Image processing Books

Book SynopsisIntroductory Digital Signal Processing with Computer Applications Second Edition Paul A. Lynn formerly: Imperial College of Science, Technology and Medicine, London, UK and Wolfgang Fuerst United Nations, New York, USA An excellent introductory book (Review of the First Edition in the International Journal of Electrical Engineering Education) .Table of ContentsPreface to the First Edition ix Preface to the Second Edition xiii 1 Introduction 1 2 Time-Domain Analysis 32 3 Frequency-Domain Analysis: The Discrete Fourier Series and the Fourier Transform 65 4 Frequency-Domain Analysis: the z-Transform 98 5 Design of Nonrecursive Digital Filters 132 6 Design of Recursive Digital Filters 167 7 The Discrete and Fast Fourier Transforms 211 8 FFT Processing 251 9 Random Digital Signals 284 10 Random DSP 316 Appendix A1 Computer Programs 351 Appendix A2 Continuous-time Fourier Analysis 433 Answers to Selected Problems 467 Bibliography 473 Index 475

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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 SynopsisTable of Contents 1 Introduction 1.1 What is Digital Image Processing? 1.2 The Origins of Digital Image Processing 1.3 Examples of Fields that Use Digital Image Processing 1.4 Fundamental Steps in Digital Image Processing 1.5 Components of an Image Processing System 2 Digital Image Fundamentals 2.1 Elements of Visual Perception 2.2 Light and the Electromagnetic Spectrum 2.3 Image Sensing and Acquisition 2.4 Image Sampling and Quantization 2.5 Some Basic Relationships Between Pixels 2.6 Introduction to the Basic Mathematical Tools Used in Digital Image Processing 3 Intensity Transformations and Spatial Filtering 3.1 Background 3.2 Some Basic Intensity Transformation Functions 3.3 Histogram Processing 3.4 Fundamentals of Spatial Filtering 3.5 Smoothing (Lowpass) Spatial Filters 3.6 Sharpening (Highpass) Spatial Filters 3.7 Highpass, Bandreject, and Bandpass Filters from Lowpass Filters 3.8 Combining Spatial Enhancement Methods 3.9 Using Fuzzy Techniques for Intensity Transformations and Spatial Filtering 4 Filtering in the Frequency Domain 4.1 Background 4.2 Preliminary Concepts 4.3 Sampling and the Fourier Transform of Sampled Functions 4.4 The Discrete Fourier Transform of One Variable 4.5 Extensions to Functions of Two Variables 4.6 Some Properties of the 2-D DFT and IDFT 4.7 The Basics of Filtering in the Frequency Domain 4.8 Image Smoothing Using Lowpass Frequency Domain Filters 4.9 Image Sharpening Using Highpass Filters 4.10 Selective Filtering 4.11 The Fast Fourier Transform 5 Image Restoration and Reconstruction 5.1 A Model of the Image Degradation/Restoration Process 5.2 Noise Models 5.3 Restoration in the Presence of Noise Only—Spatial Filtering 5.4 Periodic Noise Reduction Using Frequency Domain Filtering 5.5 Linear, Position-Invariant Degradations 5.6 Estimating the Degradation Function 5.7 Inverse Filtering 5.8 Minimum Mean Square Error (Wiener) Filtering 5.9 Constrained Least Squares Filtering 5.10 Geometric Mean Filter 5.11 Image Reconstruction from Projections 6 Wavelet and Other Image Transforms 6.1 Preliminaries 6.2 Matrix-based Transforms 6.3 Correlation 6.4 Basis Functions in the Time-Frequency Plane 6.5 Basis Images 6.6 Fourier-Related Transforms 6.7 Walsh-Hadamard Transforms 6.8 Slant Transform 6.9 Haar Transform 6.10 Wavelet Transforms 7 Color Image Processing 7.1 Color Fundamentals 7.2 Color Models 7.3 Pseudocolor Image Processing 7.4 Basics of Full-Color Image Processing 7.5 Color Transformations 7.6 Color Image Smoothing and Sharpening 7.7 Using Color in Image Segmentation 7.8 Noise in Color Images 7.9 Color Image Compression 8 Image Compression and Watermarking 8.1 Fundamentals 8.2 Huffman Coding 8.3 Golomb Coding 8.4 Arithmetic Coding 8.5 LZW Coding 8.6 Run-length Coding

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Book SynopsisComputer Vision: Algorithms and Applications explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications such as image search and autonomous navigation, as well as for fun, consumer-level tasks that students can apply to their own personal photos and videos.More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference takes a scientific approach to the formulation of computer vision problems. These problems are then analyzed using the latest classical and deep learning models and solved using rigorous engineering principles.Topics and features: Structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses Incorporates totally new material on deep learning and applications such as mobile computational photography, autonomous navigation, and augmented reality Presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects Includes 1,500 new citations and 200 new figures that cover the tremendous developments from the last decade Provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, estimation theory, datasets, and software Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.Table of Contents

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Book SynopsisThis book provides an in-depth overview of artificial intelligence and deep learning approaches with case studies to solve problems associated with biometric security such as authentication, indexing, template protection, spoofing attack detection, ROI detection, gender classification etc. This text highlights a showcase of cutting-edge research on the use of convolution neural networks, autoencoders, recurrent convolutional neural networks in face, hand, iris, gait, fingerprint, vein, and medical biometric traits. It also provides a step-by-step guide to understanding deep learning concepts for biometrics authentication approaches and presents an analysis of biometric images under various environmental conditions. This book is sure to catch the attention of scholars, researchers, practitioners, and technology aspirants who are willing to research in the field of AI and biometric security.Table of Contents1. Deep Learning-Based Hyperspectral Multimodal Biometric Authentication System Using Palmprint and Dorsal Hand Vein. 2. Cancelable Biometrics for Template Protection: Future Directives with Deep Learning. 3. On Training Generative Adversarial Network for Enhancement of Latent Fingerprints. 4. DeepFake Face Video Detection Using Hybrid Deep Residual Networks nad LSTM Architecture. 5. Multi-spectral Short-Wave Infrared Sensors and Convolutional Neural Networks for Biometric Presentation Attack Detection. 6. AI-Based Approach for Person Identification Using ECG Biometric. 7. Cancelable Biometric Systems from Research to Reality: The Road Less Travelled. 8. Gender Classification under Eyeglass Occluded Ocular Region: An Extensive Study Using Multi-spectral Imaging. 9. Investigation of the Fingernail Plate for Biometric Authentication using Deep Neural Networks. 10. Fraud Attack Detection in Remote Verification systems for Non-enrolled Users. 11. Indexing on Biometric Databases. 12. Iris Segmentation in the Wild Using Encoder-Decoder-Based Deep Learning Techniques. 13. PPG-Based Biometric Recognition: Opportunities with Machine and Deep Learning. 14. Current Trends of Machine Learning Techniques in Biometrics and its Applications.

