Handbook of Machine Vision

by Hornberg, Alexander

• ISBN13: 9783527405848
• ISBN10: 3527405844
• Edition: 1st
• Format: Hardcover
• Copyright: 2006-08-23
• Publisher: Wiley-VCH

Summary

With the demands of quality management and process control in an industrial environment machine vision is becoming an important issue. This handbook of machine vision is written by experts from leading companies in this field. It goes through all aspects of image acquisition and image processing. From the viewpoint of the industrial application the authors also elucidate in topics like illumination or camera calibration. Attention is paid to all hardware aspects, starting from lenses and camera systems to camera-computer interfaces. Besides the detailed hardware descriptions the necessary software is discussed with equal profoundness. This includes sections on digital image basics as well as image analysis and image processing. Finally the user is introduced to general aspects of industrial applications of machine vision, such as case studies and strategies for the conception of complete machine vision systems. With this handbook the reader will be enabled not only to understand up to date systems for machine vision but will also be qualified for the planning and evaluation of such technology.

Author Biography

Alexander Hornberg is Professor for Physics and Photonics at the University of Applied Sciences Esslingen, Germany. He holds a degree in physics and a doctorate in mathematics from the University of Karlsruhe. He started his professional career as development and software engineer for a major industry manufacturer (DUNLOP) in 1989. In 1992 he returned to higher education at the University of Applied Sciences Ulm. Since 1997 he has been working in the field of machine vision at the Technical University of Applied Sciences Esslingen.

Table of Contents

1 Processing of Information in the Human Visual System	1	(34)
Prof. Dr. F. Schaeffel, University of Tübingen
1.1 Preface	1	(1)
1.2 Design and Structure of the Eye	1	(4)
1.3 Optical Aberrations and Consequences for Visual Performance	5	(4)
1.4 Chromatic Aberration	9	(3)
1.5 Neural Adaptation to Monochromatic Aberrations	12	(1)
1.6 Optimizing Retinal Processing with Limited Cell Numbers, Space and Energy	13	(1)
1.7 Adaptation to Different Light Levels	13	(2)
1.8 Rod and Cone Responses	15	(3)
1.9 Spiking and Coding	18	(1)
1.10 Temporal and Spatial Performance	19	(1)
1.11 ON/OFF Structure, Division of the Whole Illuminance Amplitude in Two Segments	20	(1)
1.12 Consequences of the Rod and Cone Diversity on Retinal Wiring	21	(1)
1.13 Motion Sensitivity in the Retina	21	(2)
1.14 Visual Information Processing in Higher Centers	23	(3)
1.14.1 Morphology	23	(1)
1.14.2 Functional Aspects - Receptive Field Structures and Cortical Modules	24	(2)
1.15 Effects of Attention	26	(1)
1.16 Color Vision, Color Constancy, and Color Contrast	27	(1)
1.17 Depth Perception	28	(1)
1.18 Adaptation in the Visual System to Color, Spatial, and Temporal Contrast	29	(1)
1.19 Conclusions	30	(2)
References	32	(3)
