Advances in Optical Form and Coordinate Metrology

PRELIMS.pdf
Preface
Editor biography
Richard Leach
List of contributors
CH001.pdf
Chapter 1 Terms, definitions and standards
1.1 Introduction
1.2 Surface and coordinate terms and definitions
1.3 General metrology terms and definitions
1.4 Specification standards for coordinate metrology
1.4.1 Coordinate metrology standards
Acknowledgements
References
CH002.pdf
Chapter 2 State-of-the-art in point cloud analysis
2.1 Introduction
2.1.1 Mathematical representation of 3D point clouds
2.1.2 Common 3D point cloud file formats
2.1.3 Point cloud transformations
2.2 Extracting properties and organising information in point clouds
2.2.1 Convex hull and bounding boxes
2.2.2 Centroid and principal axes of a point cloud
2.2.3 Spatial subdivision of point clouds
2.3 Point cloud pre-processing
2.3.1 Point cloud simplification, decimation and resampling
2.3.2 Elimination of isolated points and noise reduction
2.3.3 Triangle meshes and conversion to/from point clouds
2.4 Point features and partitioning
2.4.1 Point normals
2.4.2 Point curvatures
2.4.3 Partitioning and segmentation
2.5 Point cloud fitting
2.5.1 Fitting methods
2.6 Registration of point clouds
2.6.1 Registration based on external references or based on matching landmarks
2.6.2 The absolute orientation problem
2.6.3 Alignment by means of principal component analysis
2.6.4 RANSAC alignment
2.6.5 Alignment by iterative closest points
2.6.6 Landmark matching and alignment using similarity metrics
2.7 Measurement uncertainty in point cloud surface data
2.7.1 Approaches to the estimation of measurement uncertainty
2.7.2 Uncertainty associated with point clouds
2.8 Conclusions
References
CH003.pdf
Chapter 3 Laser triangulation
3.1 Laser triangulation
3.2 Laser triangulation sensors
3.3 Laser triangulation measurement dependence on surface properties
3.3.1 Measurement uncertainty limit
3.3.2 Surface reflectance perspective
3.3.3 Measurement dependence on surface form
3.4 Laser triangulation systems
3.4.1 Extension of a point based laser triangulation sensor
3.4.2 Point measurement systems
3.4.3 Profile measurement systems
3.4.4 Surface measurement systems
3.4.5 Advanced laser triangulation systems
3.5 Working process of laser triangulation
3.5.1 Characterisation of intrinsic parameters
3.5.2 Characterisation of extrinsic parameters
3.5.3 Pre-calibration of laser triangulation systems
3.5.4 Scanning path planning
3.5.5 Image pre-processing
3.5.6 Laser feature extraction
3.5.7 Refinement and postprocessing
3.6 Application of laser triangulation measurements
3.6.1 Application of laser triangulation in emerging manufacturing methods
3.6.2 Application for geometric inspection
3.6.3 Application of 3D reconstructed models
3.7 Conclusions
References
CH004.pdf
Chapter 4 Close-range photogrammetry
4.1 Introduction
4.1.1 Modern photogrammetry
4.1.2 Camera projection theory
4.1.3 The pinhole camera model
4.1.4 Distortion modelling
4.2 Characterisation and calibration
4.2.1 Camera characterisation
4.2.2 Linear techniques
4.2.3 Non-linear methods
4.2.4 Self-calibration
4.3 System calibration
4.3.1 Arbitrary scale
4.4 Image acquisition
4.4.1 Depth of field
4.4.2 Imaging procedure optimisation
4.5 Summary
References
CH005.pdf
Chapter 5 Digital fringe projection profilometry
5.1 Introduction
5.2 Fringe pattern generation methods
5.2.1 Conventional fringe generation methods
5.2.2 Digital binary defocusing techniques
5.2.3 New fringe pattern generation methods
5.3 Fringe analysis
5.3.1 Conventional fringe analysis techniques
5.3.2 Machine learning enhanced fringe analysis methods
5.4 Phase unwrapping
5.4.1 Conventional phase unwrapping methods
5.4.2 Non-conventional phase unwrapping methods
5.4.3 Machine-learning-based phase unwrapping methods
5.5 High dynamic range techniques
5.6 Calibration
5.6.1 Conventional methods
5.6.2 Recent developments
5.7 High-speed FPP realisation
5.7.1 Conventional high-speed FPP methods
5.7.2 Recent developments
5.8 Towards automation
5.9 Towards integrated solutions
5.9.1 3D imaging system for crime scene evidence collection
5.9.2 Robotic path planning
5.10 Summary
References
CH006.pdf
Chapter 6 Machine learning approaches
6.1 Introduction
6.2 Overview of machine learning and machine learning methods
6.3 Machine learning for stereo matching
6.3.1 Learned stereo machines
6.4 Machine learning for phase unwrapping
6.5 Learning depth from a single image
6.5.1 Characterisation of cameras and projectors
6.6 Machine learning for point cloud analysis
6.6.1 Point cloud segmentation
6.6.2 Point cloud registration
6.6.3 Point cloud completion
6.7 Conclusions
References
CH007.pdf
Chapter 7 Precision freeform metrology
7.1 Overview of freeform surfaces
7.2 Framework for precision freeform metrology
7.3 Characterisation of freeform surfaces
7.3.1 Surface fitting and reconstruction
7.3.2 Surface matching
7.3.3 Surface parameters for form error evaluation
7.4 Conclusions and future research
Acknowledgments
References
CH008.pdf
Chapter 8 Performance verification for optical co-ordinate metrology
8.1 Introduction
8.2 Material measures
8.2.1 Material measure 1
8.2.2 Material measure 2
8.2.3 Material measure 3
8.2.4 Material measure 4
8.3 The different types of performance verification test
8.4 Specification of errors
8.4.1 General guidelines for performance verification
8.5 Performance verification procedures
8.5.1 Measurements with representative points
8.5.2 General preparation for the performance verification test
8.5.3 Probing characteristics
8.5.4 Distortion characteristics
8.5.5 Length measurement errors
8.6 Compliance with specifications
8.6.1 Formal definition of performance verification
8.6.2 Retesting after a failed compliance with specifications
8.7 A final note on the validity of performance verification
References