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| Vision, the Challenge | |
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| Low-Level Processing: Images and Imaging Operations | |
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| Basic Image Filtering Operations | |
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| Thresholding Techniques | |
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| Locating Objects via Their Edges | |
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| Binary Shape Analysis | |
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| Boundary Pattern Analysis | |
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| Intermediate-Level Processing: Line Detection | |
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| Circle Detection | |
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| The Hough Transform and Its Nature | |
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| Ellipse Detection | |
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| Hole Detection | |
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| Polygon and Corner Detection | |
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| Application Level Processing: Abstract Pattern Matching Techniques | |
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| The Three-Dimensional World | |
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| Tackling the Perspective n-Point Problem | |
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| Motion | |
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| Invariants and their Applications | |
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| Automated Visual Inspection | |
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| Statistical Pattern Recognition | |
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| Biologically Inspired Recognition Schemes | |
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| Texture | |
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| Image Acquisition | |
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| The Need for Speed: Real-Time Electronic Hardware Systems | |
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| Perspectives on Vision: Machine Vision, Art or Science? | |
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| Appendices | |
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| References | |
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| Subject Index | |
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| Author Index | |
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| Vision, the Challenge: Introduction | |
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| Man and his Senses | |
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| The Nature of Vision | |
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| Automated Visual Inspection | |
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| What This Book is About | |
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| The Following Chapters | |
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| Low-Level Processing: Images and Imaging Operations: Image Processing Operations | |
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| Convolutions and Point Spread Functions | |
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| Sequential Versus Parallel Operations | |
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| Basic Image Filtering Operations: Noise Suppression by Gaussian Smoothing | |
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| Median Filtering | |
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| Mode Filtering | |
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| Bias Generated by Noise Suppression Filters | |
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| Reducing Computational Load | |
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| The Role of Filters in Industrial Applications of Vision | |
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| Sharp-Unsharp Masking | |
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| Thresholding Techniques: Region-Growing Methods | |
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| Thresholding | |
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| Adaptive Thresholding | |
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| Locating Objects via Their Edges: Basic Theory of Edge Detection | |
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| The Template Matching Approach | |
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| Theory of 3 x 3 Template Operators | |
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| Summary | |
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| Design Constraints and Conclusions | |
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| The Design of Differential Gradient Operators | |
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| The Concept of a Circular Operator | |
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| Detailed Implementation of Circular Operators | |
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| Structured Bands of Pixels in Neighbourhoods of Various Sizes | |
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| The Systematic Design of Differential Edge Operators | |
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| Problems with the Above ApproachSome Alternative Schemes | |
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| Binary Shape Analysis: Connectedness in Binary Images | |
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| ObjectLabelling and Counting | |
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| Metric Properties in Digital Images | |
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| Size Filtering | |
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| The Convex Hull and Its Computation | |
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| Distance Functions and Their Uses | |
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| Skeletons and Thinning | |
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| Some Simple Measures for Shape Recognition | |
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| Shape Description by Moments | |
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| BoundaryTracking Procedures | |
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| Boundary Pattern Analysis: Boundary Tracking Procedures | |
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| Template Matchinga Reminder | |
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| Centroidal Profiles | |
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| Problems with the Centroidal Profile Approach | |
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| The (s, () Plot | |
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| Tackling the Problems of Occlusion | |
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| Chain Code | |
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| The (r, s) Plot | |
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| Accuracy of Boundary Length Measures | |
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| Concluding Remarks | |
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| Bibliographical and Historical | |
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| Notes | |
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| Intermediate-Level Processing: Line Detection: Application of the Hough Transform to Line Detection | |
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| The Foot-of-Normal Method | |
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| Longitudinal Line Localization | |
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| Final Line Fitting | |
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| Circle Detection: Hough-Based Schemes for Circular Object Detection | |
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| The Problem of Unknown Circle Radius | |
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| The Problem of Accurate Centre Location | |
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| Overcoming the Speed Problem | |
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| The Hough Transform and Its Nature: The Generalized Hough Transform | |
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| Setting Up the Generalized Hough TransformSome Relevant Questions | |
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| Spatial Matched Filtering in Images | |
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| From Spatial Matched Filters to Generalized Hough Transforms | |
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| Gradient Weighting Versus Uniform Weighting | |
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| Summary | |
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| Applying the Generalized Hough Transform to Line Detection | |
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| An Instructive Example | |
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| Tradeoffs to Reduce Computational Load | |
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| The Effects of Occlusions for Objects with Straight Edges | |
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| Fast Implementations of the HoughTransform | |
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| The Approach of Gerig and Klein | |
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| Ellipse Detection: The Diameter Bisection Method | |
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| The Chord Tangent Method | |
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| Finding the Remaining Ellipse Parameters | |
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| Reducing Computational Load for the Generalized Hough Transform Method | |
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| Comparing the Various Methods | |
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| Hole Detection: The Template Matching Approach | |
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| The Lateral Histogram Technique | |
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| The Removal of Ambiguities in the Lateral Histrogram | |