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Computer Vision : Principles, Algorithms, Applications, Learning.
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Saint Louis :
Elsevier Science,
2017.
|
| Edición: | 5th ed. |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Front Cover; Computer Vision; Copyright Page; Dedication; Contents; About the Author; Foreword; Preface to the Fifth Edition; Preface to the First Edition; Acknowledgments; Topics Covered in Application Case Studies; Influences Impinging Upon Integrated Vision System Design; Glossary of Acronyms and Abbreviations; 1 Vision, the challenge; 1.1 Introductionâ#x80;#x94;Man and His Senses; 1.2 The Nature of Vision; 1.2.1 The Process of Recognition; 1.2.2 Tackling the Recognition Problem; 1.2.3 Object Location; 1.2.4 Scene Analysis; 1.2.5 Vision as Inverse Graphics.
- 1.3 From Automated Visual Inspection to Surveillance1.4 What This Book Is About; 1.5 The Part Played by Machine Learning; 1.6 The Following Chapters; 1.7 Bibliographical Notes; 1 Low-level vision; 2 Images and imaging operations; 2.1 Introduction; 2.1.1 Gray Scale Versus Color; 2.2 Image Processing Operations; 2.2.1 Some Basic Operations on Grayscale Images; 2.2.2 Basic Operations on Binary Images; 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.
- 3 Image filtering and morphology3.1 Introduction; 3.2 Noise Suppression by Gaussian Smoothing; 3.3 Median Filters; 3.4 Mode Filters; 3.5 Rank Order Filters; 3.6 Sharpâ#x80;#x93;Unsharp Masking; 3.7 Shifts Introduced by Median Filters; 3.7.1 Continuum Model of Median Shifts; 3.7.2 Generalization to Grayscale Images; 3.7.3 Discrete Model of Median Shifts; 3.8 Shifts Introduced by Rank Order Filters; 3.8.1 Shifts in Rectangular Neighborhoods; 3.9 The Role of Filters in Industrial Applications of Vision; 3.10 Color in Image Filtering; 3.11 Dilation and Erosion in Binary Images.
- 3.11.1 Dilation and Erosion3.11.2 Cancellation Effects; 3.11.3 Modified Dilation and Erosion Operators; 3.12 Mathematical Morphology; 3.12.1 Generalized Morphological Dilation; 3.12.2 Generalized Morphological Erosion; 3.12.3 Duality Between Dilation and Erosion; 3.12.4 Properties of Dilation and Erosion Operators; 3.12.5 Closing and Opening; 3.12.6 Summary of Basic Morphological Operations; 3.13 Morphological Grouping; 3.14 Morphology in Grayscale Images; 3.15 Concluding Remarks; 3.16 Bibliographical and Historical Notes; 3.16.1 More Recent Developments; 3.17 Problems.
- 4 The role of thresholding4.1 Introduction; 4.2 Region-Growing Methods; 4.3 Thresholding; 4.3.1 Finding a Suitable Threshold; 4.3.2 Tackling the Problem of Bias in Threshold Selection; 4.4 Adaptive Thresholding; 4.4.1 Local Thresholding Methods; 4.5 More Thoroughgoing Approaches to Threshold Selection; 4.5.1 Variance-Based Thresholding; 4.5.2 Entropy-Based Thresholding; 4.5.3 Maximum Likelihood Thresholding; 4.6 The Global Valley Approach to Thresholding; 4.7 Practical Results Obtained Using the Global Valley Method; 4.8 Histogram Concavity Analysis; 4.9 Concluding Remarks.