Image Analysis

Image Analysis

by Tsinghua University Tsinghua University Press, Yujin Zhang
Released August 2017
Publisher(s): De Gruyter
ISBN: 9783110524284

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Book description

This graduate textbook presents fundamentals, applications and evaluation of image segregation, unit description, feature measurement and pattern recognition. Analysis on textile, shape and motion are discussed and mathematical tools are employed extensively. Rich in examples and excises, it prepares electrical engineering and computer science students with knowledge and skills for further studies on image understanding.

Table of contents

  1. Cover
  2. Title Page
  3. Copyright
  4. Contents
  5. 1 Introduction to Image Analysis
    1. 1.1 Image and Image Engineering
      1. 1.1.1 Image Foundation
      2. 1.1.2 Image Engineering
    2. 1.2 The Scope of Image Analysis
      1. 1.2.1 Definition and Research Content of Image Analysis
      2. 1.2.2 Image Analysis System
    3. 1.3 Digitization in Image Analysis
      1. 1.3.1 Discrete Distance
      2. 1.3.2 Connected Component
      3. 1.3.3 Digitizing Model
      4. 1.3.4 Digital Arcs and Chords
    4. 1.4 Distance Transforms
      1. 1.4.1 Definition and Property
      2. 1.4.2 Computation of Local Distances
      3. 1.4.3 Implementation of Discrete Distance Transformation
    5. 1.5 Overview of the Book
    6. 1.6 Problems and Questions
    7. 1.7 Further Reading
  6. 2 Image Segmentation
    1. 2.1 Definition and Classification
      1. 2.1.1 Definition of Segmentation
      2. 2.1.2 Classification of Algorithms
    2. 2.2 Basic Technique Groups
      1. 2.2.1 Boundary-Based Parallel Algorithms
      2. 2.2.2 Boundary-Based Sequential Algorithms
      3. 2.2.3 Region-based Parallel Algorithms
      4. 2.2.4 Region-based Sequential Algorithms
    3. 2.3 Extension and Generation
      1. 2.3.1 Extending 2-D Algorithms to 3-D
      2. 2.3.2 Generalization of Some Techniques
    4. 2.4 Segmentation Evaluation
      1. 2.4.1 A Survey on Evaluation Methods
      2. 2.4.2 An Effective Evaluation Method
      3. 2.4.3 Systematic Comparison
    5. 2.5 Problems and Questions
    6. 2.6 Further Reading
  7. 3 Object Representation and Description
    1. 3.1 Classification of Representation and Description
    2. 3.2 Boundary-Based Representation
      1. 3.2.1 Taxonomy of Boundary-Based Representation
      2. 3.2.2 Chain Codes
      3. 3.2.3 Boundary Segments
      4. 3.2.4 Polygonal Approximation
      5. 3.2.5 Boundary Signatures
      6. 3.2.6 Landmark Points
    3. 3.3 Region-Based Representation
      1. 3.3.1 Taxonomy of Region-Based Representation
      2. 3.3.2 Bounding Regions
      3. 3.3.3 Quad-Trees
      4. 3.3.4 Pyramids
      5. 3.3.5 Skeletons
    4. 3.4 Transform-Based Representation
      1. 3.4.1 Technique Classification
      2. 3.4.2 Fourier Boundary Representation
    5. 3.5 Descriptors for Boundary
      1. 3.5.1 Some Straightforward Descriptors
      2. 3.5.2 Shape Numbers
      3. 3.5.3 Boundary Moments
    6. 3.6 Descriptors for Regions
      1. 3.6.1 Some Basic Descriptors
      2. 3.6.2 Topological Descriptors
    7. 3.7 Problems and Questions
    8. 3.8 Further Reading
  8. 4 Feature Measurement and Error Analysis
    1. 4.1 Direct and Indirect Measurements
      1. 4.1.1 Direct Measurements
      2. 4.1.2 Derived Measurements
      3. 4.1.3 Measurement Combinations
    2. 4.2 Accuracy and Precision
      1. 4.2.1 Definitions
      2. 4.2.2 Relationships
      3. 4.2.3 Statistical Error and Systematic Error
    3. 4.3 Two Types of Connectivity
      1. 4.3.1 Boundary Points and Internal Points
      2. 4.3.2 Object Points and Background Points
      3. 4.3.3 Separating Connected Components
      4. 4.3.4 Open Set and Closed Set
    4. 4.4 Feature Measurement Error
      1. 4.4.1 Different Factors Influencing Measurement Accuracy
      2. 4.4.2 Influence of Optical Lens Resolution
      3. 4.4.3 Influence of Sampling Density
      4. 4.4.4 Influence of Segmentation
      5. 4.4.5 Influence of Computation Formulas
      6. 4.4.6 Combined Influences
    5. 4.5 Error Analysis
      1. 4.5.1 Upper and Lower Bounds of an 8-Digital Straight Segment
      2. 4.5.2 Approximation Errors
    6. 4.6 Problems and Questions
    7. 4.7 Further Reading
  9. 5 Texture Analysis