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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 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 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 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 SynopsisThe six volume set of LNCS 12622-12627 constitutes the proceedings of the 15th Asian Conference on Computer Vision, ACCV 2020, held in Kyoto, Japan, in November/ December 2020.*The total of 254 contributions was carefully reviewed and selected from 768 submissions during two rounds of reviewing and improvement. The papers focus on the following topics: Part I: 3D computer vision; segmentation and grouping Part II: low-level vision, image processing; motion and tracking Part III: recognition and detection; optimization, statistical methods, and learning; robot vision Part IV: deep learning for computer vision, generative models for computer vision Part V: face, pose, action, and gesture; video analysis and event recognition; biomedical image analysis Part VI: applications of computer vision; vision for X; datasets and performance analysis *The conference was held virtually.Table of ContentsApplications of Computer Vision, Vision for X.- Query by Strings and Return Ranking Word Regions with Only One Look.- Single-Image Camera Response Function Using Prediction Consistency and Gradual Refinement.- FootNet: An efficient convolutional network for multiview 3D foot reconstruction.- Synthetic-to-real domain adaptation for lane detection.- RAF-AU Database: In-the-Wild Facial Expressions with Subjective Emotion Judgement and Objective AU Annotations.- DoFNet: Depth of Field Difference Learning for Detecting Image Forgery.- Explaining image classifiers by removing input features using generative models.- Do We Need Sound for Sound Source Localization?.- Modular Graph Attention Network for Complex Visual Relational Reasoning.- CloTH-VTON: Clothing Three-dimensional reconstruction for Hybrid image-based Virtual Try-ON.- Multi-label X-ray Imagery Classification via Bottom-up Attention and Meta Fusion.- Learning End-to-End Action Interaction by Paired-Embedding Data Augmentation.- Sketch-to-Art: Synthesizing Stylized Art Images From Sketches.- Road Obstacle Detection Method Based on an Autoencoder with Semantic Segmentation.- SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection.- Trainable Structure Tensors for Autonomous Baggage Threat Detection Under Extreme Occlusion.- Audiovisual Transformer with Instance Attention for Audio-Visual Event Localization.- Watch, read and lookup: learning to spot signs from multiple supervisors.- Domain-transferred Face Augmentation Network.- Pose Correction Algorithm for Relative Frames between Keyframes in SLAM.- Dense-Scale Feature Learning in Person Re-Identification.- Class-incremental Learning with Rectified Feature-Graph Preservation.- Patch SVDD: Patch-level SVDD for Anomaly Detection and Segmentation.- Towards Robust Fine-grained Recognition by Maximal Separation of Discriminative Features.- Visually Guided Sound Source Separation using Cascaded Opponent Filter Network.- Channel Recurrent Attention Networks for Video Pedestrian Retrieval.- In Defense of LSTMs for Addressing Multiple Instance Learning Problems.- Addressing Class Imbalance in Scene Graph Parsing by Learning to Contrast and Score.- Show, Conceive and Tell: Image Captioning with Prospective Linguistic Information.- Datasets and Performance Analysis.- RGB-T Crowd Counting from Drone: A Benchmark and MMCCN Network.- Webly Supervised Semantic Embeddings for Large Scale Zero-Shot Learning.- Compensating for the Lack of Extra Training Data by Learning Extra Representation.- Class-Wise Difficulty-Balanced Loss for Solving Class-Imbalance.- OpenTraj: Assessing Prediction Complexity in Human Trajectories Datasets.- Pre-training without Natural Images.- TTPLA: An Aerial-Image Dataset for Detection and Segmentation of Transmission Towers and Power Lines.- A Day on Campus - An Anomaly Detection Dataset for Events in a Single Camera.- A Benchmark and Baseline for Language-Driven Image Editing.- Self-supervised Learning of Orc-Bert Augmentator for Recognizing Few-Shot Oracle Characters.- Understanding Motion in Sign Language: A New Structured Translation Dataset.- FreezeNet: Full Performance by Reduced Storage Costs.

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Book SynopsisTable of Contents1. Introduction 2. Fundamentals of Microscopy 3. Image Digitization and Display 4. Geometric Transformations 5. Image Enhancement 6. Morphological Image Processing 7. Image Segmentation 8. Object Measurement 9. Object Classification 10. Fluorescence Imaging 11. Multispectral Imaging 12. Three-Dimensional Imaging 13. Time-Lapse Imaging 14. Digital Microscopy 15. Super Resolution Microscopy 16. Image Informatics 17. Deep Learning in Microscope Image Analysis 18. Open Microscopy Platforms and Tool

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Book SynopsisTable of Contents1. Meta-Learning Theory 2. Meta-Learning for Medical Image Detection and Segmentation 3. Meta-Learning for Medical Image Diagnosis 4. Meta-Learning for Other Biomedical Applications 5. Meta-Learning for Health Informatics

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Book SynopsisThe popularity of magnetic resonance (MR) imaging in medicine is no mystery: it is non-invasive, it produces high quality structural and functional image data, and it is very versatile and flexible. Research into MR technology is advancing at a blistering pace, and modern engineers must keep up with the latest developments. This is only possible with a firm grounding in the basic principles of MR, and Advanced Image Processing in Magnetic Resonance Imaging solidly integrates this foundational knowledge with the latest advances in the field.Beginning with the basics of signal and image generation and reconstruction, the book covers in detail the signal processing techniques and algorithms, filtering techniques for MR images, quantitative analysis including image registration and integration of EEG and MEG techniques with MR, and MR spectroscopy techniques. The final section of the book explores functional MRI (fMRI) in detail, discussing fundamentals and advanced exploratory Table of ContentsSignal and Image Generation and Reconstruction. SNR Improvement and Inhomogeneities Correction. Image Processing and Quantitative Analysis. Spectroscopy, Diffusion, and Elasticity: From Modeling to Parametric Image Generation. BOLD Contrast MR Imaging and fMRI Signal Analysis. Index.

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Book SynopsisNonlinear signal and image processing methods are fast emerging as an alternative to established linear methods for meeting the challenges of increasingly sophisticated applications. Advances in computing performance and nonlinear theory are making nonlinear techniques not only viable, but practical.This book details recent advances in nonlinear theory and methods and explores an array of modern signal and image processing applications. The first several chapters focus on nonlinear signal processing theory, targeting three critical areas: filter analysis, nonlinear filter class design, and signal analysis. The remaining chapters explore nonlinear approaches across the broad spectrum of applications with signal processing components, from data traffic modeling and image enhancement to cutting edge applications in genomics. All of the chapters were contributed by well-known theorists and application-driven researchers who explore current and emerging nonlinear methods Table of ContentsEnergy Conservation in Adaptive Filtering. Fuzzy Methods in Nonlinear Signal Processing: Part I - Theory. Fuzzy Methods in Nonlinear Signal Processing: Part Ii - Applications. Time-Frequency Wigner Distribution Approach to Differential Equations. Weighted Myriad Filters. Data Traffic Modeling - A Signal Processing Perspective. Nonlinear Adaptive Filters for Acoustic Echo Cancellation in Mobile Terminals. Blind and Semi-Blind Channel Estimation. Bayesian Image and Video Enhancement Using a Non-Gaussian Prior. Statistical Image Modeling and Processing Using Wavelet Domain Hidden Markov Models. Self-Organizing Maps and their Applications in Image Processing, Information Organization, and Retrieval. Nonlinear Techniques for Color Image Processing. Genetic Regulatory Networks: A Nonlinear Signal Processing Perspective.

