Front Cover -- Machine Vision: Theory, Algorithms, Practicalities -- Copyright Page -- Contents -- Foreword -- Preface -- Acknowledgments -- CHAPTER 1. Vision, the Challenge -- 1.1 Introduction-The Senses -- 1.2 The Nature of Vision -- 1.3 From Automated Visual Inspection to Surveillance -- 1.4 What This Book Is About -- 1.5 The Following Chapters -- 1.6 Bibliographical Notes -- PART 1: Low-Level Vision -- CHAPTER 2. Images and Imaging Operations -- 2.1 Introduction -- 2.3 Convolutions and Point Spread Functions -- 2.4 Sequential versus Parallel Operations -- 2.5 Concluding Remarks -- 2.6 Bibliographical and Historical Notes -- 2.7 Problems -- CHAPTER 3. Basic Image Filtering Operations -- 3.1 Introduction -- 3.2 Noise Suppression by Gaussian Smoothing -- 3.3 Median Filters -- 3.4 Mode Filters -- 3.5 Rank Order Filters -- 3.6 Reducing Computational Load -- 3.7 Sharp-Unsharp Masking -- 3.8 Shifts Introduced by Median Filters -- 3.9 Discrete Model of Median Shifts -- 3.10 Shifts Introduced by Mode Filters -- 3.11 Shifts Introduced by Mean and Gaussian Filters -- 3.12 Shifts Introduced by Rank Order Filters -- 3.13 The Role of Filters in Industrial Applications of Vision -- 3.14 Color in Image Filtering -- 3.15 Concluding Remarks -- 3.16 Bibliographical and Historical Notes -- 3.17 Problems -- CHAPTER 4. Thresholding Techniques -- 4.1 Introduction -- 4.2 Region-growing Methods -- 4.3 Thresholding -- 4.4 Adaptive Thresholding -- 4.5 More Thoroughgoing Approaches to Threshold Selection -- 4.6 Concluding Remarks -- 4.7 Bibliographical and Historical Notes -- 4.8 Problems -- CHAPTER 5. Edge Detection -- 5.1 Introduction -- 5.2 Basic Theory of Edge Detection -- 5.3 The Template Matching Approach -- 5.4 Theory of 3 X 3 Template Operators -- 5.5 Summary-Design Constraints and Conclusions.

5.6 The Design of Differential Gradient Operators -- 5.7 The Concept of a Circular Operator -- 5.8 Detailed Implementation of Circular Operators -- 5.9 Structured Bands of Pixels in Neighborhoods of Various Sizes -- 5.10 The Systematic Design of Differential Edge Operators -- 5.11 Problems with the above Approach-Some Alternative Schemes -- 5.12 Concluding Remarks -- 5.13 Bibliographical and Historical Notes -- 5.14 Problems -- CHAPTER 6. Binary Shape Analysis -- 6.1 Introduction -- 6.2 Connectedness in Binary Images -- 6.3 Object Labeling and Counting -- 6.4 Metric Properties in Digital Images -- 6.5 Size Filtering -- 6.6 The Convex Hull and Its Computation -- 6.7 Distance Functions and Their Uses -- 6.8 Skeletons and Thinning -- 6.9 Some Simple Measures for Shape Recognition -- 6.10 Shape Description by Moments -- 6.11 Boundary Tracking Procedures -- 6.12 More Detail on the Sigma and Chi Functions -- 6.13 Concluding Remarks -- 6.14 Bibliographical and Historical Notes -- 6.15 Problems -- CHAPTER 7. Boundary Pattern Analysis -- 7.1 Introduction -- 7.2 Boundary Tracking Procedures -- 7.3 Template Matching-A Reminder -- 7.4 Centroidal Profiles -- 7.5 Problems with the Centroidal Profile Approach -- 7.6 The (s,y ) Plot -- 7.7 Tackling the Problems of Occlusion -- 7.8 Chain Code -- 7.9 The (r, s) Plot -- 7.10 Accuracy of Boundary Length Measures -- 7.11 Concluding Remarks -- 7.12 Bibliographical and Historical Notes -- 7.13 Problems -- CHAPTER 8. Mathematical Morphology -- 8.1 Introduction -- 8.2 Dilation and Erosion in Binary Images -- 8.3 Mathematical Morphology -- 8.4 Connectivity-based Analysis of Images -- 8.5 Gray-scale Processing -- 8.6 Effect of Noise on Morphological Grouping Operations -- 8.7 Concluding Remarks -- 8.8 Bibliographical and Historical Notes -- 8.9 Problem -- PART 2: Intermediate-Level Vision -- CHAPTER 9. Line Detection.