2 Introduction to Building a Machine Vision Inspection	35	(38)
Axel Telljohann, Consulting Team Machine Vision (CTMV)
2.1 Preface	35	(1)
2.2 Specifying a Machine Vision System	36	(5)
2.2.1 Task and Benefit	37	(1)
2.2.2 Parts	37	(1)
2.2.2.1 Different Part Types	38	(1)
2.2.3 Part Presentation	38	(1)
2.2.4 Performance Requirements	39	(1)
2.2.4.1 Accuracy	39	(1)
2.2.4.2 Time Performance	39	(1)
2.2.5 Information Interfaces	39	(1)
2.2.6 Installation Space	40	(1)
2.2.7 Environment	41	(1)
2.2.8 Checklist	41	(1)
2.3 Designing a Machine Vision System	41	(15)
2.3.1 Camera Type	41	(1)
2.3.2 Field of View	42	(1)
2.3.3 Resolution	43	(3)
2.3.3.1 Camera Sensor Resolution	44	(1)
2.3.3.2 Spatial Resolution	44	(1)
2.3.3.3 Measurement Accuracy	44	(1)
2.3.3.4 Calculation of Resolution	45	(1)
2.3.3.5 Resolution for a Line Scan Camera	45	(1)
2.3.4 Choice of Camera, Frame Grabber, and Hardware Platform	46	(2)
2.3.4.1 Camera Model	46	(1)
2.3.4.2 Frame Grabber	46	(1)
2.3.4.3 Pixel Rate	46	(1)
2.3.4.4 Hardware Platform	47	(1)
2.3.5 Lens Design	48	(2)
2.3.5.1 Focal Length	48	(1)
2.3.5.2 Lens Flange Focal Distance	49	(1)
2.3.5.3 Extension Tubes	49	(1)
2.3.5.4 Lens Diameter and Sensor Size	50	(1)
2.3.5.5 Sensor Resolution and Lens Quality	50	(1)
2.3.6 Choice of Illumination	50	(3)
2.3.6.1 Concept: Maximize Contrast	51	(1)
2.3.6.2 Illumination Setups	51	(1)
2.3.6.3 Light Sources	52	(1)
2.3.6.4 Approach to the Optimum Setup	52	(1)
2.3.6.5 Interfering Lighting	53	(1)
2.3.7 Mechanical Design	53	(1)
2.3.8 Electrical Design	53	(1)
2.3.9 Software	54	(3)
2.3.9.1 Software Library	54	(1)
2.3.9.2 Software Structure	54	(1)
2.3.9.3 General Topics	55	(1)
2.4 Costs	56	(1)
2.5 Words on Project Realization	57	(1)
2.5.1 Development and Installation	57	(1)
2.5.2 Test Run and Acceptance Test	58	(1)
2.5.3 Training and Documentation	58	(1)
2.6 Examples	58	(15)
2.6.1 Diameter Inspection of Rivets	59	(6)
2.6.1.1 Task	59	(1)
2.6.1.2 Specification	59	(1)
2.6.1.3 Design	60	(5)
2.6.2 Tubing Inspection	65	(8)
2.6.2.1 Task	65	(1)
2.6.2.2 Specification	65	(1)
2.6.2.3 Design	66	(7)
3 Lighting in Machine Vision	73	(132)
I. Jahr, Vision & Control GmbH
3.1 Introduction	73	(5)
3.1.1 Prologue	73	(2)
3.1.2 The Involvement of Lighting in the Complex Machine Vision Solution	75	(3)
3.2 Demands on Machine Vision lighting	78	(4)
3.3 Light used in Machine Vision	82	(23)
3.3.1 What is Light? Axioms of Light	82	(2)
3.3.2 Light and Light Perception	84	(4)
3.3.3 Light Sources for Machine Vision	88	(12)
3.3.3.1 Incandescent Lamps / Halogen Lamps	89	(2)
3.3.3.2 Metal Vapor Lamps	91	(1)
3.3.3.3 Xenon Lamps	92	(1)
3.3.3.4 Fluorescent Lamps	93	(2)
3.3.3.5 LEDs (Light Emitting Diodes)	95	(4)
3.3.3.6 Lasers	99	(1)
3.3.4 The Light Sources in Comparison	100	(1)
3.3.5 Considerations for Light Sources: Lifetime, Aging, Drift	100	(5)
3.3.5.1 Lifetime	100	(2)
3.3.5.2 Aging and Drift	102	(3)
3.4 Interaction of Test Object and Light	105	(20)
3.4.1 Risk Factor Test Object	105	(11)
3.4.1.1 What Does the Test Object do With the Incoming Light?	106	(1)
3.4.1.2 Reflection/reflectance /scattering	107	(4)
3.4.1.3 Total Reflection	111	(1)
3.4.1.4 Transmission/transmittance	112	(1)
