaChapter 9 Patient Models for Dosimetry Applications..........................................................141Michael G. StabinChapter 10 Patient- specific Dosimetry Calculations.............................................................155Manuel Bardies, Naomi Clayton, Gunjan Kayal, and Alex Vergara GilChapter 11 Whole- body Dosimetry..................................................169Jonathan GearChapter 12 Personalized Dosimetry in Radioembolization........................................................................................183Remco Bastiaannet and Hugo W.A.M. de JongChapter 13 Thyroid Imaging and Dosimetry..........................................................................207Michael Lassmann and Heribert HanscheidChapter 14 Bone Marrow Dosimetry........................................................................................223Cecilia HindorfChapter 15 Cellular and Multicellular Dosimetry...................................................................235Roger W. HowellChapter 16 Alpha- particle Dosimetry................................................................267Stig PalmChapter 17 Staff Radiation Protection........................................................................275Lena JonssonChapter 18 IAEA Support to Nuclear Medicine...........................................................293Gian Luca Poli

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Book SynopsisThe Essential Guide to Flash Games is a unique tool for Flash game developers.Table of Contents The Second Game Theory Creating an AS3 Game Framework Creating Super Click Laying the Groundwork for Flak Cannon Building the Flak Cannon Game Loop Laying the Groundwork for No Tanks! Creating the Full No Tanks! Game Creating the Color Drop Casual Puzzle Game Creating the Dice Battle Puzzle Game Blit Scrolling in a Tile-Based World Creating an Optimized Post-Retro Game Creating a Viral Game: Tunnel Panic

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Book SynopsisBeginning 3D Game Development with Unity 4 is perfect for those who would like to come to grips with programming Unity. You may be an artist who has learned 3D tools such as 3ds Max, Maya, or Cinema 4D, or you may come from 2D tools such as Photoshop and Illustrator. On the other hand, you may just want to familiarize yourself with programming games and the latest ideas in game production. This book introduces key game production concepts in an artist-friendly way, and rapidly teaches the basic scripting skills you''ll need with Unity. It goes on to show how you, as an independent game artist, can create interactive games, ideal in scope for today''s casual and mobile markets, while also giving you a firm foundation in game logic and design. The first part of the book explains the logic involved in game interaction, and soon has you creating game assets through simple examples that you can build upon and gradually expand. In the second part, yoTable of Contents 01. Introduction to Game Development 02. Unity UI basics 03. Introduction to Scripting 04. Terrain Generation and Environment 05. Exploring Navigation 06. Cursor Control and Interaction 07. Importing Assets 08. Action Objects 09. Managing State 10. Exploring Transitions 11. Physics and Special Effects 12. Message Text and HUD 13. Inventory Logic 14. Managing Inventory 15. Dialogue Trees 16. Mecanim 17. Game Environment 18. Setting up the Game 19. Menus and Levels

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Book SynopsisBased on the authors' research in Fourier analysis, Brief Notes in Advanced DSP: Fourier Analysis with MATLAB addresses many concepts and applications of digital signal processing (DSP). The included MATLAB codes illustrate how to apply the ideas in practice.The book begins with the basic concept of the discrete Fourier transformation and its properties. It then describes lifting schemes, integer transformations, the discrete cosine transform, and the paired transform method for calculating the discrete Hadamard transform. The text also examines the decomposition of the 1D signal by so-called section basis signals as well as new forms of 2D signal/image representation and decomposition by direction signals/images. Focusing on Fourier transform wavelets and GivensHaar transforms, the last chapter discusses the problem of signal multiresolution.This book presents numerous interesting problems and concepts of unitary trTable of ContentsDiscrete Fourier Transform. Integer Fourier Transform. Cosine Transform. Hadamard Transform. Paired Transform-Based Decomposition. Fourier Transform and Multiresolution. References. Index.