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Book SynopsisA Complete One-Stop ResourceWhile digital color is now the technology of choice for printers, the knowledge required to address the quality and productivity issues of these devices is scattered across several technologies, as is its supporting literature. Bringing together information from diverse fields, Control of Color Imaging Systems: Analysis and Design is the first book to provide comprehensive coverage of the fundamentals and algorithms of the numerous disciplines associated with digital color printing in a single resource. The authors review the history of digital printing systems, explore its current status, and explain fundamental concepts, including: digital image formation, sampling, quantization, image coding, spot color calibration, and one- and multi-dimensional tone control of color management systems â including process physics and controls.A Complete Self-Tutorial With Over 150 Design Examples and 1Trade Review"... brings together the technical fields of imaging systems and feedback control systems in a self-contained manner. ... an excellent addition to the literature on the analysis and design of color-imaging systems. It should be recommended to anyone who wants to become familiar with state-of-the-art techniques in these areas."-- Daniel Viassolo, Vestas Technology R&D, Power Plant Department, Houston, Texas Table of ContentsPreface. Acknowledgments. An Overview of Digital Printing Systems. Fundamentals of Digital Image Processing. Mathematical Foundations. State-Variable Representation. Closed-Loop System Analysis and Design. Interpolation of Multidimensional Functions. Three-Dimensional Control of Color Management Systems. One-Dimensional, Two-Dimensional, and Spot-Color. Management and Control Methods. Internal Process Controls. Printing System Models. Appendices (A-C). Index.

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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 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 SynopsisComputer Vision: Algorithms and Applications explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications such as image search and autonomous navigation, as well as for fun, consumer-level tasks that students can apply to their own personal photos and videos.More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference takes a scientific approach to the formulation of computer vision problems. These problems are then analyzed using the latest classical and deep learning models and solved using rigorous engineering principles.Topics and features: Structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses Incorporates totally new material on deep learning and applications such as mobile computational photography, autonomous navigation, and augmented reality Presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects Includes 1,500 new citations and 200 new figures that cover the tremendous developments from the last decade Provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, estimation theory, datasets, and software Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.Table of Contents

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Book SynopsisThis book addresses one of the most important unsolved problems in artificial intelligence: the task of learning, in an unsupervised manner, from massive quantities of spatiotemporal visual data that are available at low cost. The book covers important scientific discoveries and findings, with a focus on the latest advances in the field. Presenting a coherent structure, the book logically connects novel mathematical formulations and efficient computational solutions for a range of unsupervised learning tasks, including visual feature matching, learning and classification, object discovery, and semantic segmentation in video. The final part of the book proposes a general strategy for visual learning over several generations of student-teacher neural networks, along with a unique view on the future of unsupervised learning in real-world contexts. Offering a fresh approach to this difficult problem, several efficient, state-of-the-art unsupervised learning algorithms are reviewed in detail, complete with an analysis of their performance on various tasks, datasets, and experimental setups. By highlighting the interconnections between these methods, many seemingly diverse problems are elegantly brought together in a unified way. Serving as an invaluable guide to the computational tools and algorithms required to tackle the exciting challenges in the field, this book is a must-read for graduate students seeking a greater understanding of unsupervised learning, as well as researchers in computer vision, machine learning, robotics, and related disciplines. Table of Contents1. Unsupervised Visual Learning: from Pixels to Seeing.- 2. Unsupervised Learning of Graph and Hypergraph Matching.- 3. Unsupervised Learning of Graph and Hypergraph Clustering.- 4. Feature Selection meets Unsupervised Learning.- 5. Unsupervised Learning of Object Segmentation in Video with Highly Probable Positive Features.- 6. Coupling Appearance and Motion: Unsupervised Clustering for Object Segmentation through Space and Time.- 7. Unsupervised Learning in Space and Time over Several Generations of Teacher and Student Networks.- 8. Unsupervised Learning Towards the Future.

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Book SynopsisThis book constitutes the refereed proceedings of the 13th International Conference on Computer Vision Systems, ICVS 2021, held in September 2021. Due to COVID-19 pandemic the conference was held virtually. The 20 papers presented were carefully reviewed and selected from 29 submissions. cover a broad spectrum of issues falling under the wider scope of computer vision in real-world applications, including among others, vision systems for robotics, autonomous vehicles, agriculture and medicine. In this volume, the papers are organized into the sections: attention systems; classification and detection; semantic interpretation; video and motion analysis; computer vision systems in agriculture.Table of ContentsAttention Systems.- Thermal Image Super-Resolution Using Second-Order Channel Attention with Varying Receptive Fields.- MARL: Multimodal Attentional Representation Learning for Disease Prediction.- Object Localization with Attribute Preference based on Top-Down Attention.- See the silence: improving visual-only voice activity detection by optical flow and RGB fusion.- Classification and Detection.- Score to Learn: a Comparative Analysis of Scoring Functions for Active Learning in Robotics.- Enhancing the performance of image classification through features automatically learned from depth-maps.- Object Detection on TPU Accelerated Embedded Devices.- Tackling Inter-Class Similarity and Intra-Class Variance for Microscopic Image-based Classification.- Semantic Interpretation.- Measuring the Sim2Real gap in 3D Object classification for different 3D data representation.- Spatially-Constrained Semantic Segmentation with Topological Μaps and Visual Εmbeddings.- Knowledge-enabled generation of semantically annotated image sequences of manipulation activities from VR demonstrations.- Make It Easier: An Empirical Simplification of a Deep 3D Segmentation Network for Human Body Parts.- Video and Motion Analysis.- Video Popularity Prediction through Fusing Early Viewership with Video Content.- Action Prediction during Human-Object Interaction based on DTW and Early Fusion of Human and Object Representations.- GridTrack: Detection and Tracking of Multiple Objects in Dynamic Occupancy Grids.- An Efficient Video Desnowing and Deraining Method with a Novel Variant Dataset.- Computer Vision Systems in Agriculture.- Robust Counting of Soft Fruit through Occlusions with Re-identification.- Non-destructive Soft Fruit Mass and Volume Estimation for Phenotyping in Horticulture.- Learning Image-based Contaminant Detection in Wool Fleece from Noisy Annotations.- Active Learning for Crop-Weed Discrimination by Image Classification from Convolutional Neural Network’s Feature Pyramid Levels.