    1. 5.1 Concepts and Classification
      1. 5.1.1 Meanings and Scale
      2. 5.1.2 Research and Application Related to Texture
      3. 5.1.3 Approaches for Texture Analysis
    2. 5.2 Statistical Approaches
      1. 5.2.1 Co-occurrence Matrix
      2. 5.2.2 Descriptors Based on a Gray-Level Co-occurrence Matrix
      3. 5.2.3 Law’s Texture Energy Measurements
    3. 5.3 Structural Approaches
      1. 5.3.1 Two Basic Components
      2. 5.3.2 Typical Structural Methods
      3. 5.3.3 Local Binary Mode
    4. 5.4 Spectral Approaches
      1. 5.4.1 Fourier Spectrum
      2. 5.4.2 Bessel-Fourier Spectrum
      3. 5.4.3 Gabor Spectrum
    5. 5.5 Texture Segmentation
      1. 5.5.1 Supervised Texture Segmentation
      2. 5.5.2 Unsupervised Texture Segmentation
      3. 5.5.3 Texture Classification Based on Wavelet Transformation
    6. 5.6 Problems and Questions
    7. 5.7 Further Reading
  10. 6 Shape Analysis
    1. 6.1 Definitions and Tasks
      1. 6.1.1 Definition of Shape
      2. 6.1.2 Shape Analysis Tasks
    2. 6.2 Different Classes of 2-D Shapes
      1. 6.2.1 Classification of Shapes
      2. 6.2.2 Further Discussions
    3. 6.3 Description of Shape Property
      1. 6.3.1 Compactness Descriptors
      2. 6.3.2 Complexity Descriptors
    4. 6.4 Technique-Based Descriptors
      1. 6.4.1 Polygonal Approximation-Based Shape Descriptors
      2. 6.4.2 Curvature-Based Shape Descriptors
    5. 6.5 Wavelet Boundary Descriptors
      1. 6.5.1 Definition and Normalization
      2. 6.5.2 Properties of the Wavelet Boundary Descriptor
      3. 6.5.3 Comparisons with Fourier Descriptors
    6. 6.6 Fractal Geometry
      1. 6.6.1 Set and Dimension
      2. 6.6.2 The Box-Counting Approach
      3. 6.6.3 Implementing the Box-Counting Method
      4. 6.6.4 Discussions
    7. 6.7 Problems and Questions
    8. 6.8 Further Reading
  11. 7 Motion Analysis
    1. 7.1 The Purpose and Subject of Motion Analysis
      1. 7.1.1 Motion Detection
      2. 7.1.2 Locating and Tracking Moving Objects
      3. 7.1.3 Moving Object Segmentation and Analysis
      4. 7.1.4 Three-Dimensional Scene Reconstruction and Motion Understanding
    2. 7.2 Motion Detection
      1. 7.2.1 Motion Detection Using Image Differences
      2. 7.2.2 Model-Based Motion Detection
    3. 7.3 Moving Object Detection
      1. 7.3.1 Background Modeling
      2. 7.3.2 Optical Flow
      3. 7.3.3 Detecting Specific Movement Pattern
    4. 7.4 Moving Object Segmentation
      1. 7.4.1 Object Segmentation and Motion Information Extraction
      2. 7.4.2 Dense Optical Flow Algorithm
      3. 7.4.3 Parameter and Model-Based Segmentation
    5. 7.5 Moving Object Tracking
      1. 7.5.1 Typical Technology
      2. 7.5.2 Subsequences Decision Strategy
    6. 7.6 Problems and Questions
    7. 7.7 Further Reading
  12. 8 Mathematical Morphology
    1. 8.1 Basic Operations of Binary Morphology
      1. 8.1.1 Binary Dilation and Erosion
      2. 8.1.2 Binary Opening and Closing
    2. 8.2 Combined Operations of Binary Morphology
      1. 8.2.1 Hit-or-Miss Transform
      2. 8.2.2 Binary Composition Operations
    3. 8.3 Practical Algorithms of Binary Morphology
      1. 8.3.1 Noise Removal
      2. 8.3.2 Corner Detection
      3. 8.3.3 Boundary Extraction
      4. 8.3.4 Object Detection and Localization
      5. 8.3.5 Region Filling
      6. 8.3.6 Extraction of Connected Components
      7. 8.3.7 Calculation of Region Skeleton
    4. 8.4 Basic Operations of Grayscale Morphology
      1. 8.4.1 Grayscale Dilation and Erosion
      2. 8.4.2 Grayscale Opening and Closing
    5. 8.5 Combined Operations of Grayscale Morphology
      1. 8.5.1 Morphological Gradient
      2. 8.5.2 Morphological Smoothing
      3. 8.5.3 Top Hat Transform and Bottom Hat Transform
      4. 8.5.4 Morphological Filters
      5. 8.5.5 Soft Morphological Filters
    6. 8.6 Practical Algorithms of Grayscale Morphology
      1. 8.6.1 Background Estimation and Elimination
      2. 8.6.2 Morphological Edge Detection
      3. 8.6.3 Cluster Fast Segmentation
    7. 8.7 Problems and Questions
    8. 8.8 Further Reading
  13. Answers to Selected Problems and Questions
  14. References
  15. Index

Product information

  • Title: Image Analysis
  • Author(s): Tsinghua University Tsinghua University Press, Yujin Zhang
  • Release date: August 2017
  • Publisher(s): De Gruyter
  • ISBN: 9783110524284