3.4.1.5 Absorption/absorbance	113	(1)
3.4.1.6 Diffraction	114	(1)
3.4.1.7 Refraction	115	(1)
3.4.2 Light Color and Part Color	116	(9)
3.4.2.1 Visible Light (VIS) — Monochromatic Light	116	(2)
3.4.2.2 Visible Light (VIS) — White Light	118	(1)
3.4.2.3 Infrared Light (IR)	119	(2)
3.4.2.4 Ultraviolet Light (UV)	121	(1)
3.4.2.5 Polarized Light	122	(3)
3.5 Basic Rules and Laws of Light Distribution	125	(13)
3.5.1 Basic Physical Quantities of Light	125	(2)
3.5.2 The Photometric Inverse Square Law	127	(1)
3.5.3 The Constancy of Luminance	128	(1)
3.5.4 What Light Arrives at the Sensor — Light Transmission Through the Lens	129	(2)
3.5.5 Light Distribution of Lighting Components	131	(3)
3.5.6 Contrast	134	(2)
3.5.7 Exposure	136	(2)
3.6 Light Filters	138	(12)
3.6.1 Characteristic Values of Light Filters	138	(2)
3.6.2 Influences of Light Filters on the Optical Path	140	(1)
3.6.3 Types of Light Filters	141	(2)
3.6.4 Anti-Reflective Coatings (AR)	143	(1)
3.6.5 Light Filters for Machine Vision	144	(6)
3.6.5.1 UV Blocking Filter	144	(1)
3.6.5.2 Daylight Suppression Filter	144	(2)
3.6.5.3 IR Suppression Filter	146	(1)
3.6.5.4 Neutral Filter/Neutral Density Filter/Gray Filter	146	(1)
3.6.5.5 Polarization Filter	147	(1)
3.6.5.6 Color Filters	148	(1)
3.6.5.7 Filter Combinations	149	(1)
3.7 Lighting Techniques and Their Use	150	(36)
3.7.1 How to Find a Suitable Lighting?	150	(1)
3.7.2 Planning the Lighting Solution — Influence Factors	151	(3)
3.7.3 Lighting Systematics	154	(6)
3.7.3.1 Directional Properties of the Light	155	(2)
3.7.3.2 Arrangement of the Lighting	157	(1)
3.7.3.3 Properties of the Illuminated Field	158	(2)
3.7.4 The Lighting Techniques in Detail	160	(24)
3.7.4.1 Diffuse Bright Field Incident Light	160	(2)
3.7.4.2 Directed Bright Field Incident Light	162	(1)
3.7.4.3 Telecentric Bright Field Incident Light	163	(2)
3.7.4.4 Structured Bright Field Incident Light	165	(4)
3.7.4.5 Diffuse/Directed Partial Bright Field Incident Light	169	(4)
3.7.4.6 Diffuse/Directed Dark Field Incident Light	173	(3)
3.7.4.7 The Limits of the Incident Lighting	176	(1)
3.7.4.8 Diffuse Bright Field Transmitted Lighting	177	(1)
3.7.4.9 Directed Bright Field Transmitted Lighting	178	(2)
3.7.4.10 Telecentric Bright Field Transmitted Lighting	180	(4)
3.7.4.11 Diffuse/Directed Transmitted Dark Field Lighting	184	(1)
3.7.5 Combined Lighting Techniques	184	(2)
3.8 Lighting Control	186	(15)
3.8.1 Reasons for Light Control - the Environmental Industrial Conditions	186	(1)
3.8.2 Electrical Control	186	(12)
3.8.2.1 Stable Operation	186	(3)
3.8.2.2 Brightness Control	189	(1)
3.8.2.3 Temporal Control: Static-Pulse-Flash	189	(2)
3.8.2.4 Some Considerations for the Use of Flash Light	191	(4)
3.8.2.5 Temporal and Local Control: Adaptive Lighting	195	(3)
3.8.3 Geometrical Control	198	(2)
3.8.3.1 Lighting from Large Distances	198	(1)
3.8.3.2 Light Deflection	199	(1)
3.8.4 Suppression of Ambient and Extraneous Light - Measures for a Stable Lighting	200	(1)
3.9 Lighting Perspectives for the Future	201	(1)
References	202	(3)
4 Optical Systems in Machine Vision	205	(128)