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Trade ReviewFrom the reviews of the second edition: "This fascinating book deconstructs the process of producing graphics and in doing so raises many fascinating questions on the nature and representation of information...This second edition is almost twice the size of the original, with six new chapters and substantial revisions." Short Book Reviews of the International Statistical Institute, December 2005 "When the first edidtion of this book appeared in 2000 it was much praised. I called it a tour de force of the highest order. (Wainer, 2001), Edward Wegman (2000) argued that it was destined to become a classic. Now, six years later this very fine book has been much improved." Howard Wainer for Psychometrika "...The second edition is an impressive expansion beyond a quite remarkable first edition. The text remains dense and even more encyclopedic, but it is a pleasure to read, whether a novice or an expert in graphics...this book is a bargain...The second edition is a must-have volume for anyone interested in graphics." Thomas E. Bradstreet for the Journal of the American Statistical Association, December 2006 "I find myself still thinking about the book and its ideas, several weeks after I finished reading it. I love that kind of book." Mark Bailey for Techometrics, Vol. 49, No. 1, February 2007 "Warts and all, The Grammar of Graphics is a richly rewarding work, an outstanding achievement by one of the leaders of statistical graphics. Seek it out." Nicholas J. Cox for the Journal of Statistical Software, January 2007 "The second edition is a quite fascinating book as well, and it comes with many color graphics. Anyone working in this field can see how many hours the author (plus coworkers) has spent on such a volume. … Demands for good graphics are high and this book will help to wetten the appetite to create future computer packages that will meet this demand. An occasional reader will get insights into a modern world of computing … ." (Wolfgang Polasek, Statistical Papers, Vol. 48, 2007)Table of ContentsSyntax.- How To Make a Pie.- Data.- Variables.- Algebra.- Scales.- Statistics.- Geometry.- Coordinates.- Aesthetics.- Facets.- Guides.- Semantics.- Space.- Time.- Uncertainty.- Analysis.- Control.- Automation.- Reader.- Coda.

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Book SynopsisPreface.- Acknowledgements.- List of Figures.- List of Tables.- Introduction.- CG Basics.- Observation Skills.- Measurements.- Modeling 1: Polygons.- Resolution.- Optimization.- Validation.- Texture Coordinates (UVs).- Shaders and Texturing.- Rendering.- Animation.- Modeling 2: NURBS.- Modeling 3: Advanced.- Industry Standards.- Appendix.- Glossary.- Index.Trade ReviewFrom the reviews of the second edition:“This book presents basic CG topics in a novel, skill-related way that better reflects real-world, entertainment-related industry expectations and standards. … this attractive full-color book is an excellent resource for study topics and curricula. I recommend it to professionals in the entertainment industry … and to any other readers interested in state-of-the-art innovations and improvements and new modeling technologies as applied to artistic design.” (Athanasios D. Styliadis, Computing Reviews, November, 2013)Table of ContentsPreface.- Acknowledgements.- List of Figures.- List of Tables.- Introduction.- CG Basics.- Observation Skills.- Measurements.- Modeling 1: Polygons.- Resolution.- Optimization.- Validation.- Texture Coordinates (UVs).- Shaders and Texturing.- Rendering.- Animation.- Modeling 2: NURBS.- Modeling 3: Advanced.- Industry Standards.- Appendix.- Glossary.- Index.

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Book SynopsisBecause this book is specifically devoted to one-shot imaging, "One-Shot Color Astronomical Imaging" begins by looking at all the basics - what equipment will be needed, how color imaging is done, and most importantly, what specific steps need to be followed after the one-shot color images are taken.What is one-shot color imaging?Trade ReviewFrom the book reviews:“The book contains lots of good advice and tips for any imager – even if you have a mono CCD camera. This is a great book for imaging as it takes through all the steps required in order to generate pleasing images. One Shot Colour Astronomical Imaging is thoroughly recommended if you want a good overview of how to get into imaging no matter whether you have a mono or colour camera.” (astronomylog.co.uk, July, 2014)“There is a way to save time by using a so-called one-shot color CCD camera … . This book is about using such a camera, the equipment needed, the set-up for imaging, some tips and suggestions … it is an important guide to getting started with this kind of equipment. The book would also be of interest to those astrophotographers who are just getting started in the field … . Very useful and concise, and also inspirational.” (Kadri Tinn, AstroMadness.com, July, 2014)Table of ContentsDigital Imaging.- One-Shot Color vs. Multiple Color Filter Exposures.- Evaluating Your Existing Equipment.- Choosing the Right Stuff.- Finding Targets to Image.- Setting Up Your Imaging Confirmation.- Polar Alignment, Focusing, and Framing.- Calibration.- Taking Exposures and Auto Guiding.- Stack 'Em Up.- Histogram Display.- Image Processing and Enhancement.- Displaying Your Images.- More Things You Can Do.- Additional Resources.