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Book SynopsisThis book, geared towards both students and professionals, examines the synthesis of artificial intelligence (AI) and psychology in detecting mis-/disinformation in digital media content, and suggests practical means to intervene and curtail this current global ‘infodemic’. This interdisciplinary book explores technological, psychological, philosophical, and linguistic insights into the nature of truth and deception, trust and credibility, cognitive biases and logical fallacies and how, through AI and human intervention, content users can be alerted to the presence of deception. The author investigates how AI can mimic the procedures and know-hows of humans, showing how AI can help spot fakes and how AI tools can work to debunk rumors and fact-check. The book describes how AI detection systems work and how they fit with broader societal and individual concerns. Each chapter focuses attention on key concepts and their inter-connection. The first part of the book seeks theoretical footing to understand our interactions with new information and reviews relevant empirical findings in behavioral sciences. The second part is about applied knowledge. The author looks at several known practices that guard us against deception, and provides several real-world examples of manipulative persuasive techniques in advertising, political propaganda, and public relations. She provides links to the downloadable executable files to three AI applications (clickbait, satire, and falsehood detectors) via LiT.RL GitHub, an open access repository. The book is useful to students and professionals studying AI and media studies as well as library and information professionals. Examines how artificial intelligence (AI) and psychology can aid in detecting mis-/disinformation and the language of deceit in digital media content; Suggests practical computational means to intervene and curtail the global ‘infodemic’ of fake news; Presents how AI can sift, sort, and shuffle digital content, to reduce the amount of content needed to be reviewed by humans. Table of ContentsIntroduction.- Infodemic in the Digital Media Content.- Part I. Human Nature of Deception and Perceptions of Truth.- Psychology of Mis-/Disinformation and Language of Deceit.- Library and Information Science on Credibility and Trust in Computing.- Philosophies of Truth.- Part II. Applied Practices and Artificial Intelligence (AI).- Investigation in Law Enforcement, Journalism, and Sciences.- Manipulation in Marketing, Advertising, and Public Relations.- Artificially Intelligent Solutions: Detection, Debunking, Fact-Checking.- Lessons for Infodemic Control and Future of Digital Content Verification.- Conclusion.

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Book SynopsisThis volume constitutes the refereed proceedings of the 4th International Conference on Recent Trends in Image Processing and Pattern Recognition, RTIP2R 2021, held in Msida, Malta, in December 2021. Due to the COVID-19 pandemic the conference was held online. The 19 full papers and 14 short papers presented were carefully reviewed and selected from 84 submissions. The papers are organized in the following topical sections:​ healthcare: medical imaging and informatics; computer vision and pattern recognition; document analysis and recognition; signal processing and machine learning; satellite imaging and remote sensing. Table of ContentsHealthcare: medical imaging and informatics.- Computer Vision and Pattern Recognition.- Document analysis and recognition.- Signal processing and machine learning.- Satellite imaging and remote sensing.

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Book SynopsisThis book constitutes the proceedings of the 11th International Conference, MCSS 2022, held in Kraków, Poland, during November 3–4, 2022. The 13 full papers included in this book were carefully reviewed and selected from 33 submissions. The papers cover ongoing research activities in the following topics: cybersecurity, multimedia services; intelligent monitoring; audio-visual systems; biometric applications; experiments and deployments.Table of ContentsSecrecy Performance of Scenario with Multiple Antennas in Cooperative Satellite Networks.- Attack Detection in SS7.- Sector-specific Training - A Federated Maritime Scenario.- E-Skills in Cybersecurity.- Multi-Sector Risk Management Framework for Analysis Cybersecurity Challenges and Opportunities.- AI Cybersecurity Assurance for Autonomous Transport Systems: Scenario, Model, and IMECA-based Analysis.- Integration of Image Analysis Component with Industrial Workflow Management System.- Impact of nonbinary input vectors on security of Tree Parity Machine.- Approach to sector-specific Cybersecurity Certifications Schemes: Key Elements and Security Problem Definition.- Technology and Police: a way to create predicting policing.- BCI: Technologies and Applications Review and Toolkit Proposal.- Clustering-based Filtering of Big Data to improve Forecasting Effectiveness and Efficiency.- Method for Assessing Objective Video Quality for Automatic License Plate Recognition Tasks.

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Book SynopsisThis two-volume set (CCIS 1762-1763) constitutes the refereed proceedings of the 4th International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2022, held in Bhopal, India, in December 2022. The 64 papers presented in this two-volume set were thoroughly reviewed and selected from 399 submissions. The papers are organized according to the following topical sections: ​machine learning and computational intelligence; data sciences; image processing and computer vision; network and cyber security.Table of ContentsMachine Learning and Computational Intelligence.- Data Sciences.- Image Processing and Computer Vision.- Network and Cyber Security.

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Book SynopsisThis book constitutes the proceedings of the 9th International Conference on Algorithms and Discrete Applied Mathematics, CALDAM 2023, which was held in Gandhinagar, India, during February 9-11, 2023.The 32 papers presented in this volume were carefully reviewed and selected from 67 submissions. The papers were organized in topical sections named: algorithms and optimization; computational geometry; game theory; graph coloring; graph connectivity; graph domination; graph matching; graph partition and graph covering.Table of ContentsStable Approximation Schemes.- A whirlwind tour of intersection graph enumeration.- Graph modification problems with forbidden minors.- Algorithms & Optimization Efficient reductions and algorithms for Subset Product.- Optimal length cutting plane refutations of integer programs.- Fault-Tolerant Dispersion Resource management in device-to-device communications.- Computational Geometry Algorithms for k-Dispersion for Points in Convex Position in the Plane.- Arbitrary oriented color spanning region for line segments.- Games with a Simple Rectilinear Obstacle in Plane.- Diverse Fair Allocations: Complexity and Algorithms.- Graph Coloring New bounds and constructions for neighbor-locating colorings of graphs.- D K 5-list coloring toroidal 6-regular triangulations in linear time.- On Locally Identifying Coloring of Graphs.- On Structural Parameterizations of Star Coloring.- Reddy Perfectness of G-generalized join of graphs.- Coloring of a superclass of 2K2-free graphs.- The Weak (2,2)-Labelling Problem for graphs with forbidden induced structures.- Graph Connectivity Short cycles dictate dichotomy status of the Steiner tree problem on Bisplit graphs.- Some insights on dynamic maintenance of Gomory-Hu tree in cactus graphs and general graphs.- Monitoring edge-geodetic sets in graphs.- Cyclability, Connectivity and Circumference.- Graph Domination On three domination-based identification problems in block graphs.- Graph modification problems with forbidden minors.- Computational Aspects of Double Dominating Sequences in Graph.- Relation between broadcast domination and multipacking numbers on chordal graphs.- Pushing Cops and Robber on Oriented Graphs.- Mind the Gap: Edge Facility Location Problems in Theory and Practice.- Complexity Results on Cosecure Domination in Graphs.- Kusum and Arti Pandey Graph Matching Latin Hexahedra and Related Combinatorial Structures.- Minimum Maximal Acyclic Matching in Proper Interval Graphs.- Graph Partition & Graph Covering Transitivity on subclasses of chordal graphs.- Maximum subgraph problem for 3-regular Knödel graphs and its wirelength.- Covering using Bounded Size Subgraphs.- Axiomatic characterization of the the toll walk function of some graph classes.- Structural Parameterization of Alliance Problems.