Dr. Karl Lenhardt, Jos. Schneider Optische Werke GmbH
4.1 A Look on the Foundations of Geometrical Optics	205	(5)
4.1.1 From Electrodynamics to the Light Rays	205	(3)
4.1.2 The Basic Laws of Geometrical Optics	208	(2)
4.2 Gaussian Optics	210	(58)
4.2.1 Reflection and Refraction at the Boundary between two Media	210	(2)
4.2.2 Linearizing the Law of Refraction - the Paraxial Approximation	212	(1)
4.2.3 Basic Optical Conventions	213	(3)
4.2.4 The Cardinal Elements of a Lens in Gaussian Optics	216	(5)
4.2.5 The Thin Lens Approximation	221	(1)
4.2.6 Beam Converging and Beam Diverging Lenses	222	(1)
4.2.7 Graphical Image Constructions	223	(1)
4.2.7.1 Beam Converging Lenses	223	(1)
4.2.7.2 Beam Diverging Lenses	224	(1)
4.2.8 Imaging Equations and Their Related Coordinate Systems	224	(5)
4.2.8.1 Reciprocity Equation	225	(1)
4.2.8.2 Newton's Equations	226	(1)
4.2.8.3 General Imaging Equation	227	(2)
4.2.8.4 The Axial Magnification Ratio	229	(1)
4.2.9 The Overlapping of Object and Image Space	229	(1)
4.2.10 Focal Length, Lateral Magnification and the Field of View	229	(2)
4.2.11 Systems of Lenses	231	(3)
4.2.12 Consequences of the Finite Extension of Ray Pencils	234	(10)
4.2.12.1 Effects of Limitations of the Ray Pencils	234	(3)
4.2.12.2 Several Limiting Openings	237	(3)
4.2.12.3 Characterizing the Limits of Ray Pencils	240	(3)
4.2.12.4 The Relation to the Linear Camera Model	243	(1)
4.2.13 Geometrical Depth of Field and Depth of Focus	244	(7)
4.2.13.1 Depth of Field as a Function of the Object Distance p	246	(1)
4.2.13.2 Depth of Field as a Function of β	247	(1)
4.2.13.3 The Hyperfocal Distance	248	(1)
4.2.13.4 The Permissible Size for the Circle of Confusion d'	249	(2)
4.2.14 The Laws of Central Projection-Telecentric System	251	(17)
4.2.14.1 An Introduction to the Laws of Perspective	251	(9)
4.2.14.2 Central Projection from Infinity - Telecentric Perspective	260	(8)
4.3 The Wave Nature of Light	268	(19)
4.3.1 Introduction	268	(1)
4.3.2 The Rayleigh-Sommerfeld Diffraction Integral	269	(3)
4.3.3 Further Approximations to the Huygens-Fresnel Principle	272	(3)
4.3.3.1 Fresnel's Approximation	273	(2)
4.3.4 The Impulse Response of an Aberration Free Optical System	275	(3)
4.3.4.1 The Case of Circular Aperture, Object Point on the Optical Axis	278	(1)
4.3.5 The Intensity Distribution in the Neighbourhood of the Geometrical Focus	278	(4)
4.3.6 The Extension of the Point Spread Function in a Defocused Image Plane	282	(3)
4.3.7 Consequences for the Depth of Field Considerations	285	(2)
4.4 Information Theoretical Treatment of Image Transfer and Storage	287	(29)
4.4.1 Physical Systems as Linear, Invariant Filters	288	(8)
4.4.2 The Optical Transfer Function (OTF) and the meaning of spatial frequency	296	(2)
4.4.3 Extension to the Two-Dimensional Case	298	(4)
4.4.3.1 The Interpretation of Spatial Frequency Components (r, s)	298	(2)
4.4.3.2 Reduction to One-Dimensional Representations	300	(2)
4.4.4 Impulse Response and MTF for Semiconductor Imaging Devices	302	(2)
4.4.5 The Transmission Chain	304	(1)
4.4.6 The Aliasing Effect and the Space Variant Nature of Aliasing	305	(11)
