Machine vision theory, algorithms, practicalities
In the last 40 years, machine vision has evolved into a mature field embracing a wide range of applications including surveillance, automated inspection, robot assembly, vehicle guidance, traffic monitoring and control, signature verification, biometric measurement, and analysis of remotely sensed i...
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| Format: | eBook |
| Language: | Inglés |
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Amsterdam ; Oxford :
Morgan Kaufmann
2005.
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| Edition: | 3rd ed |
| Series: | Signal Processing and its Applications
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| Subjects: | |
| See on Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009627138106719 |
Table of Contents:
- 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 ProblemsCHAPTER 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 Notes3.17 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 Operator5.8 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 Uses6.8 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