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Book SynopsisThis book constitutes the refereed post-conference proceedings of the workshops held at the 16th Asian Conference on Computer Vision, ACCV 2022, which took place in Macao, China, in December 2022. The 25 papers included in this book were carefully reviewed and selected from 40 submissions. They have been organized in topical sections as follows: Learning with limited data for face analysis; adversarial machine learning towards advanced vision systems; computer vision for medical computing; machine learning and computing for visual semantic analysis; vision transformers theory and applications; and deep learning-based small object detection from images and videos.Table of ContentsLearning with Limited Data for Face Analysis.- FAPN: Face Alignment Propagation Network for Face Video Super-Resolution.- Micro-expression recognition using a shallow ConvLSTM-based network.- Adversarial Machine Learning towards Advanced Vision Systems.- ADVFilter: Adversarial Example Generated by Perturbing Optical Path.- Enhancing Federated Learning Robustness Through clustering Non-IID Features.- Towards Improving the Anti-attack Capability of the RangeNet++.- Computer Vision for Medical Computing.- Ensemble Model of Visual Transformer and CNN Helps BA Diagnosis for Doctors in Underdeveloped Areas.- Understanding Tumor Micro Environment using Graph theory.- Handling Domain Shift for Lesion Detection via Semi-Supervised Domain Adaptation.- Photorealistic Facial Wrinkles Removal.- Improving Segmentation of Breast Arterial Calcifications from Digital Mammography: Good Annotation Is All You Need.- Machine Learning and Computing for Visual Semantic Analysis.- Towards Scene Understanding for Autonomous Operations on Airport Aprons.- Lightweight Hyperspectral Image Reconstruction Network with Deep Feature Hallucination.- A Transformer-based Model for Preoperative Early Recurrence Prediction of Hepatocellular Carcinoma with Muti-p.- CaltechFN: Distorted and Partially Occluded Digits.- Temporal Extension Topology Learning for Video-based Person Re-Identification.- Deep RGB-driven Learning Network for Unsupervised Hyperspectral Image Super-resolution.- Gift from nature: Potential Energy Minimization for explainable dataset distillation.- Object Centric Point Sets Feature Learning with Matrix Decomposition.- Aerial Image Segmentation via Noise Dispelling and Content Distilling.- Vision Transformers Theory and Applications.- Temporal Cross-attention for Action Recognition.- Transformer Based Motion In-Betweening.- Convolutional point Transformer.- Cross-Attention Transformer for Video Interpolation.- Deep Learning-Based Small Object Detection from Images and Videos.- Evaluating and Bench-marking Object Detection Models for Traffic Sign and Traffic Light Datasets.- Exploring Spatial-temporal Instance Relationships In an Intermediate Domain For Image-to-video Object Detection.

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Book SynopsisThis book constitutes selected papers presented during the two events: the First Forum, GranDGamesBR 2020, held in Recife, Brazil, in November 2020, and the Second Forum, GranDGamesBR 2021, held in Gramado, Brazi, in October 2021.The 12 papers presented were thoroughly reviewed and selected from 24 submissions. The topics included in this volume cover the following fields connected to games and entertainment computing: game design, educational games, games evaluation, game-based learning, player experience, human-computer interaction, games industry, business models, game software ecosystems, ethics, serious games, cyberdemocracy, emotional design, computer graphics, cognitive simulation, immersive entertainment, virtual/augmented/extended reality, gamification, and creative process.Table of ContentsChallenges in Evaluating Players’ Interaction with Digital Games.- The pursuit of fun in digital games: From the sandpit to the console and beyond.- Business Model for Indie Studios in Game Software Ecosystems.- Games as Mediating Platforms in an Open and Digital World.- Balancing Game Elements, Learning, and Emotions in Game Design.- Enhancing Students’ Learning Experience through Gamification: Perspectives and Challenges.- Ethics and Games, ethical games and ethics in game.- Challenges for XR in Games.- Stimulation of the Executive Functions Mediated by Digital Games: Current Challenges in the School Context.- Perceptual Analysis of Computer Graphics Characters in Digital Entertainment.- Nine Challenges for Immersive Entertainment.- Strategies to Promote Stakeholders’ Autonomy while Creating Educational Digital Games.

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Book SynopsisPixInsight has taken the astro-imaging world by storm. As the first comprehensive postprocessing platform to be created by astro-imagers for astro-imagers, it has for many replaced other generic graphics editors as the software of choice. PixInsight has been embraced by professionals such as the James Webb (and Hubble) Space Telescope's science imager Joseph DePasquale and Calar Alto's Vicent Peris, as well as thousands of amateurs around the world. While PixInsight is extremely powerful, very little has been printed on the subject. The first edition of this book broke that mold, offering a comprehensive look into the software’s capabilities. This second edition expands on the several new processes added to the PixInsight platform since that time, detailing and demonstrating each one with a now-expanded workflow. Addressing topics such as PhotometricColorCalibration, Large-Scale Pixel Rejection, LocalNormalization and a host of other functions, this text remains the authoritative guide to PixInsight.Table of ContentsPreface.- Acknowledgements.- About the Author.- Part 1: Preprocessing.- Chapter 1: Image Evaluation.- Chapter 2: Calibration and Integration.- Chapter 3: Cosmetic Correction.- Chapter 4: One-Shot Color.- Chapter 5: Star Alignment.- Chapter 6: Image Integration.- Chapter 7: Batch Preprocessing.- Part 2: Linear Post-Processing.- Chapter 8: File Preparation.- Chapter 9: Background Modelization.- Chapter 10: Introduction to Masks.- Chapter 11: Deconvolution.- Chapter 12: Linear Color Processing and Noise Reduction.- Part 3: Nonlinear Post-Processing.- Chapter 13: Delinearization and LRGB Combination.- Chapter 14: A Look Back.- Chapter 15: Nonlinear Noise Reduction.- Chapter 16: High Dynamic Range Compression.- Chapter 17: Contrast and Sharpness.- Chapter 18: Color Saturation.- Chapter 19: Fine Finishers.- Chapter 20: Archiving and Exporting.- Chapter 21: Learning by Example: One-Shot Color and Monochromatic Workflow.- Part 4: Special Processing.- Chapter 22: Multiscale, Drizzle, High Dynamic Range, and Comet Techniques.- Chapter 23: Narrowband Processing.- Chapter 24: Mosaic Processing.- Chapter 25: More Insight.- Afterword.- Index.

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Book SynopsisThis book publishes a collection of original scientific research articles that address the state-of-art in using partial differential equations for image and signal processing. Coverage includes: level set methods for image segmentation and construction, denoising techniques, digital image inpainting, image dejittering, image registration, and fast numerical algorithms for solving these problems. Table of ContentsDigital Image Inpainting, Image Dejittering, and Optical Flow Estimation.- Image Inpainting Using a TV-Stokes Equation.- Error Analysis for H1 Based Wavelet Interpolations.- Image Dejittering Based on Slicing Moments.- CLG Method for Optical Flow Estimation Based on Gradient Constancy Assumption.- Denoising and Total Variation Methods.- On Multigrids for Solving a Class of Improved Total Variation Based Staircasing Reduction Models.- A Method for Total Variation-based Reconstruction of Noisy and Blurred Images.- Minimization of an Edge-Preserving Regularization Functional by Conjugate Gradient Type Methods.- A Newton-type Total Variation Diminishing Flow.- Chromaticity Denoising using Solution to the Skorokhod Problem.- Improved 3D Reconstruction of Interphase Chromosomes Based on Nonlinear Diffusion Filtering.- Image Segmentation.- Some Recent Developments in Variational Image Segmentation.- Application of Non-Convex BV Regularization for Image Segmentation.- Region-Based Variational Problems and Normal Alignment – Geometric Interpretation of Descent PDEs.- Fast PCLSM with Newton Updating Algorithm.- Fast Numerical Methods.- Nonlinear Multilevel Schemes for Solving the Total Variation Image Minimization Problem.- Fast Implementation of Piecewise Constant Level Set Methods.- The Multigrid Image Transform.- Minimally Stochastic Schemes for Singular Diffusion Equations.- Image Registration.- Total Variation Based Image Registration.- Variational Image Registration Allowing for Discontinuities in the Displacement Field.- Inverse Problems.- Shape Reconstruction from Two-Phase Incompressible Flow Data using Level Sets.- Reservoir Description Using a Binary Level Set Approach with Additional Prior Information About the Reservoir Model.

