Handbook of machine and computer vision : the guide for developers and users

Handbook of machine and computer vision the guide for developers and users

Detalles Bibliográficos
Otros Autores: Hornberg, Alexander, editor (editor)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Weinheim, Germany : Wiley-VCH 2017.
Edición:Second, revised and updated edition
Materias:
Computer vision > Handbooks, manuals, etc.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009849074206719
Tabla de Contenidos:
  • Cover
  • Title Page
  • Copyright
  • Contents
  • Preface Second Edition
  • Preface First Edition
  • List of Contributors
  • Chapter 1 Processing of Information in the Human Visual System
  • 1.1 Preface
  • 1.2 Design and Structure of the Eye
  • 1.3 Optical Aberrations and Consequences for Visual Performance
  • 1.4 Chromatic Aberration
  • 1.5 Neural Adaptation to Monochromatic Aberrations
  • 1.6 Optimizing Retinal Processing with Limited Cell Numbers, Space, and Energy
  • 1.7 Adaptation to Different Light Levels
  • 1.8 Rod and Cone Responses
  • 1.9 Spiking and Coding
  • 1.10 Temporal and Spatial Performance
  • 1.11 ON/OFF Structure, Division of the Whole Illuminance Amplitude
  • 1.12 Consequences of the Rod and Cone Diversity on Retinal Wiring
  • 1.13 Motion Sensitivity in the Retina
  • 1.14 Visual Information Processing in Higher Centers
  • 1.14.1 Morphology
  • 1.14.2 Functional Aspects - Receptive Field Structures and Cortical Modules
  • 1.15 Effects of Attention
  • 1.16 Color Vision, Color Constancy, and Color Contrast
  • 1.17 Depth Perception
  • 1.18 Adaptation in the Visual System to Color, Spatial, and Temporal Contrast
  • 1.19 Conclusions
  • Acknowledgements
  • References
  • Chapter 2 Introduction to Building a Machine Vision Inspection
  • 2.1 Preface
  • 2.2 Specifying a Machine Vision System
  • 2.2.1 Task and Benefit
  • 2.2.2 Parts
  • 2.2.3 Part Presentation
  • 2.2.4 Performance Requirements
  • 2.2.5 Information Interfaces
  • 2.2.6 Installation Space
  • 2.2.7 Environment
  • 2.2.8 Checklist
  • 2.3 Designing a Machine Vision System
  • 2.3.1 Camera Type
  • 2.3.2 Field of View
  • 2.3.3 Resolution
  • 2.3.4 Choice of Camera, Frame Grabber, and Hardware Platform
  • 2.3.5 Lens Design
  • 2.3.6 Choice of Illumination
  • 2.3.7 Mechanical Design
  • 2.3.8 Electrical Design
  • 2.3.9 Software
  • 2.4 Costs
  • 2.5 Words on Project Realization.
  • 2.5.1 Development and Installation
  • 2.5.2 Test Run and Acceptance Test
  • 2.5.3 Training and Documentation
  • 2.6 Examples
  • 2.6.1 Diameter Inspection of Rivets
  • 2.6.2 Tubing Inspection
  • Chapter 3 Lighting in Machine Vision
  • 3.1 Introduction
  • 3.1.1 Prologue
  • 3.1.2 The Involvement of Lighting in the Complex Machine Vision Solution
  • 3.2 Demands on Machine Vision lighting
  • 3.3 Light used in Machine Vision
  • 3.3.1 What is Light? Axioms of Light
  • 3.3.2 Light and Light Perception
  • 3.3.3 Light Sources for Machine Vision
  • 3.3.4 The Light Sources in Comparison
  • 3.3.5 Considerations for Light Sources: Lifetime, Aging, Drift
  • 3.4 Interaction of Test Object and Light
  • 3.4.1 Risk Factor Test Object
  • 3.4.2 Light Color and Part Color
  • 3.5 Basic Rules and Laws of Light Distribution
  • 3.5.1 Basic Physical Quantities of Light
  • 3.5.2 The Photometric Inverse Square Law
  • 3.5.3 The Constancy of Luminance
  • 3.5.4 What Light Arrives at the Sensor - Light Transmission Through the Lens
  • 3.5.5 Light Distribution of Lighting Components
  • 3.5.6 Contrast
  • 3.5.7 Exposure
  • 3.6 Light Filters
  • 3.6.1 Characteristic Values of Light Filters
  • 3.6.2 Influences of Light Filters on the Optical Path
  • 3.6.3 Types of Light Filters
  • 3.6.4 Anti-Reflective Coatings (AR)
  • 3.6.5 Light Filters for Machine Vision
  • 3.7 Lighting Techniques and Their Use
  • 3.7.1 How to Find a Suitable Lighting?