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Book SynopsisTrade Review"Visualization is a young field with only a few primary texts available. What distinguishes this one is the way it synthesizes past work to develop a comprehensive framework for design and analysis. … The author builds a framework for understanding the key elements of visualization and develops a synthesis of current best practices. … The book is filled with examples from the universe of visualization. Virtually all the possibilities for visualization design are illustrated with specific examples. … This is an attractive book, one that’s likely to be a fundamental source for the field. It’s worth a look for anyone with even a passing interest."—MAA Reviews, March 2015"Munzner’s Visualization Analysis and Design is the first comprehensive textbook covering the topic of information visualization. She covers basic theory, careful analysis of the design space, design methodology, and numerous practical examples. Her taxonomic approach is ideally suited for use in the classroom to guide students through the many design decisions associated with creating effective visualizations."—Chris North, Virginia Tech"Visualization Analysis and Design does a fantastic job in providing a framework and language for analyzing, critiquing, and discussing visualizations. This book provides a wonderful foundation for the field."—Miriah Meyer, University of Utah"Visualization Analysis and Design is a book that fills the gaps in the existing literature. It offers a synthesized view and a framework most useful to guide the newcomer to visualization. The nested model that unifies design and evaluation is particularly enlightening. The book is truly valuable for an initial InfoVis course at the graduate level."—Beatriz Sousa Santos, Universidade de Aveiro"Munzner elegantly synthesizes an astounding amount of cutting-edge work on visualization into a clear, engaging, and comprehensive textbook that will prove indispensable to students, designers, and researchers."—Steven Franconeri, Northwestern University"A very detailed and thorough discussion of many topics central to information visualization. A must-read for researchers, sophisticated practitioners, and graduate students."—Jim Foley, Georgia Institute of Technology"Munzner's new book is thorough and beautiful. It belongs on the shelf of anyone whose work and life are touched and enriched by visualization."—Chris Johnson, University of Utah"Visualization is often presented in the classroom as a motley collection of techniques and algorithms designed to unearth insights from data. Tamara Munzner is one of the leading voices of the school that seeks to establish visualization as a discipline resting on well-understood pillars of perception, cognition, and interaction. This new volume from Tamara reflects her expansive views and presents visualization as a wholesome and essential topic for this age of Big Data and all things analytic."—Raghu Machiraju, The Ohio State University"Tamara Munzner is one of the world’s very top researchers in information visualization, and this meticulously crafted volume is probably the most thoughtful and deep synthesis the field has yet seen."—Michael McGuffin, École de Technologie Supérieure"Tamara Munzner shares her deep insights in visualization with us in this excellent textbook, equally useful for students and experts in the field. Highly structured, with many examples that illustrate the underlying framework."—Jarke van Wijk, Eindhoven University of Technology"This book provides the most comprehensive coverage of the fundamentals of visualization design that I have found. It is a much-needed and long-awaited resource for both teachers and practitioners of visualization."—Kwan-Liu Ma, University of California, Davis"Visualization is fundamental to meeting the unprecedented challenges and exploiting the wonderful opportunities of the ever-expanding deluge of data confronting virtually every field. Tamara Munzner’s new book provides a principled treatment of visualization design. This is the visualization textbook I have long awaited. It emphasizes abstraction, design principles, and the importance of evaluation and interactivity."—Jim Hollan, University of California, San Diego"Tamara Munzner is an outstanding scientist, a gifted scholar, and deeply cares about bringing research into practice … She is the driving force behind unifying methodology and terminology in the proliferating field of information visualization. Providing guidance, preventing mistakes, and showing best practices are the ingredients of the secret sauce that make this work so indispensable. The book puts together much of the wisdom she has accumulated over the years in a systematic, well-structured form and shapes the field of visualization in an unprecedented way. It helps to better understand problems, design better systems, avoid common mistakes, and better communicate results. Simply a must-read for everyone concerned with visualization!"—Wolfgang Aigner, St. Pölten University of Applied Sciences"Visualization Analysis and Design gives a framework that formalizes a notion of effective visualization. By connecting design choices with visualization idioms, Munzner provides readers with tools to both articulate the analysis of visualizations and to invent their own."—Joshua A. Levine, Clemson University"Without a doubt, Visualization Analysis and Design is the most comprehensive book on information visualization (InfoVis) to date … Perhaps what is most impressive about this book is its coverage in both the breadth and depth of relevant InfoVis techniques and topics. It will be immediately accessible to both newcomers and veterans of InfoVis who are interested in catching up to the state of the art. The book can be used both as a textbook in a classroom setting or as a reference book in any visualization research group."—Remco Chang, Tufts University"Visualization Analysis and Design is a pleasure to read for the students in my course. Tamara Munzner is striving to make visualization accessible to a very broad audience and is succeeding. This is a textbook we were waiting for."—Torsten Möller, University of Vienna "I like this book because it begins with providing a good way to think about visualization at a high level, and then follows through by providing the building blocks to use in achieving those goals. I think this book will be valuable to both researchers and practitioners because it provides well-grounded foundations as well as a framework to build upon them."—Michael Gleicher, University of Wisconsin–Madison"This highly readable and well-organized book not only covers the fundamentals of visualization design, but also provides a solid framework for analyzing visualizations and visualization problems with concrete examples from the academic community. I am looking forward to teaching from this book and sharing it with my research group."—Michele C. Weigle, Old Dominion University"Dr. Munzner’s work is at the right balance of theory of application—it is not just focused on the why, which is important, but the how. Concrete guidance at every point of the visualization design process is provided, an invaluable resource for instruction and learning."—T.J. Jankun-Kelly, Mississippi State University"Visualization is a young field with only a few primary texts available. What distinguishes this one is the way it synthesizes past work to develop a comprehensive framework for design and analysis. … The author builds a framework for understanding the key elements of visualization and develops a synthesis of current best practices. … The book is filled with examples from the universe of visualization. Virtually all the possibilities for visualization design are illustrated with specific examples. … This is an attractive book, one that’s likely to be a fundamental source for the field. It’s worth a look for anyone with even a passing interest."—MAA Reviews, March 2015"Munzner’s Visualization Analysis and Design is the first comprehensive textbook covering the topic of information visualization. She covers basic theory, careful analysis of the design space, design methodology, and numerous practical examples. Her taxonomic approach is ideally suited for use in the classroom to guide students through the many design decisions associated with creating effective visualizations."—Chris North, Virginia Tech"Visualization Analysis and Design does a fantastic job in providing a framework and language for analyzing, critiquing, and discussing visualizations. This book provides a wonderful foundation for the field."—Miriah Meyer, University of Utah"Visualization Analysis and Design is a book that fills the gaps in the existing literature. It offers a synthesized view and a framework most useful to guide the newcomer to visualization. The nested model that unifies design and evaluation is particularly enlightening. The book is truly valuable for an initial InfoVis course at the graduate level."—Beatriz Sousa Santos, Universidade de Aveiro"Munzner elegantly synthesizes an astounding amount of cutting-edge work on visualization into a clear, engaging, and comprehensive textbook that will prove indispensable to students, designers, and researchers."—Steven Franconeri, Northwestern University"A very detailed and thorough discussion of many topics central to information visualization. A must-read for researchers, sophisticated practitioners, and graduate students."—Jim Foley, Georgia Institute of Technology"Munzner's new book is thorough and beautiful. It belongs on the shelf of anyone whose work and life are touched and enriched by visualization."—Chris Johnson, University of Utah"Visualization is often presented in the classroom as a motley collection of techniques and algorithms designed to unearth insights from data. Tamara Munzner is one of the leading voices of the school that seeks to establish visualization as a discipline resting on well-understood pillars of perception, cognition, and interaction. This new volume from Tamara reflects her expansive views and presents visualization as a wholesome and essential topic for this age of Big Data and all things analytic."—Raghu Machiraju, The Ohio State University"Tamara Munzner is one of the world’s very top researchers in information visualization, and this meticulously crafted volume is probably the most thoughtful and deep synthesis the field has yet seen."—Michael McGuffin, École de Technologie Supérieure"Tamara Munzner shares her deep insights in visualization with us in this excellent textbook, equally useful for students and experts in the field. Highly structured, with many examples that illustrate the underlying framework."—Jarke van Wijk, Eindhoven University of Technology"This book provides the most comprehensive coverage of the fundamentals of visualization design that I have found. It is a much-needed and long-awaited resource for both teachers and practitioners of visualization."—Kwan-Liu Ma, University of California, Davis"Visualization is fundamental to meeting the unprecedented challenges and exploiting the wonderful opportunities of the ever-expanding deluge of data confronting virtually every field. Tamara Munzner’s new book provides a principled treatment of visualization design. This is the visualization textbook I have long awaited. It emphasizes abstraction, design principles, and the importance of evaluation and interactivity."—Jim Hollan, University of California, San Diego"Tamara Munzner is an outstanding scientist, a gifted scholar, and deeply cares about bringing research into practice … She is the driving force behind unifying methodology and terminology in the proliferating field of information visualization. Providing guidance, preventing mistakes, and showing best practices are the ingredients of the secret sauce that make this work so indispensable. The book puts together much of the wisdom she has accumulated over the years in a systematic, well-structured form and shapes the field of visualization in an unprecedented way. It helps to better understand problems, design better systems, avoid common mistakes, and better communicate results. Simply a must-read for everyone concerned with visualization!"—Wolfgang Aigner, St. Pölten University of Applied Sciences"Visualization Analysis and Design gives a framework that formalizes a notion of effective visualization. By connecting design choices with visualization idioms, Munzner provides readers with tools to both articulate the analysis of visualizations and to invent their own."—Joshua A. Levine, Clemson University"Without a doubt, Visualization Analysis and Design is the most comprehensive book on information visualization (InfoVis) to date … Perhaps what is most impressive about this book is its coverage in both the breadth and depth of relevant InfoVis techniques and topics. It will be immediately accessible to both newcomers and veterans of InfoVis who are interested in catching up to the state of the art. The book can be used both as a textbook in a classroom setting or as a reference book in any visualization research group."—Remco Chang, Tufts University"Visualization Analysis and Design is a pleasure to read for the students in my course. Tamara Munzner is striving to make visualization accessible to a very broad audience and is succeeding. This is a textbook we were waiting for."—Torsten Möller, University of Vienna"I like this book because it begins with providing a good way to think about visualization at a high level, and then follows through by providing the building blocks to use in achieving those goals. I think this book will be valuable to both researchers and practitioners because it provides well-grounded foundations as well as a framework to build upon them."—Michael Gleicher, University of Wisconsin–Madison"This highly readable and well-organized book not only covers the fundamentals of visualization design, but also provides a solid framework for analyzing visualizations and visualization problems with concrete examples from the academic community. I am looking forward to teaching from this book and sharing it with my research group."—Michele C. Weigle, Old Dominion University"Dr. Munzner’s work is at the right balance of theory of application—it is not just focused on the why, which is important, but the how. Concrete guidance at every point of the visualization design process is provided, an invaluable resource for instruction and learning."—T.J. Jankun-Kelly, Mississippi State UniversityTable of ContentsWhat's Vis, and Why Do It? What: Data Abstraction. Why: Task Abstraction. Analysis: Four Levels for Validation. Marks and Channels. Rules of Thumb. Arrange Tables. Arrange Spatial Data. Arrange Networks and Trees. Map Color and Other Channels. Manipulate View. Facet into Multiple Views. Reduce Items and Attributes. Embed: Focus+Context. Analysis Case Studies. Bibliography.