4.4.6.1 The Space Variant Nature of Aliasing	312	(4)
4.5 Criteria for Image Quality	316	(10)
4.5.1 Gaussian Data	316	(1)
4.5.2 Overview on Aberrations of Third Order	316	(1)
4.5.3 Image Quality in the Space Domain: PSF, LSF, ESF and Distortion	317	(4)
4.5.4 Image Quality in Spatial Frequency Domain: MTF	321	(2)
4.5.5 Other Image Quality Parameters	323	(2)
4.5.5.1 Relative Illumination (Relative Irradiance ) [17]	323	(2)
4.5.5.2 Deviation from Telecentricity (for Telecentric Lenses only)	325	(1)
4.5.6 Manufacturing Tolerances and Image Quality	325	(1)
4.6 Practical Aspects	326	(5)
References	331	(2)
5 Camera Calibration	333	(28)
R. Godding, AICON 3D Systems GmbH
5.1 Introduction	333	(1)
5.2 Terminology	334	(2)
5.2.1 Camera, Camera system	334	(1)
5.2.2 Coordinate systems	335	(1)
5.2.3 Interior Orientation and Calibration	335	(1)
5.2.4 Exterior and Relative Orientation	335	(1)
5.2.5 System Calibration	336	(1)
5.3 Physical Effects	336	(2)
5.3.1 Optical System	336	(1)
5.3.2 Camera and Sensor Stability	336	(1)
5.3.3 Signal Processing and Transfer	337	(1)
5.4 Mathematical Calibration Model	338	(8)
5.4.1 Central Projection	338	(1)
5.4.2 Camera Model	339	(1)
5.4.3 Focal Length and Principal Point	340	(1)
5.4.4 Distortion and Affinity	340	(1)
5.4.5 Radial symmetrical distortion	341	(1)
5.4.6 Radial Asymmetrical and Tangential Distortion	342	(1)
5.4.7 Affinity and Nonorthogonality	343	(1)
5.4.8 Variant Camera Parameters	343	(2)
5.4.9 Sensor Flatness	345	(1)
5.4.10 Other Parameters	345	(1)
5.5 Calibration and Orientation Techniques	346	(8)
5.5.1 In the Laboratory	346	(1)
5.5.2 Using Bundle Adjustment to Determine Camera Parameters	346	(6)
5.5.2.1 Calibration based Exclusively on Image Information	347	(2)
5.5.2.2 Calibration and Orientation with Additional Object Information	349	(2)
5.5.2.3 Extended System Calibration	351	(1)
5.5.3 Other Techniques	352	(2)
5.6 Verification of Calibration Results	354	(1)
5.7 Applications	355	(3)
5.7.1 Applications with Simultaneous Calibration	355	(1)
5.7.2 Applications with precalibrated cameras	356	(5)
5.7.2.1 Tube Measurement within a Measurement Cell	356	(1)
5.7.2.2 Online Measurements in the Field of Car Safety	357	(1)
5.7.2.3 Other Applications	358	(1)
References	358	(3)
6 Camera Systems in Machine Vision	361	(66)
Horst Mattfeldt, Allied Vision Technologies GmbH
6.1 Camera Technology	361	(2)
6.1.1 History in Brief	361	(1)
6.1.2 Machine Vision versus Closed Circuit Television (CCTV)	362	(1)
6.2 Sensor Technologies	363	(9)
6.2.1 Spatial Differentiation: 1D and 2D	364	(1)
6.2.2 CCD Technology	364	(1)
6.2.3 Full Frame Principle	365	(1)
6.2.4 Frame Transfer Principle	366	(1)
6.2.5 Interline Transfer	366	(6)
6.2.5.1 Interlaced Scan Interline Transfer	367	(2)
6.2.5.2 Frame Readout	369	(1)
6.2.5.3 Progressive Scan Interline Transfer	370	(2)
6.3 CCD Image Artifacts	372	(1)
6.3.1 Blooming	372	(1)
6.3.2 Smear	372	(1)
6.4 CMOS Image Sensor	373	(10)
6.4.1 Advantages of CMOS Sensors	374	(2)
6.4.2 CMOS Sensor Shutter Concepts	376	(7)
6.4.2.1 Comparison of CMOS versus CCD	378	(1)
6.4.2.2 Integration Complexity of CDD versus CMOS Camera Technology	379	(1)