  • 3.7.2 Planning the Lighting Solution - Influence Factors
  • 3.7.3 Lighting Systematics
  • 3.7.4 The Lighting Techniques in Detail
  • 3.7.5 Combined Lighting Techniques
  • 3.8 Lighting Control
  • 3.8.1 Reasons for Light Control - The Environmental Industrial Conditions
  • 3.8.2 Electrical Control
  • 3.8.3 Geometrical Control
  • 3.8.4 Suppression of Ambient and Extraneous Light - Measures for a Stable Lighting
  • 3.9 Lighting Perspectives for the Future.
  • References
  • Chapter 4 Optical Systems in Machine Vision
  • 4.1 A Look at the Foundations of Geometrical Optics
  • 4.1.1 From Electrodynamics to Light Rays
  • 4.1.2 Basic Laws of Geometrical Optics
  • 4.2 Gaussian Optics
  • 4.2.1 Reflection and Refraction at the Boundary between two Media
  • 4.2.2 Linearizing the Law of Refraction - The Paraxial Approximation
  • 4.2.3 Basic Optical Conventions
  • 4.2.4 Cardinal Elements of a Lens in Gaussian Optics
  • 4.2.5 Thin Lens Approximation
  • 4.2.6 Beam-Converging and Beam-Diverging Lenses
  • 4.2.7 Graphical Image Constructions
  • 4.2.8 Imaging Equations and Their Related Coordinate Systems
  • 4.2.9 Overlapping of Object and Image Space
  • 4.2.10 Focal Length, Lateral Magnification, and the Field of View
  • 4.2.11 Systems of Lenses
  • 4.2.12 Consequences of the Finite Extension of Ray Pencils
  • 4.2.13 Geometrical Depth of Field and Depth of Focus
  • 4.2.14 Laws of Central Projection-Telecentric System
  • 4.3 Wave Nature of Light
  • 4.3.1 Introduction
  • 4.3.2 Rayleigh-Sommerfeld Diffraction Integral
  • 4.3.3 Further Approximations to the Huygens-Fresnel Principle
  • 4.3.4 Impulse Response of an Aberration-Free Optical System
  • 4.3.5 Intensity Distribution in the Neighborhood of the Geometrical Focus
  • 4.3.6 Extension of the Point Spread Function in a Defocused Image Plane
  • 4.3.7 Consequences for the Depth of Field Considerations
  • 4.4 Information Theoretical Treatment of Image Transfer and Storage
  • 4.4.1 Physical Systems as Linear Invariant Filters
  • 4.4.2 Optical Transfer Function (OTF) and the Meaning of Spatial Frequency
  • 4.4.3 Extension to the Two-Dimensional Case
  • 4.4.4 Impulse Response and MTF for Semiconductor Imaging Devices
  • 4.4.5 Transmission Chain
  • 4.4.6 Aliasing Effect and the Space-Variant Nature of Aliasing
  • 4.5 Criteria for Image Quality
  • 4.5.1 Gaussian Data.
  • 4.5.2 Overview on Aberrations of the Third Order
  • 4.5.3 Image Quality in the Space Domain: PSF, LSF, ESF, and Distortion
  • 4.5.4 Image Quality in the Spatial Frequency Domain: MTF
  • 4.5.5 Other Image Quality Parameters
  • 4.5.6 Manufacturing Tolerances and Image Quality
  • 4.6 Practical Aspects: How to Specify Optics According to the Application Requirements?