9.1 Introduction -- 9.2 Application of the Hough Transform to Line Detection -- 9.3 The Foot-of-Normal Method -- 9.4 Longitudinal Line Localization -- 9.5 Final Line Fitting -- 9.6 Concluding Remarks -- 9.7 Bibliographical and Historical Notes -- 9.8 Problems -- CHAPTER 10. Circle Detection -- 10.1 Introduction -- 10.2 Hough-based Schemes for Circular Object Detection -- 10.3 The Problem of Unknown Circle Radius -- 10.4 The Problem of Accurate Center Location -- 10.5 Overcoming the Speed Problem -- 10.6 Concluding Remarks -- 10.7 Bibliographical and Historical Notes -- 10.8 Problems -- CHAPTER 11. The Hough Transform and Its Nature -- 11.1 Introduction -- 11.2 The Generalized Hough Transform -- 11.3 Setting Up the Generalized Hough Transform-Some Relevant Questions -- 11.4 Spatial Matched Filtering in Images -- 11.5 From Spatial Matched Filters to Generalized Hough Transforms -- 11.6 Gradient Weighting versus Uniform Weighting -- 11.7 Summary -- 11.8 Applying the Generalized Hough Transform to Line Detection -- 11.9 The Effects of Occlusions for Objects with Straight Edges -- 11.10 Fast Implementations of the Hough Transform -- 11.11 The Approach of Gerig and Klein -- 11.12 Concluding Remarks -- 11.13 Bibliographical and Historical Notes -- 11.14 Problem -- CHAPTER 12. Ellipse Detection -- 12.1 Introduction -- 12.2 The Diameter Bisection Method -- 12.3 The Chord-Tangent Method -- 12.4 Finding the Remaining Ellipse Parameters -- 12.5 Reducing Computational Load for the Generalized Hough Transform Method -- 12.6 Comparing the Various Methods -- 12.7 Concluding Remarks -- 12.8 Bibliographical and Historical Notes -- 12.9 Problems -- CHAPTER 13. Hole Detection -- 13.1 Introduction -- 13.2 The Template Matching Approach -- 13.3 The Lateral Histogram Technique.

13.4 The Removal of Ambiguities in the Lateral Histogram Technique -- 13.5 Application of the Lateral Histogram Technique for Object Location -- 13.6 Appraisal of the Hole Detection Problem -- 13.7 Concluding Remarks -- 13.8 Bibliographical and Historical Notes -- 13.9 Problems -- CHAPTER 14. Polygon and Corner Detection -- 14.1 Introduction -- 14.2 The Generalized Hough Transform -- 14.3 Application to Polygon Detection -- 14.4 Determining Polygon Orientation -- 14.5 Why Corner Detection? -- 14.6 Template Matching -- 14.7 Second-order Derivative Schemes -- 14.8 A Median-Filter-Based Corner Detector -- 14.9 The Hough Transform Approach to Corner Detection -- 14.10 The Plessey Corner Detector -- 14.11 Corner Orientation -- 14.12 Concluding Remarks -- 14.13 Bibliographical and Historical Notes -- 14.14 Problems -- CHAPTER 15. Abstract Pattern Matching Techniques -- 15.1 Introduction -- 15.2 A Graph-theoretic Approach to Object Location -- 15.3 Possibilities for Saving Computation -- 15.4 Using the Generalized Hough Transform for Feature Collation -- 15.5 Generalizing the Maximal Clique and Other Approaches -- 15.6 Relational Descriptors -- 15.7 Search -- 15.8 Concluding Remarks -- 15.9 Bibliographical and Historical Notes -- 15.10 Problems -- PART 3: 3-D Vision and Motion -- CHAPTER 16. The Three-dimensional World -- 16.1 Introduction -- 16.2 Three-Dimensional Vision-The Variety of Methods -- 16.3 Projection Schemes for Three-dimensional Vision -- 16.4 Shape from Shading -- 16.5 Photometric Stereo -- 16.6 The Assumption of Surface Smoothness -- 16.7 Shape from Texture -- 16.8 Use of Structured Lighting -- 16.9 Three-Dimensional Object Recognition Schemes -- 16.10 The Method of Ballard and Sabbah -- 16.11 The Method of Silberberg et al. -- 16.12 Horaud's Junction Orientation Technique -- 16.13 An Important Paradigm-Location of Industrial Parts.

16.14 Concluding Remarks -- 16.15 Bibliographical and Historical Notes -- 16.16 Problems -- CHAPTER 17. Tackling the Perspective n-Point Problem -- 17.1 Introduction -- 17.2 The Phenomenon of Perspective Inversion -- 17.3 Ambiguity of Pose under Weak Perspective Projection -- 17.4 Obtaining Unique Solutions to the Pose Problem -- 17.5 Concluding Remarks -- 17.6 Bibliographical and Historical Notes -- 17.7 Problems -- CHAPTER 18. Motion -- 18.1 Introduction -- 18.2 Optical Flow -- 18.3 Interpretation of Optical Flow Fields -- 18.4 Using Focus of Expansion to Avoid Collision -- 18.5 Time-to-Adjacency Analysis -- 18.6 Basic Difficulties with the Optical Flow Model -- 18.7 Stereo from Motion -- 18.8 Applications to the Monitoring of Traffic Flow -- 18.9 People Tracking -- 18.10 Human Gait Analysis -- 18.11 Model-based Tracking of Animals-A Case Study -- 18.12 Snakes -- 18.13 The Kalman Filter -- 18.14 Concluding Remarks -- 18.15 Bibliographical and Historical Notes -- 18.16 Problem -- CHAPTER 19. Invariants and Their Applications -- 19.1 Introduction -- 19.2 Cross Ratios: The ''Ratio of Ratios'' Concept -- 19.3 Invariants for Noncollinear Points -- 19.4 Invariants for Points on Conics -- 19.5 Differential and Semidifferential Invariants -- 19.6 Symmetrical Cross Ratio Functions -- 19.7 Concluding Remarks -- 19.8 Bibliographical and Historical Notes -- 19.9 Problems -- CHAPTER 20. Egomotion and Related Tasks -- 20.1 Introduction -- 20.2 Autonomous Mobile Robots -- 20.3 Active Vision -- 20.4 Vanishing Point Detection -- 20.5 Navigation for Autonomous Mobile Robots -- 20.6 Constructing the Plan View of Ground Plane -- 20.7 Further Factors Involved in Mobile Robot Navigation -- 20.8 More on Vanishing Points -- 20.9 Centers of Circles and Ellipses -- 20.10 Vehicle Guidance in Agriculture-A Case Study -- 20.11 Concluding Remarks.

20.12 Bibliographical and Historical Notes.