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More About This Title Handbook of Machine and Computer Vision - TheGuide for Developers and Users 2e
English
Written by expert practitioners from leading companies operating in machine vision, this one-stop handbook guides readers through all aspects of image acquisition and image processing, including optics, electronics and software. The authors approach the subject in terms of industrial applications, elucidating such topics as illumination and camera calibration. Initial chapters concentrate on the latest hardware aspects, ranging from lenses and camera systems to camera-computer interfaces, with the software necessary discussed to an equal depth in later sections. These include digital image basics as well as image analysis and image processing. The book concludes with extended coverage of industrial applications in optics and electronics, backed by case studies and design strategies for the conception of complete machine vision systems. As a result, readers are not only able to understand the latest systems, but also to plan and evaluate this technology.
With more than 500 images and tables to illustrate relevant principles and steps.
English
All contributors to this work are written by practitioners from leading companies which operate in the field of computer vision.
English
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