  • 4.6.1 Example for the Calculation of an Imaging Constellation
  • References
  • Chapter 5 Camera Calibration
  • 5.1 Introduction
  • 5.2 Terminology
  • 5.2.1 Camera, Camera System
  • 5.2.2 Coordinate Systems
  • 5.2.3 Interior Orientation and Calibration
  • 5.2.4 Exterior and Relative Orientation
  • 5.2.5 System Calibration
  • 5.3 Physical Effects
  • 5.3.1 Optical System
  • 5.3.2 Camera and Sensor Stability
  • 5.3.3 Signal Processing and Transfer
  • 5.4 Mathematical Calibration Model
  • 5.4.1 Central Projection
  • 5.4.2 Camera Model
  • 5.4.3 Focal Length and Principal Point
  • 5.4.4 Distortion and Affinity
  • 5.4.5 Radial Symmetrical Distortion
  • 5.4.6 Radial Asymmetrical and Tangential Distortion
  • 5.4.7 Affinity and Nonorthogonality
  • 5.4.8 Variant Camera Parameters
  • 5.4.9 Sensor Flatness
  • 5.4.10 Other Parameters
  • 5.5 Calibration and Orientation Techniques
  • 5.5.1 In the Laboratory
  • 5.5.2 Using Bundle Adjustment to Determine Camera Parameters
  • 5.5.3 Other Techniques
  • 5.6 Verification of Calibration Results
  • 5.7 Applications
  • 5.7.1 Applications with Simultaneous Calibration
  • 5.7.2 Applications with Precalibrated Cameras
  • References
  • Chapter 6 Camera Systems in Machine Vision
  • 6.1 Camera Technology
  • 6.1.1 History in Brief
  • 6.1.2 Machine Vision versus Closed Circuit TeleVision (CCTV)
  • 6.2 Sensor Technologies
  • 6.2.1 Spatial Differentiation: 1D and 2D
  • 6.2.2 CCD Technology
  • 6.2.3 CMOS Image Sensor
  • 6.2.4 MATRIX VISION Available Cameras.
  • 6.3 Block Diagrams and Their Description
  • 6.3.1 Block Diagram of SONY Progressive Scan Analog Camera
  • 6.3.2 Block Diagram of Color Camera with Digital Image Processing
  • 6.4 mvBlueCOUGAR-X Line of Cameras
  • 6.4.1 Black and White Digital Camera mvBlueCOUGAR-X Camera Series
  • 6.4.2 Color Camera mvBlueCOUGAR-X Family
  • 6.4.3 Controlling Image Capture
  • 6.4.4 Acquisition and Trigger Modes
  • 6.4.5 Data Transmission
  • 6.4.6 Pixel Data
  • 6.4.7 Camera Connection
  • 6.4.8 Operating the Camera
  • 6.4.9 HiRose Jack Pin Assignment
  • 6.4.10 Sensor Frame Rates and Bandwidth
  • 6.5 Configuration of a GigE Vision Camera
  • 6.6 Qualifying Cameras and Noise Measurement (Dr. Gert Ferrano MV)
  • 6.6.1 Explanation of the Most Important Measurements
  • 6.7 Camera Noise (by Henning Haider AVT, Updated by Author)
  • 6.7.1 Photon Noise
  • 6.7.2 Dark Current Noise
  • 6.7.3 Fixed Pattern Noise (FPN)
  • 6.7.4 Photo Response Non Uniformity (PRNU)
  • 6.7.5 Reset Noise
  • 6.7.6 1/f Noise (Amplifier Noise)
  • 6.7.7 Quantization Noise
  • 6.7.8 Noise Floor
  • 6.7.9 Dynamic Range
  • 6.7.10 Signal to Noise Ratio
  • 6.7.11 Example 1: SONY IMX-174 Sensor (mvBlueFOX3-2024)
  • 6.7.12 Example 2: CMOSIS CMV2000 (mvBlueCOUGAR-X104)
  • 6.8 Useful Links and Literature
  • 6.9 Digital Interfaces
  • Chapter 7 Smart Camera and Vision Systems Design
  • 7.1 Introduction to Vision System Design
  • 7.2 Definitions
  • 7.3 Smart Cameras
  • 7.3.1 Applications
  • 7.3.2 Component Parts
  • 7.3.3 Programming and Configuring
  • 7.3.4 Environment
  • 7.4 Vision Sensors
  • 7.4.1 Applications
  • 7.4.2 Component Parts
  • 7.4.3 Programming and Configuring
  • 7.4.4 Environment
  • 7.5 Embedded Vision Systems
  • 7.5.1 Applications
  • 7.5.2 Component Parts
  • 7.5.3 Programming and Configuring
  • 7.5.4 Environment
  • 7.6 Conclusion
  • References
  • Further Reading
  • Chapter 8 Camera Computer Interfaces.
  • 8.1 Overview.

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