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Book SynopsisIntegrating Scale in Remote Sensing and GIS serves as the most comprehensive documentation of the scientific and methodological advances that have taken place in integrating scale and remote sensing data. This work addresses the invariants of scale, the ability to change scale, measures of the impact of scale, scale as a parameter in process models, and the implementation of multiscale approaches as methods and techniques for integrating multiple kinds of remote sensing data collected at varying spatial, temporal, and radiometric scales. Researchers, instructors, and students alike will benefit from a guide that has been pragmatically divided into four thematic groups: scale issues and multiple scaling; physical scale as applied to natural resources; urban scale; and human health/social scale. Teeming with insights that elucidate the significance of scale as a foundation for geographic analysis, this book is a vital resource to those seriously involved in the field Trade Review"This book provides a new and comprehensive view of what scale means in today's rapidly advancing world of geographic information technologies. The authors and editors are some of the most reputable figures in the field, and passionate about creating more awareness of the importance of scale, and more knowledge of its properties and impacts. It is a very welcome addition to the literature on the topic, one that should be part of the library of every environmental or social scientist."—Michael F. Goodchild, University of California, Santa Barbara, USA"This book is a superb mix of theory and a wide range of impactful applications, and at the same time integrates this with modern concepts and data sources such as complexity science and crowd-sourcing. I recommend this book to readers who are keen to understand the real world, and to know how to manipulate spatial and space-time data in a principled way."—Peter M. Atkinson, Lancaster University, United Kingdom"The scale is a fundamental concept in geographical analysis, and this book addresse[s] the importance of scale in remote sensing (or broadly GIScience) from different per-spectives. This well-organized book includes four themes (13 Chapters), namely scale/multi-scaling issues, physical scale, human scale, and social scale."—Mingshu Wang, University of Twente, NetherlandsTable of ContentsIntroduction. Fundamentals of Multiscaled Remote Sensing Data for GIS Integration. Scale and Remote Sensing and GIS Integration: A Revisit of the Issues. Remote Sensing: Advances in Sensors and Data. Integration of Multispatial, Multitemporal, and Multispectral Remote Sensing Data in GIS: Progress and Challenges. Theory, Methods, and Techniques for Multiscale Data Integration. Computational and Technological Issues. Implementation of Multiscale Approaches: Methods and Examples. Modeling Methods for GIS Integration of Multiscaled Remote Sensing Data. Multiscaled Data Fusion for GIS Integration. Uncertainty and Error Analysis in Remote Sensing Data Integration with GIS. Geographic Object-Based Image Analysis. Temporal Analysis for Remote Sensing/GIS Integration. Applications of Multiscaled Remote Sensing and GIS. Approaches to Land Use/Land Change with Multiscaled Remote Sensing Data. Multiscaled Remote Sensing Data for Analysis of Landscape Heterogeneity. Environmental Modeling with Multiscaled Data. Use of Hyperspectral Data Remote Sensing Data in GIS. Analysis of Multiscaled Thermal Remote Sensing Data. Multiscaled Remote Sensing Data and GIS for Modeling Land Surface Processes. GIS, Multiscaled Remote Sensing Data for Climate Change Analysis. Integration of GPS, GIS, and Multiscaled Remote Sensing Data. Real Time Data and GIS Integration Applications. Multiscaled Remote Sensing Data, GIS Integration, and the Future. Summary. Epilogue.

