challenging and rapidly developing applications for machine vision today.
- Automated surface inspection
- An alternative surface description
- Reconstruction of acquired surface details
- Experimental work
- Analysis of surface defects
- Example case study applications to industrial machine vision surface inspection
- Overview of a generic inspection system.
System Inspection Techniques will appeal to practising engineers and scientists. As well as undergraduate and postgraduate students, offering a better understanding of the theory and practical application of image processing
and computer graphics in surface inspection tasks. Manufacturing engineers and inspection system developers, quality engineers, and anyone requiring an insight into the complex issues involved in automated surface inspection will find this book useful.
Chapter 1 Introduction.
1.1 An absence of automated surface inspection.
1.2 The nature of surface defects.
1.3 Laser beam properties.
1.4 The need for flexibility.
1.5 An overview of the book.
Chapter 2 Automated Surface Inspection.
2.1 Application of machine vision to surface flaw detection.
2.2 Surface defects in the presence of a complex background.
2.3 Other related work.
Chapter 3 An Alternative Surface Description.
3.1 A new surface model.
3.2 The Gaussian image and the extended Gaussian image.
3.3 Structural defects as a shape aberration.
3.4 The bump map as a topographical description.
3.5 The albedo map.
Chapter 4 Photoclinometry.
4.1 Reflection models.
4.2 Surface albedo and surface normal recovery.
4.3 Three-light coordinate frame photometric stereo.
4.4 Consideration of color photometric stereo.
4.5 Consideration of specular reflection.
4.6 Adaption of conventional methods of image analysis to the acquired bump map.
Chapter 5 Reconstruction of Acquired Surface Detail.
5.1 Generation of synthetic images.
5.2 Reconstruction of the surface depth map.
Chapter 6 Experimental Work.
6.1 Aims of the experimental work.
6.2 Construction of the experimental apparatus.
6.3 Experimental procedure.
6.4 Presentation and discussion of results.
Chapter 7 Analysis of Surface Defects.
7.1 Existing standards.
7.2 Classification of defects.
7.3 Distribution of surface shape as a new alternative.
7.4 Shape as a hierarchical structure.
7.5 The gradient space domain.
7.6 Independence of object pose.
7.7 A generic surface inspection strategy.
7.8 Classifying defects from spatial and gradient plot signatures.
7.9 A measure of distribution.
Chapter 8 Experimental Work.
8.1 Pose-independent determination.
8.2 Analysis of surface structural texture.
8.3 Defect upon a cosmetically sensitive polyhedral component.
8.4 Isolation of bump map from surface geometry.
8.5 The classification and quantification of surface defect features using the ellipsoidal model, in the case of an unconstrained specimen.
8.6 Summary of the experimental work.
Chapter 9 Example Case Study Applications in Industrial Machine Vision Surface Inspection.
9.1 Decorative ceramic tiles.
9.2 Alphanumeric character recognition on gas turbine blades.
9.3 Wood product inspection.
Chapter 10 Overview of a Generic Inspection System.
Chapter 11 Conclusions and Future Work.
11.2 Future work.
Appendix 1 Technical Papers Arising from this Work.
Appendix 2 The Four Stages of Machine Vision.
Appendix 3 Perspective and Orthographic Projection.
Appendix 4 A List of Programs.
Appendix 5 Validation of Blob analysis software using Synthetic Scratches and Method of Moment Analysis.
Appendix 6 An Approximation of Feature Depth from Spatial and Gradient Distributions.
Appendix 7 Ellipsoidal Feature Width Using Method of Moment Analysis.
Appendix 8 Calculation of Principal Dimensions of a 2D Feature Given Only Area and Perimeter.
Appendix 9 Selected Experimental Results.
Appendix 10 Altering the Light Source Position.