6.4.2.3 Video Standards	379	(1)
6.4.2.4 Sensor Sizes and Dimensions	380	(1)
6.4.2.5 Sony HAD Technology	381	(1)
6.4.2.6 Sony SuperHAD Technology	381	(1)
6.4.2.7 Sony EXView HAD Technology	381	(2)
6.5 Block Diagrams and their Description	383	(10)
6.5.1 Block Diagram of a Progressive Scan Analog Camera	383	(6)
6.5.1.1 CCD Read-Out Clocks	383	(3)
6.5.1.2 Spectral Sensitivity	386	(1)
6.5.1.3 Analog Signal Processing	387	(1)
6.5.1.4 Camera and Frame Grabber	388	(1)
6.5.2 Block Diagram of Color Camera with Digital Image Processing	389	(4)
6.5.2.1 Bayer™ Complementary Color Filter Array	389	(1)
6.5.2.2 Complementary Color Filters Spectral Sensitivity	390	(1)
6.5.2.3 Generation of Color Signals	390	(3)
6.6 Digital Cameras	393	(14)
6.6.1 Black and White Digital Cameras	393	(3)
6.6.1.1 B/W Sensor and Processing	394	(2)
6.6.2 Color Digital Cameras	396	(11)
6.6.2.1 Analog Processing	396	(1)
6.6.2.2 One-Chip Color Processing	396	(2)
6.6.2.3 Analog Front End (AFE)	398	(1)
6.6.2.4 One Push White Balance	399	(1)
6.6.2.5 Automatic White Balance	400	(1)
6.6.2.6 Manual Gain	400	(1)
6.6.2.7 Auto Shutter/Gain	400	(1)
6.6.2.8 A/D Conversion	400	(1)
6.6.2.9 Lookup Table (LUT ) and Gamma Function	401	(1)
6.6.2.10 Shading Correction	402	(1)
6.6.2.11 Horizontal Mirror Function	403	(1)
6.6.2.12 Frame Memory and Deferred Image Transport	404	(1)
6.6.2.13 Color Interpolation	404	(2)
6.6.2.14 Color Correction	406	(1)
6.6.2.15 RGB to YUV Conversion	406	(1)
6.6.2.16 Binning versus Area of Interest (AOI)	406	(1)
6.7 Controlling Image Capture	407	(11)
6.7.1 Hardware Trigger Modes	408	(2)
6.7.1.1 Latency (Jitter) Aspects	409	(1)
6.7.2 Pixel Data	410	(1)
6.7.3 Data Transmission	411	(1)
6.7.4 IEEE-1394 Port Pin Assignment	412	(2)
6.7.5 Operating the Camera	414	(1)
6.7.6 HiRose Jack Pin Assignment	414	(1)
6.7.7 Frame Rates and Bandwidth	415	(3)
6.8 Configuration of the Camera	418	(2)
6.8.1 Camera Status Register	418	(2)
6.9 Camera Noise¹	420	(6)
6.9.1 Photon Noise	421	(1)
6.9.2 Dark Current Noise	421	(1)
6.9.3 Photo Response Nonuniformity (PRNU)	422	(1)
6.9.4 Reset Noise	422	(1)
6.9.5 1/f Noise (Amplifier Noise)	422	(1)
6.9.6 Quantization Noise	423	(1)
6.9.7 Noise Floor	423	(1)
6.9.8 Dynamic Range	423	(1)
6.9.9 Signal to Noise Ratio	424	(1)
6.10 Digital Interfaces	424	(2)
References	426	(1)
7 Camera Computer Interfaces	427	(84)
Tony Iglesias, Anita Salmon, Johann Scholtz, Robert Hedegore, Julianna Borgendale, Brent Runnels, Nathan McKimpson, National Instruments
7.1 Overview	427	(2)
7.2 Analog Camera Buses	429	(5)
7.2.1 Analog Video Signal	429	(1)
7.2.2 Interlaced Video	430	(1)
7.2.3 Progressive Scan Video	431	(1)
7.2.4 Timing Signals	431	(1)
7.2.5 Analog Image Acquisition	432	(1)
7.2.6 S-Video	432	(1)
7.2.7 RGB	433	(1)
7.2.8 Analog Connectors	433	(1)
7.3 Parallel Digital Camera Buses	434	(6)
7.3.1 Digital Video Transmission	434	(1)
7.3.2 Taps	434	(2)
7.3.3 Differential Signaling	436	(1)
7.3.4 Line Scan	436	(1)
7.3.5 Parallel Digital Connectors	437	(1)
7.3.6 Camera Link	437	(2)
7.3.7 Camera Link Signals	439	(1)
7.3.7.1 Camera Link Connectors	440	(1)