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Book SynopsisIn3D Printing With MatterControl, Joan Horvath and Rich Cameron, the team behindMastering 3D Printing, explain step-by-step how to use the MatterControl program, which allows you to control many common types of 3D printers (including both cartesian and delta style machines).3D Printing With MatterControlcan stand alone, or it can be a companion toMastering 3D Printingto show you how to install, configure, and use best practices with your printer and printing software. The book includes both step by step software walkthroughs and case studies with typical 3D printed objects. Whether you are a "maker" or a teacher of makers,3D Printing with MatterControlwill show you how to get the most out of your printer with the new standard for open source 3D printing software. While there are books available on 3D printers, and even a few on software to make models for printers, there are few good sources covering the software thatactually controls these printers. MatterControl is emerging as the leading open source software for 3D printers, and3DPrinting With MatterControlcovers this new standard in this brief book.Table of ContentsPart 1: The 3D-Printing EcosystemChapter 1. The Desktop 3D PrinterChapter 2. What is MatterControl?Chapter 3. Downloading and Configuring MatterControlPart 2: The 3D-Printing ProcessChapter 4. Making a 3D ModelChapter 5. Slicing a 3D ModelChapter 6. Controlling your 3D PrinterChapter 7. Material ConsiderationsChapter 8. Special CasesPart 3: Your Printer at WorkChapter 9. File and Settings Management and the Touch TabletChapter 10. Case Studies and Classroom TipsChapter 11. MatterControl PluginsChapter 12. Troubleshooting and Post-ProcessingAppendix A. Supported Printer ManufacturersAppendix B. Links

