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[书籍类资料] Handbook of Machine and Computer Vision:The Guide for Developers and Users

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    2024-5-21 09:46
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    [LV.9]以坛为家II

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    小白

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    发表于 2023-8-29 17:19 | 显示全部楼层 |阅读模式
    这本书是2017版的(第二版),其中06版的我见已经有友友分享过了,这里把17版的也分享上来~
    其中光学、算法相关的知识都有。也有3D的。适合机器视觉领域的初学者以及想要深入研究的朋友们。目录如下

    TABLE OF CONTENTSPreface Second Edition xxiii

    Preface First Edition xxv

    List of Contributors xxvii

    1 Processing of Information in the Human Visual System 1
    Frank Schaeffel

    1.1 Preface 1

    1.2 Design and Structure of the Eye 1

    1.3 Optical Aberrations and Consequences for Visual Performance 3

    1.4 Chromatic Aberration 10

    1.5 Neural Adaptation to Monochromatic Aberrations 11

    1.6 Optimizing Retinal Processing with Limited Cell Numbers, Space, and Energy 11

    1.7 Adaptation to Different Light Levels 12

    1.8 Rod and Cone Responses 14

    1.9 Spiking and Coding 16

    1.10 Temporal and Spatial Performance 17

    1.11 ON/OFF Structure, Division of the Whole Illuminance Amplitude 18

    1.12 Consequences of the Rod and Cone Diversity on RetinalWiring 18

    1.13 Motion Sensitivity in the Retina 19

    1.14 Visual Information Processing in Higher Centers 20

    1.15 Effects of Attention 23

    1.16 Color Vision, Color Constancy, and Color Contrast 23

    1.17 Depth Perception 25

    1.18 Adaptation in the Visual System to Color, Spatial, and Temporal Contrast 26

    1.19 Conclusions 26

    Acknowledgements 28

    References 28

    2 Introduction to Building a Machine Vision Inspection 31
    Axel Telljohann

    2.1 Preface 31

    2.2 Specifying a Machine Vision System 32

    2.3 Designing a Machine Vision System 36

    2.4 Costs 48

    2.5 Words on Project Realization 49

    2.6 Examples 50

    3 Lighting in Machine Vision 63
    Irmgard Jahr

    3.1 Introduction 63

    3.2 Demands on Machine Vision lighting 67

    3.3 Light used in Machine Vision 70

    3.4 Interaction of Test Object and Light 91

    3.5 Basic Rules and Laws of Light Distribution 109

    3.6 Light Filters 121

    3.7 Lighting Techniques and Their Use 131

    3.8 Lighting Control 163

    3.9 Lighting Perspectives for the Future 176

    References 177

    4 Optical Systems in Machine Vision 179
    Karl Lenhardt

    4.1 A Look at the Foundations of Geometrical Optics 179

    4.2 Gaussian Optics 183

    4.3 Wave Nature of Light 235

    4.4 Information Theoretical Treatment of Image Transfer and Storage 252

    4.5 Criteria for Image Quality 277

    4.6 Practical Aspects: How to Specify Optics According to the Application Requirements? 285

    References 289

    5 Camera Calibration 291
    Robert Godding

    5.1 Introduction 291

    5.2 Terminology 292

    5.3 Physical Effects 293

    5.4 Mathematical Calibration Model 295

    5.5 Calibration and Orientation Techniques 302

    5.6 Verification of Calibration Results 308

    5.7 Applications 309

    References 314

    6 Camera Systems in Machine Vision 317
    Horst Mattfeldt

    6.1 Camera Technology 317

    6.2 Sensor Technologies 319

    6.3 Block Diagrams andTheir Description 344

    6.4 mvBlueCOUGAR-X Line of Cameras 354

    6.5 Configuration of a GigE Vision Camera 384

    6.6 Qualifying Cameras and Noise Measurement (Dr. Gert Ferrano MV) 386

    6.7 Camera Noise (by Henning Haider AVT, Updated by Author) 391

    6.8 Useful Links and Literature 394

    6.9 Digital Interfaces 395

    7 Smart Camera and Vision Systems Design 399
    Howard D. Gray and Nate Holmes

    7.1 Introduction to Vision System Design 399

    7.2 Definitions 400

    7.3 Smart Cameras 403

    7.4 Vision Sensors 418

    7.5 Embedded Vision Systems 421

    7.6 Conclusion 425

    References 426

    Further Reading 429

    8 Camera Computer Interfaces 431
    Nate Holmes

    8.1 Overview 431

    8.2 Camera Buses 432

    8.3 Choosing a Camera Bus 459

    8.4 Computer Buses 463

    8.5 Choosing a Computer Bus 471

    8.6 Driver Software 473

    8.7 Features of a Machine Vision System 491

    8.8 Summary 501

    References 502

    9 Machine Vision Algorithms 505
    Carsten Steger

    9.1 Fundamental Data Structures 505

    9.2 Image Enhancement 509

    9.3 Geometric Transformations 532

    9.4 Image Segmentation 540

    9.5 Feature Extraction 552

    9.6 Morphology 560

    9.7 Edge Extraction 579

    9.8 Segmentation and Fitting of Geometric Primitives 602

    9.9 Camera Calibration 613

    9.10 Stereo Reconstruction 631

    9.11 Template Matching 643

    9.12 Optical Character Recognition 672

    References 690

    10 Machine Vision in Manufacturing 699
    Peter Waszkewitz

    10.1 Introduction 699

    10.2 Application Categories 701

    10.3 System Categories 706

    10.4 Integration and Interfaces 715

    10.5 Mechanical Interfaces 716

    10.6 Electrical Interfaces 725

    10.7 Information Interfaces 729

    10.8 Temporal Interfaces 738

    10.9 Human–Machine Interfaces 745

    10.10 3D Systems 753

    10.11 Industrial Case Studies 772

    10.12 Constraints and Conditions 789

    References 796

    Appendix 801

    Index 805



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