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Book SynopsisThis title contains the most up-to-date and comprehensive information on the development of the Charge-Coupled Device (CCD), which makes possible the widespread use of consumer camcorders and broadcasting color cameras. It is comprehensive enough to be of great value to researchers, industrialists and post-graduate students in image technology.Table of ContentsPreface to the Series, Preface, Acknowledgments, 1. Introduction, 2. Structure and Operation of CCD Image Sensor, 3. CCD Area Sensor, 4. The CCD Manufacturing Process, 5. Process Modeling and Simulation with the SPADES Simulator, 6. Imaging and Signal Processing, 7. CCD Camera and Applications, 8. CCD Delay Line and CCD Linear Sensor, 9. Conclusion, References, Index

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Book SynopsisThis book provides a comprehensive review of all aspects relating to visual quality assessment for stereoscopic images, including statistical mathematics, stereo vision and deep learning. It covers the fundamentals of stereoscopic image quality assessment (SIQA), the relevant engineering problems and research significance, and also offers an overview of the significant advances in visual quality assessment for stereoscopic images, discussing and analyzing the current state-of-the-art in SIQA algorithms, the latest challenges and research directions as well as novel models and paradigms. In addition, a large number of vivid figures and formulas help readers gain a deeper understanding of the foundation and new applications of objective stereoscopic image quality assessment technologies.Reviewing the latest advances, challenges and trends in stereoscopic image quality assessment, this book is a valuable resource for researchers, engineers and graduate students working in related fields, including imaging, displaying and image processing, especially those interested in SIQA research.Table of ContentsIntroduction.- Basic of 2D Image Quality Assessment.- The Difference Between 2D IQA and 3D IQA.- Stereoscopic Image Quality Assessment Based on 2D IQA Models.- Stereoscopic Image Quality Assessment Based on Binocular Vision.- Learning Perceptual Quality of Stereopsis from Human Visual Properties.- Stereoscopic Image Quality Assessment Based on Deep Convolutional Neural Models.- Summary and Future Directions.

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Book SynopsisThe information presented in this book will startle the world. For centuries, the authenticity of the Holy Shroud has been argued about. Skeptics push their negative opinion based on a few highly questionable clues, while the authenticists continue to detect new facts confirming that the Relic wrapped the corpse of Jesus Christ and that the body image impressed on it was produced by a source of energy generated during the Resurrection.What is world-changing is that to explain this "impossible image" of a tortured and crucified man, the book presents a startling new hypothesis, the "Divine Photograph" taken at the instant of the Resurrection, based on a phenomenon, the "Miracle of the Holy Fire" that manifests on every Holy Saturday at the Holy Sepulcher in Jerusalem. As this amazing relationship becomes more broadly known, the world will be shocked.Table of Contents1. The Miracle of the Holy Fire 2. Miracle of the Holy Fire, History and Religious Significance 3. Science Investigates the Holy Fire 4. The Holy Shroud and the Impossible Image 5. The Divine Photography 6. Conclusion

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Book SynopsisThis book describes the principles of image and video compression techniques and introduces current and popular compression standards, such as the MPEG series. Derivations of relevant compression algorithms are developed in an easy-to-follow fashion. Numerous examples are provided in each chapter to illustrate the concepts.Table of ContentsPreface. 1 Introduction. 1.1 What is Source Coding? 1.2 Why is Compression Necessary? 1.3 Image and Video Compression Techniques. 1.4 Video Compression Standards. 1.5 Organization of the Book. 1.6 Summary. References. 2 Image Acquisition. 2.1 Introduction. 2.2 Sampling a Continuous Image. 2.3 Image Quantization. 2.4 Color Image Representation. 2.5 Summary. References. Problems. 3 Image Transforms. 3.1 Introduction. 3.2 Unitary Transforms. 3.3 Karhunen–Loeve Transform. 3.4 Properties of Unitary Transforms. 3.5 Summary. References. Problems. 4 Discrete Wavelet Transform. 4.1 Introduction. 4.2 Continuous Wavelet Transform. 4.3 Wavelet Series. 4.4 Discrete Wavelet Transform. 4.5 Efficient Implementation of 1D DWT. 4.6 Scaling and Wavelet Filters. 4.7 Two-Dimensional DWT. 4.8 Energy Compaction Property. 4.9 Integer or Reversible Wavelet. 4.10 Summary. References. Problems. 5 Lossless Coding. 5.1 Introduction. 5.2 Information Theory. 5.3 Huffman Coding. 5.4 Arithmetic Coding. 5.5 Golomb–Rice Coding. 5.6 Run–Length Coding. 5.7 Summary. References. Problems. 6 Predictive Coding. 6.1 Introduction. 6.2 Design of a DPCM. 6.3 Adaptive DPCM. 6.4 Summary. References. Problems. 7 Image Compression in the Transform Domain. 7.1 Introduction. 7.2 Basic Idea Behind Transform Coding. 7.3 Coding Gain of a Transform Coder. 7.4 JPEG Compression. 7.5 Compression of Color Images. 7.6 Blocking Artifact. 7.7 Variable Block Size DCT Coding. 7.8 Summary. References. Problems. 8 Image Compression in the Wavelet Domain. 8.1 Introduction. 8.2 Design of a DWT Coder. 8.3 Zero-Tree Coding. 8.4 JPEG2000. 8.5 Digital Cinema. 8.6 Summary. References. Problems. 9 Basics of Video Compression. 9.1 Introduction. 9.2 Video Coding. 9.3 Stereo Image Compression. 9.4 Summary. References. Problems. 10 Video Compression Standards. 10.1 Introduction. 10.2 MPEG-1 and MPEG-2 Standards. 10.3 MPEG-4. 10.4 H.264. 10.5 Summary. References. Problems. Index.