7.4 Standard PC Buses	440	(13)
7.4.1 USB	440	(2)
7.4.1.1 USB for Machine Vision	442	(1)
7.4.2 IEEE 1394 (FireWire®)	442	(8)
7.4.2.1 IEEE 1394 for Machine Vision	445	(5)
7.4.3 Gigabit Ethernet (IEEE 802.3z)	450	(3)
7.4.3.1 Gigabit Ethernet for Machine Vision	451	(2)
7.5 Choosing a Camera Bus	453	(9)
7.5.1 Bandwidth	454	(1)
7.5.2 Resolution	455	(2)
7.5.3 Frame Rate	457	(1)
7.5.4 Cables	457	(1)
7.5.5 Line Scan	458	(1)
7.5.6 Reliability	458	(2)
7.5.7 Summary of Camera Bus Specifications	460	(1)
7.5.8 Sample Use Cases	460	(2)
7.5.8.1 Manufacturing inspection	460	(1)
7.5.8.2 LCD inspection	461	(1)
7.5.8.3 Security	461	(1)
7.6 Computer Buses	462	(10)
7.6.1 ISA/EISA	462	(2)
7.6.2 PCI/CompactPCI/PXI	464	(1)
7.6.3 PCI-X	465	(1)
7.6.4 PCI Express/CompactPCI Express/PXI Express	466	(3)
7.6.5 Throughput	469	(2)
7.6.6 Prevalence and Lifetime	471	(1)
7.6.7 Cost	472	(1)
7.7 Choosing a Computer Bus	472	(3)
7.7.1 Determine Throughput Requirements	472	(2)
7.7.2 Applying the Throughput Requirements	474	(1)
7.8 Driver Software	475	(20)
7.8.1 Application Programming Interface	476	(3)
7.8.2 Supported Platforms	479	(1)
7.8.3 Performance	479	(2)
7.8.4 Utility Functions	481	(1)
7.8.5 Acquisition Mode	481	(4)
7.8.5.1 Snap	481	(1)
7.8.5.2 Grab	482	(1)
7.8.5.3 Sequence	483	(1)
7.8.5.4 Ring	483	(2)
7.8.6 Image Representation	485	(7)
7.8.6.1 Image Representation in Memory	485	(4)
7.8.6.2 Bayer Color Encoding	489	(2)
7.8.6.3 Image Representation on Disk	491	(1)
7.8.7 Image Display	492	(3)
7.8.7.1 Understanding Display Modes	492	(2)
7.8.7.2 Palettes	494	(1)
7.8.7.3 Nondestructive Overlays	494	(1)
7.9 Features of a Machine Vision System	495	(16)
7.9.1 Image Reconstruction	496	(1)
7.9.2 Timing and Triggering	497	(3)
7.9.3 Memory Handling	500	(2)
7.9.4 Additional Features	502	(6)
7.9.4.1 Look-up Tables	502	(2)
7.9.4.2 Region of Interest	504	(1)
7.9.4.3 Color Space Conversion	505	(2)
7.9.4.4 Shading Correction	507	(1)
7.9.5 Summary	508	(3)
8 Machine Vision Algorithms	511	(182)
Dr. Carsten Steger, MVTec Software GmbH
8.1 Fundamental Data Structures	511	(5)
8.1.1 Images	511	(2)
8.1.2 Regions	513	(2)
8.1.3 Subpixel-Precise Contours	515	(1)
8.2 Image Enhancement	516	(20)
8.2.1 Gray Value Transformations	516	(3)
8.2.2 Radiometric Calibration	519	(6)
8.2.3 Image Smoothing	525	(11)
8.3 Geometric Transformations	536	(8)
8.3.1 Affine Transformations	537	(1)
8.3.2 Projective Transformations	538	(1)
8.3.3 Image Transformations	539	(5)
8.3.4 Polar Transformations	544	(1)
8.4 Image Segmentation	544	(11)
8.4.1 Thresholding	545	(6)
8.4.2 Extraction of Connected Components	551	(2)
8.4.3 Subpixel-Precise Thresholding	553	(2)
8.5 Feature Extraction	555	(11)
8.5.1 Region Features	556	(4)
8.5.2 Gray Value Features	560	(5)
8.5.3 Contour Features	565	(1)
8.6 Morphology	566	(21)
8.6.1 Region Morphology	566	(17)
8.6.2 Gray Value Morphology	583	(4)
8.7 Edge Extraction	587	(25)
8.7.1 Definition of Edges in 1D and 2D	587	(4)
8.7.2 1D Edge Extraction	591	(6)
8.7.3 2D Edge Extraction	597	(8)
8.7.4 Accuracy of Edges	605	(7)
8.8 Segmentation and Fitting of Geometric Primitives	612	(12)
8.8.1 Fitting Lines	613	(4)