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Book Synopsis Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You''ll see the OpenCV algorithms and how to use them for image processing.  The next section looks at advanced machine learning and deep learning methods for image processing and classification. You''ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you''ll explore how models are made in real time and then deployed using various DevOps tools.  All the concepTable of ContentsChapter 1: Installation and Environment Setup Chapter Goal: Making System Ready for Image Processing and Analysis No of pages 20 Sub -Topics (Top 2) 1. Installing Jupyter Notebook 2. Installing OpenCV and other Image Analysis dependencies 3. Installing Neural Network Dependencies Chapter 2: Introduction to Python and Image Processing Chapter Goal: Introduction to different concepts of Python and Image processing Application on it. No of pages: 50 Sub - Topics (Top 2) 1. Essentials of Python 2. Terminologies related to Image Analysis Chapter 3: Advanced Image Processing using OpenCV Chapter Goal: Understanding Algorithms and their applications using Python No of pages: 100 Sub - Topics (Top 2): 1. Operations on Images 2. Image Transformations Chapter 4: Machine Learning Approaches in Image Processing Chapter Goal: Basic Implementation of Machine and Deep Learning Models, which takes care of Image Processing, before applications in real-time scenario No of pages: 100 Sub - Topics (Top 2): 1. Image Classification and Segmentation 2. Applying Supervised and Unsupervised Learning approaches on Images using Python Chapter 5: Real Time Use Cases Chapter Goal: Working on 5 projects using Python, applying all the concepts learned in this book No of pages: 100 Sub - Topics (Top 5): 1. Facial Detection 2. Facial Recognition 3. Hand Gesture Movement Recognition 4. Self-Driving Cars Conceptualization: Advanced Lane Finding 5. Self-Driving Cars Conceptualization: Traffic Signs Detection Chapter 6: Appendix A Chapter Goal: Advanced concepts Introduction No of pages: 50 Sub - Topics (Top 2): 1. AdaBoost and XGBoost 2. Pulse Coupled Neural Networks