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Book SynopsisProgrammers, scientists, and engineers are always in need of newer techniques and algorithms to manipulate and interpret images. Algorithms for Image Processing and Computer Vision is an accessible collection of algorithms for common image processing applications that simplifies complicated mathematical calculations.Table of ContentsPreface xxi Chapter 1 Practical Aspects of a Vision System — Image Display, Input/Output, and Library Calls 1 OpenCV 2 The Basic OpenCV Code 2 The IplImage Data Structure 3 Reading and Writing Images 6 Image Display 7 An Example 7 Image Capture 10 Interfacing with the AIPCV Library 14 Website Files 18 References 18 Chapter 2 Edge-Detection Techniques 21 The Purpose of Edge Detection 21 Traditional Approaches and Theory 23 Models of Edges 24 Noise 26 Derivative Operators 30 Template-Based Edge Detection 36 Edge Models: The Marr-Hildreth Edge Detector 39 The Canny Edge Detector 42 The Shen-Castan (ISEF) Edge Detector 48 A Comparison of Two Optimal Edge Detectors 51 Color Edges 53 Source Code for the Marr-Hildreth Edge Detector 58 Source Code for the Canny Edge Detector 62 Source Code for the Shen-Castan Edge Detector 70 Website Files 80 References 82 Chapter 3 Digital Morphology 85 Morphology Defined 85 Connectedness 86 Elements of Digital Morphology — Binary Operations 87 Binary Dilation 88 Implementing Binary Dilation 92 Binary Erosion 94 Implementation of Binary Erosion 100 Opening and Closing 101 MAX — A High-Level Programming Language for Morphology 107 The ‘‘Hit-and-Miss’’ Transform 113 Identifying Region Boundaries 116 Conditional Dilation 116 Counting Regions 119 Grey-Level Morphology 121 Opening and Closing 123 Smoothing 126 Gradient 128 Segmentation of Textures 129 Size Distribution of Objects 130 Color Morphology 131 Website Files 132 References 135 Chapter 4 Grey-Level Segmentation 137 Basics of Grey-Level Segmentation 137 Using Edge Pixels 139 Iterative Selection 140 The Method of Grey-Level Histograms 141 Using Entropy 142 Fuzzy Sets 146 Minimum Error Thresholding 148 Sample Results From Single Threshold Selection 149 The Use of Regional Thresholds 151 Chow and Kaneko 152 Modeling Illumination Using Edges 156 Implementation and Results 159 Comparisons 160 Relaxation Methods 161 Moving Averages 167 Cluster-Based Thresholds 170 Multiple Thresholds 171 Website Files 172 References 173 Chapter 5 Texture and Color 177 Texture and Segmentation 177 A Simple Analysis of Texture in Grey-Level Images 179 Grey-Level Co-Occurrence 182 Maximum Probability 185 Moments 185 Contrast 185 Homogeneity 185 Entropy 186 Results from the GLCM Descriptors 186 Speeding Up the Texture Operators 186 Edges and Texture 188 Energy and Texture 191 Surfaces and Texture 193 Vector Dispersion 193 Surface Curvature 195 Fractal Dimension 198 Color Segmentation 201 Color Textures 205 Website Files 205 References 206 Chapter 6 Thinning 209 What Is a Skeleton? 209 The Medial Axis Transform 210 Iterative Morphological Methods 212 The Use of Contours 221 Choi/Lam/Siu Algorithm 224 Treating the Object as a Polygon 226 Triangulation Methods 227 Force-Based Thinning 228 Definitions 229 Use of a Force Field 230 Subpixel Skeletons 234 Source Code for Zhang-Suen/Stentiford/Holt Combined Algorithm 235 Website Files 246 References 247 Chapter 7 Image Restoration 251 Image Degradations — The Real World 251 The Frequency Domain 253 The Fourier Transform 254 The Fast Fourier Transform 256 The Inverse Fourier Transform 260 Two-Dimensional Fourier Transforms 260 Fourier Transforms in OpenCV 262 Creating Artificial Blur 264 The Inverse Filter 270 The Wiener Filter 271 Structured Noise 273 Motion Blur — A Special Case 276 The Homomorphic Filter — Illumination 277 Frequency Filters in General 278 Isolating Illumination Effects 280 Website Files 281 References 283 Chapter 8 Classification 285 Objects, Patterns, and Statistics 285 Features and Regions 288 Training and Testing 292 Variation: In-Class and Out-Class 295 Minimum Distance Classifiers 299 Distance Metrics 300 Distances Between Features 302 Cross Validation 304 Support Vector Machines 306 Multiple Classifiers — Ensembles 309 Merging Multiple Methods 309 Merging Type 1 Responses 310 Evaluation 311 Converting Between Response Types 312 Merging Type 2 Responses 313 Merging Type 3 Responses 315 Bagging and Boosting 315 Bagging 315 Boosting 316 Website Files 317 References 318 Chapter 9 Symbol Recognition 321 The Problem 321 OCR on Simple Perfect Images 322 OCR on Scanned Images — Segmentation 326 Noise 327 Isolating Individual Glyphs 329 Matching Templates 333 Statistical Recognition 337 OCR on Fax Images — Printed Characters 339 Orientation — Skew Detection 340 The Use of Edges 345 Handprinted Characters 348 Properties of the Character Outline 349 Convex Deficiencies 353 Vector Templates 357 Neural Nets 363 A Simple Neural Net 364 A Backpropagation Net for Digit Recognition 368 The Use of Multiple Classifiers 372 Merging Multiple Methods 372 Results From the Multiple Classifier 375 Printed Music Recognition — A Study 375 Staff Lines 376 Segmentation 378 Music Symbol Recognition 381 Source Code for Neural Net Recognition System 383 Website Files 390 References 392 Chapter 10 Content-Based Search — Finding Images by Example 395 Searching Images 395 Maintaining Collections of Images 396 Features for Query by Example 399 Color Image Features 399 Mean Color 400 Color Quad Tree 400 Hue and Intensity Histograms 401 Comparing Histograms 402 Requantization 403 Results from Simple Color Features 404 Other Color-Based Methods 407 Grey-Level Image Features 408 Grey Histograms 409 Grey Sigma — Moments 409 Edge Density — Boundaries Between Objects 409 Edge Direction 410 Boolean Edge Density 410 Spatial Considerations 411 Overall Regions 411 Rectangular Regions 412 Angular Regions 412 Circular Regions 414 Hybrid Regions 414 Test of Spatial Sampling 414 Additional Considerations 417 Texture 418 Objects, Contours, Boundaries 418 Data Sets 418 Website Files 419 References 420 Systems 424 Chapter 11 High-Performance Computing for Vision and Image Processing 425 Paradigms for Multiple-Processor Computation 426 Shared Memory 426 Message Passing 427 Execution Timing 427 Using clock() 428 Using QueryPerformanceCounter 430 The Message-Passing Interface System 432 Installing MPI 432 Using MPI 433 Inter-Process Communication 434 Running MPI Programs 436 Real Image Computations 437 Using a Computer Network — Cluster Computing 440 A Shared Memory System — Using the PC Graphics Processor 444 GLSL 444 OpenGL Fundamentals 445 Practical Textures in OpenGL 448 Shader Programming Basics 451 Vertex and Fragment Shaders 452 Required GLSL Initializations 453 Reading and Converting the Image 454 Passing Parameters to Shader Programs 456 Putting It All Together 457 Speedup Using the GPU 459 Developing and Testing Shader Code 459 Finding the Needed Software 460 Website Files 461 References 461 Index 465

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Book SynopsisDescribes the operating principles of analog MOS integrated circuits and how to design and use such circuits. The initial section explores general properties of analog MOS integrated circuits and the math and physics background required. The remainder of the book is devoted to the design of circuits.Table of ContentsTransformation Methods. MOS Devices as Circuit Elements. MOS Operational Amplifiers. Switched-Capacitor Filters. Nonfiltering Applications of Switched-Capacitor Circuits. Nonideal Effects in Switched-Capacitor Circuits. Systems Considerations and Applications. Index.