8.8.2 Fitting Circles	617	(2)
8.8.3 Fitting Ellipses	619	(1)
8.8.4 Segmentation of Contours into Lines, Circles, and Ellipses	620	(4)
8.9 Template Matching	624	(29)
8.9.1 Gray-Value-Based Template Matching	626	(6)
8.9.2 Matching Using Image Pyramids	632	(4)
8.9.3 Subpixel-Accurate Gray-Value-Based Matching	636	(1)
8.9.4 Template Matching with Rotations and Scalings	637	(1)
8.9.5 Robust Template Matching	638	(15)
8.10 Stereo Reconstruction	653	(13)
8.10.1 Stereo Geometry	654	(8)
8.10.2 Stereo Matching	662	(4)
8.11 Optical Character Recognition	666	(22)
8.11.1 Character Segmentation	667	(2)
8.11.2 Feature Extraction	669	(3)
8.11.3 Classification	672	(16)
References	688	(5)
9 Machine Vision in Manufacturing	693	(88)
Dr.-Ing. Peter Waszkewitz, Robert Bosch GmbH
9.1 Introduction	693	(1)
9.2 Application Categories	694	(6)
9.2.1 Types of Tasks	694	(2)
9.2.2 Types of Production	696	(2)
9.2.2.1 Discrete Unit Production Versus Continuous Flow	697	(1)
9.2.3 Types of Evaluations	698	(1)
9.2.4 Value-Adding Machine Vision	699	(1)
9.3 System Categories	700	(8)
9.3.1 Common Types of Systems	700	(1)
9.3.2 Sensors	701	(1)
9.3.3 Vision Sensors	702	(1)
9.3.4 Compact Systems	703	(1)
9.3.5 Vision Controllers	704	(1)
9.3.6 PC-Based Systems	704	(3)
9.3.7 Summary	707	(1)
9.4 Integration and Interfaces	708	(2)
9.5 Mechanical Interfaces	710	(10)
9.5.1 Dimensions and Fixation	711	(1)
9.5.2 Working Distances	711	(1)
9.5.3 Position Tolerances	712	(1)
9.5.4 Forced Constraints	713	(1)
9.5.5 Additional Sensor Requirements	713	(1)
9.5.6 Additional Motion Requirements	714	(1)
9.5.7 Environmental Conditions	715	(1)
9.5.8 Reproducibility	716	(2)
9.5.9 Gauge Capability	718	(2)
9.6 Electrical Interfaces	720	(5)
9.6.1 Wiring and Movement	721	(1)
9.6.2 Power Supply	721	(1)
9.6.3 Internal Data Connections	722	(2)
9.6.4 External Data Connections	724	(1)
9.7 Information Interfaces	725	(9)
9.7.1 Interfaces and Standardization	725	(1)
9.7.2 Traceability	726	(1)
9.7.3 Types of Data and Data Transport	727	(1)
9.7.4 Control Signals	727	(1)
9.7.5 Result and Parameter Data	728	(1)
9.7.6 Mass Data	729	(1)
9.7.7 Digital I/O	729	(1)
9.7.8 Field Bus	730	(1)
9.7.9 Serial Interfaces	730	(1)
9.7.10 Network	731	(1)
9.7.11 Files	732	(1)
9.7.12 Time and Integrity Considerations	732	(2)
9.8 Temporal Interfaces	734	(9)
9.8.1 Discrete Motion Production	735	(2)
9.8.2 Continuous Motion Production	737	(3)
9.8.3 Line-Scan Processing	740	(3)
9.9 Human—Machine Interfaces	743	(9)
9.9.1 Interfaces for Engineering Vision Systems	743	(2)
9.9.2 Runtime Interface	745	(4)
9.9.3 Remote Maintenance	749	(1)
9.9.4 Offline Setup	750	(2)
9.10 Industrial Case Studies	752	(17)
9.10.1 Glue Check under UV Light	752	(2)
9.10.1.1 Solution	752	(2)
9.10.2 Completeness Check	754	(3)
9.10.3 Multiple Position and Completeness Check	757	(3)
9.10.4 Pin Type Verification	760	(3)
9.10.5 Robot Guidance	763	(3)
9.10.6 Type and Result Data Management	766	(3)
9.11 Constraints and Conditions	769	(6)
9.11.1 Inspection Task Requirements	769	(1)
9.11.2 Circumstantial Requirements	770	(3)
9.11.3 Limits and Prospects	773	(2)
References	775	(6)
Index	781