Contents – Image Analysis


1Introduction to Image Analysis

1.1Image and Image Engineering

1.1.1Image Foundation

1.1.2Image Engineering

1.2The Scope of Image Analysis

1.2.1Definition and Research Content of Image Analysis

1.2.2Image Analysis System

1.3Digitization in Image Analysis

1.3.1Discrete Distance

1.3.2Connected Component

1.3.3Digitizing Model

1.3.4Digital Arcs and Chords

1.4Distance Transforms

1.4.1Definition and Property

1.4.2Computation of Local Distances

1.4.3Implementation of Discrete Distance Transformation

1.5Overview of the Book

1.6Problems and Questions

1.7Further Reading

2Image Segmentation

2.1Definition and Classification

2.1.1Definition of Segmentation

2.1.2Classification of Algorithms

2.2Basic Technique Groups

2.2.1Boundary-Based Parallel Algorithms

2.2.2Boundary-Based Sequential Algorithms

2.2.3Region-based Parallel Algorithms

2.2.4Region-based Sequential Algorithms

2.3Extension and Generation

2.3.1Extending 2-D Algorithms to 3-D

2.3.2Generalization of Some Techniques

2.4Segmentation Evaluation

2.4.1A Survey on Evaluation Methods

2.4.2An Effective Evaluation Method

2.4.3Systematic Comparison

2.5Problems and Questions

2.6Further Reading

3Object Representation and Description

3.1Classification of Representation and Description

3.2Boundary-Based Representation

3.2.1Taxonomy of Boundary-Based Representation

3.2.2Chain Codes

3.2.3Boundary Segments

3.2.4Polygonal Approximation

3.2.5Boundary Signatures

3.2.6Landmark Points

3.3Region-Based Representation

3.3.1Taxonomy of Region-Based Representation

3.3.2Bounding Regions




3.4Transform-Based Representation

3.4.1Technique Classification

3.4.2Fourier Boundary Representation

3.5Descriptors for Boundary

3.5.1Some Straightforward Descriptors

3.5.2Shape Numbers

3.5.3Boundary Moments

3.6Descriptors for Regions

3.6.1Some Basic Descriptors

3.6.2Topological Descriptors

3.7Problems and Questions

3.8Further Reading

4Feature Measurement and Error Analysis

4.1Direct and Indirect Measurements

4.1.1Direct Measurements

4.1.2Derived Measurements

4.1.3Measurement Combinations

4.2Accuracy and Precision



4.2.3Statistical Error and Systematic Error

4.3Two Types of Connectivity

4.3.1Boundary Points and Internal Points

4.3.2Object Points and Background Points

4.3.3Separating Connected Components

4.3.4Open Set and Closed Set

4.4Feature Measurement Error

4.4.1Different Factors Influencing Measurement Accuracy

4.4.2Influence of Optical Lens Resolution

4.4.3Influence of Sampling Density

4.4.4Influence of Segmentation

4.4.5Influence of Computation Formulas

4.4.6Combined Influences

4.5Error Analysis

4.5.1Upper and Lower Bounds of an 8-Digital Straight Segment

4.5.2Approximation Errors

4.6Problems and Questions

4.7Further Reading

5Texture Analysis

5.1Concepts and Classification

5.1.1Meanings and Scale

5.1.2Research and Application Related to Texture

5.1.3Approaches for Texture Analysis

5.2Statistical Approaches

5.2.1Co-occurrence Matrix

5.2.2Descriptors Based on a Gray-Level Co-occurrence Matrix

5.2.3Law’s Texture Energy Measurements

5.3Structural Approaches

5.3.1Two Basic Components

5.3.2Typical Structural Methods

5.3.3Local Binary Mode

5.4Spectral Approaches

5.4.1Fourier Spectrum

5.4.2Bessel-Fourier Spectrum

5.4.3Gabor Spectrum

5.5Texture Segmentation

5.5.1Supervised Texture Segmentation

5.5.2Unsupervised Texture Segmentation

5.5.3Texture Classification Based on Wavelet Transformation

5.6Problems and Questions

5.7Further Reading

6Shape Analysis

6.1Definitions and Tasks

6.1.1Definition of Shape

6.1.2Shape Analysis Tasks

6.2Different Classes of 2-D Shapes

6.2.1Classification of Shapes

6.2.2Further Discussions

6.3Description of Shape Property

6.3.1Compactness Descriptors

6.3.2Complexity Descriptors

6.4Technique-Based Descriptors

6.4.1Polygonal Approximation-Based Shape Descriptors

6.4.2Curvature-Based Shape Descriptors

6.5Wavelet Boundary Descriptors

6.5.1Definition and Normalization

6.5.2Properties of the Wavelet Boundary Descriptor

6.5.3Comparisons with Fourier Descriptors

6.6Fractal Geometry

6.6.1Set and Dimension

6.6.2The Box-Counting Approach

6.6.3Implementing the Box-Counting Method


6.7Problems and Questions

6.8Further Reading

7Motion Analysis

7.1The Purpose and Subject of Motion Analysis

7.1.1Motion Detection

7.1.2Locating and Tracking Moving Objects

7.1.3Moving Object Segmentation and Analysis

7.1.4Three-Dimensional Scene Reconstruction and Motion Understanding

7.2Motion Detection

7.2.1Motion Detection Using Image Differences

7.2.2Model-Based Motion Detection

7.3Moving Object Detection

7.3.1Background Modeling

7.3.2Optical Flow

7.3.3Detecting Specific Movement Pattern

7.4Moving Object Segmentation

7.4.1Object Segmentation and Motion Information Extraction

7.4.2Dense Optical Flow Algorithm

7.4.3Parameter and Model-Based Segmentation

7.5Moving Object Tracking

7.5.1Typical Technology

7.5.2Subsequences Decision Strategy

7.6Problems and Questions

7.7Further Reading

8Mathematical Morphology

8.1Basic Operations of Binary Morphology

8.1.1Binary Dilation and Erosion

8.1.2Binary Opening and Closing

8.2Combined Operations of Binary Morphology

8.2.1Hit-or-Miss Transform

8.2.2Binary Composition Operations

8.3Practical Algorithms of Binary Morphology

8.3.1Noise Removal

8.3.2Corner Detection

8.3.3Boundary Extraction

8.3.4Object Detection and Localization

8.3.5Region Filling

8.3.6Extraction of Connected Components

8.3.7Calculation of Region Skeleton

8.4Basic Operations of Grayscale Morphology

8.4.1Grayscale Dilation and Erosion

8.4.2Grayscale Opening and Closing

8.5Combined Operations of Grayscale Morphology

8.5.1Morphological Gradient

8.5.2Morphological Smoothing

8.5.3Top Hat Transform and Bottom Hat Transform

8.5.4Morphological Filters

8.5.5Soft Morphological Filters

8.6Practical Algorithms of Grayscale Morphology

8.6.1Background Estimation and Elimination

8.6.2Morphological Edge Detection

8.6.3Cluster Fast Segmentation

8.7Problems and Questions

8.8Further Reading

Answers to Selected Problems and Questions