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Book SynopsisWith detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project.

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Book SynopsisConsistently rated as the best overall introduction to computer-based image processing, The Image Processing Handbook covers two-dimensional (2D) and three-dimensional (3D) imaging techniques, image printing and storage methods, image processing algorithms, image and feature measurement, quantitative image measurement analysis, and more.Incorporating image processing and analysis examples at all scales, from nano- to astro-, this Seventh Edition: Features a greater range of computationally intensive algorithms than previous versions Provides better organization, more quantitative results, and new material on recent developments Includes completely rewritten chapters on 3D imaging and a thoroughly revamped chapter on statistical analysis Contains more than 1700 references to theory, methods, and applications in a wide variety of disciplines Presents 500+ entirely new figures and images, with more thanTrade Review"With a new co-author (the same Brent Neal who has collaborated with him before in writing the excellent book Measuring Shape), John Russ has again produced a winner—a textbook and reference book that belongs on the shelf, and perhaps on the desk, of anyone involved in digital imaging. Even if you have a copy of one of the previous editions, this is a highly worthwhile addition." —Microscopy and Microanalysis, October 2016 Table of ContentsIntroduction. Acquiring Images. Printing and Storage. Human Vision. Correcting Imaging Defects. Image Enhancement in the Spatial Domain. Processing Images in Frequency Space. Segmentation and Thresholding. Processing Binary Images. Image Measurements. Feature Measurements. Characterizing Shape. Correlation, Classification, Identification, and Matching. 3D Imaging. 3D Processing and Measurement. Imaging Surfaces. References.

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Book Synopsis3D Modeling and Animation: Synthesis and Analysis Techniques for the Human Body aims to cover the areas of modeling and animating 3D synthetic human models at a level that is useful to students, researchers, software developers and content generators. This book provides a reference for the state-of-the-art methods, delivered by the leading researchers in this area, who are invited to contribute to the appropriate chapters according to their expertise. The reader will be presented with the latest, research-level, techniques for the analysis and synthesis of still and moving human bodies, with particular emphasis in facial and gesture characteristics.Table of ContentsIntroduction: Advances in Vision-Based Human Body Modeling, Virtual Character Definition and Animation within the MPEG-4 Standard, A Survey of Passive Camera Calibration, Real-time Analysis of Human Body Parts, and Gesture-Activity Recognition in 3D, Facial Expression and Gesture Analysis for Emotionally-rich Man-machine Interaction, Techniques for Face Motion & Expression Analysis on Monocular Images, Analysis and Synthesis of Facial Expressions, Modeling and Synthesis of Realistic Visual Speech in 3D, Automatic 3-D Face Model Adaptation with two Comp exity Modes for Visual Communication, Learning 3D Face Animation Model: Methods and Applications, Synthesis and Analysis Techniques for the Human Body: R&D Projects

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