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Book SynopsisA proven, cost-effective approach to solving analog signal processing design problems Most design problems involving analog circuits require a great deal of creativity to solve. But, as the authors of this groundbreaking guide demonstrate, finding solutions to most analog signal processing problems does not have to be that difficult. Analog Signal Processing presents an original, five-step, design-oriented approach to solving analog signal processing problems using standard ICs as building blocks. Unlike most authors who prescribe a bottom-up approach, Professors Pallás-Areny and Webster cast design problems first in functional terms and then develop possible solutions using available ICs, focusing on circuit performance rather than internal structure. The five steps of their approach move from signal classification, definition of desired functions, and description of analog domain conversions to error classification and error analysis. Featuring 90 worked exTable of ContentsSignals and Signal Processing. Voltage Amplification. Current-to-Voltage and Voltage-to-Current Conversion. Linear Analog Functions. AC/DC Signal Conversion. Other Nonlinear Analog Functions. Analog Signal Filtering. Analog Signal Switching, Multiplexing and Sampling. Error Analysis and Reduction. Interference and Its Reduction. Noise, Drift and Their Reduction. Appendices. Index.

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Book SynopsisUsing a pedagogical style along with detailed proofs and illustrative examples, this book opens a view to the largely unexplored area of nonlinear systems with uncertainties. The focus is on adaptive nonlinear control results introduced with the new recursive design methodology--adaptive backstepping.Table of ContentsSTATE FEEDBACK. Design Tools for Stabilization. Adaptive Backstepping Design. Tuning Functions Design. Modular Design with Passive Identifiers. Modular Design with Swapping Identifiers. OUTPUT FEEDBACK. Output-Feedback Design Tools. Tuning Functions Designs. Modular Designs. Linear Systems. Appendices. Bibliography. Index.

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Book SynopsisA comprehensive, practical and up-to-date exposition on digital signal processing. Both mathematical and useful, this book uses a rigorous approach to help readers learn the theory and practice of DSP. It discusses practical spectral analysis, including the use of windows for spectral analysis, sinusoidal signal analysis, and the effect of noise.Table of ContentsReview of Frequency-Domain Analysis. Sampling and Reconstruction. The Discrete Fourier Transform. The Fast Fourier Transform. Practical Spectral Analysis. Review of z-Transforms and Difference Equations. Introduction to Digital Filters. Finite Impulse Response Filters. Infinite Impulse Response Filters. Digital Filter Realization and Implementation. Multirate Signal Processing. Analysis and Modeling of Random Signals. Digital Signal Processing Applications. Bibliography. Index.

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Book SynopsisA readable, understandable introduction to DSP for professionals and students alike... This practical guide is a welcome alternative to more complicated introductions to DSP.Table of ContentsThe Development of Digital Signal Processing. Why Do It Digitally Anyway? Converting Analog to Digital. Filtering. Transforming Signals into the Frequency Domain. Encoding of Waveforms-Increasing the Channel Bandwidth. Practical DSP Hardware Design Issues. DSP System Design Flow. Glossary of Acronyms. Index.

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Book SynopsisAn up-to-date analysis of the SAR wavefront reconstruction signal theory and its digital implementation. With the advent of fast computing and digital information processing techniques, synthetic aperture radar (SAR) technology has become both more powerful and more accurate.Table of ContentsRange Imaging. Cross-Range Imaging. SAR Radiation Pattern. Generic Synthetic Aperture Radar. Spotlight Synthetic Aperture Radar. Stripmap Synthetic Aperture Radar. Circular Synthetic Aperture Radar. Monopulse Synthetic Aperture Radar. Bibliography. Index.

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Book SynopsisThis text is designed to give students a strong grounding in the mathematical basis of photogrammetry while introducing them to related fields, such as remote sensing and digital image processing.Suitable for undergraduate photogrammetry courses typically aimed at junior and senior students, and for graduate-level courses at the Master''s level. Excellent reference for those working in related fields.Table of Contents1 Introduction 1 2 Elementary Photogrammetry 13 3 Photogrammetric Sensing Systems 33 4 Mathematical Concepts in Photogrammetry 80 5 Resection, Intersection, and Triangulation 107 6 Digital Photogrammetry 152 7 Photogrammetric Instruments 203 8 Photogrammetric Products 225 9 Close-range Photogrammetry 247 10 Analysis of Multispectral and Hyperspectral Image Data 276 11 Active Sensing Systems 301 Appendix A: Mathematics for Photogrammetry 351 Appendix B: Least Squares Adjustment 387 Appendix C: Linearization of Photogrammetric Condition Equations 423 Appendix D: Mathematical Description of Linear Features 433 Appendix E: Further Consideration of the Rotation Matrix 446 Appendix F: Orbital Photogrammetry 455 Appendix G: Software of Photogrammetric Applications 464 Index 473

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Book SynopsisThe explosive growth of multimedia data transmission has generated a critical need for efficient, high-capacity image databases, as well as powerful search engines to retrieve image data from them. This book brings together contributions by an international all-star team of innovators in the field who share their insights into all key aspects of image database and search engine construction. Readers get in-depth discussions of the entire range of crucial image database architecture, indexing and retrieval, transmission, display, and user interface issues. And, using examples from an array of disciplines, the authors present cutting-edge applications in medical imagery, multimedia communications, earth science, remote sensing, and other major application areas.Table of ContentsContributors. Preface. Introduction. Digital Imagery: Fundamentals (V. Castelli & L. Bergman). SELECTED APPLICATION. Visible Image Retrieval (C. Colombo & A. Del Bimbo). Satellite Imagery in Earth Science Applications (H. Ramapriyan). Medical Imagery (S. Wong & K. Hoo). Images in the Exploration for Oil and Gas (P. Tilke). STORAGE AND SYSTEM ARCHITECTURE. Storage Architectures for Digital Imagery (H. Vin). Database Support for Multimedia Applications (M. Ortega-Binderberger and K. Chakrabarti). Image Compression--A Review (S. Hemami). Transmission of Digital Imagery (J. Percival). INDEXING AND RETRIEVAL. Introduction to Content-Based Image Retrieval-Overview of Key Techniques (Y. Li and C. Kuo). Color for Image Retrieval (J. Smith). Texture Features for Image Retreival (B. Manjunath & W. Ma). Shape Representation for Image Retrieval (B. Kimia). Multidimensional Indexing Structures for Content-Based Retrieval (V. Castelli). Multimedia Indexing (C. Faloutsos). Compressed or Progressive Image Search (S. Panchanathan). Concepts and Techniques for Indexing Visual Semantics (A. Jaimes & S. Chang). Index.

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Book SynopsisThis book responds to the dramatic growth in digital signal processing (DSP) over the past decade. While its focal point is signal modeling, the book integrates and explores the relationships of signal modeling to the important problems of optimal filtering, spectral estimation, and adaptive filtering.Table of ContentsBackground. Discrete-Time Random Processes. Signal Modeling. The Levinson Recursion. Lattice Filters. Wiener Filtering. Spectrum Estimation. Adaptive Filtering. Appendix. Table of Symbols. Index.

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Book SynopsisA concise introduction to the design and analysis of digital signal processors. Unique in its presentation of advanced topics at the undergraduate level. Contains excellent graphics and includes coverage of the A/D-digital filter and D/A structures of digital systems. Each chapter includes many carefully worked-out examples and concludes with a summary and problems.Table of ContentsFundamentals of Discrete-Time Systems. The Z-Transform. Analog Filter Design. Digital Filter Design. Realizations of Filters. The Discrete Fourier Transform.

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