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Computer Science
Computer Graphics and Visualization
Digital Imaging and Processing
1. Fundamentals of Digital Imaging
2. Image Enhancement in the Spatial Domain
3. Image Enhancement in the Frequency Domain
4. Image Restoration
5. Color Image Processing
6. Image Compression
7. Morphological Image Processing
8. Image Segmentation
9. Feature Extraction and Description
10. Pattern Recognition and Classification
11. Advanced Topics and Applications
Feature Extraction and Description
Feature Representation Fundamentals
Feature Types
Geometric Features
Statistical Features
Structural Features
Feature Selection Criteria
Discriminability
Reliability
Independence
Computational Efficiency
Boundary Representation and Description
Chain Codes
Freeman Chain Code
Differential Chain Code
Properties and Normalization
Polygonal Approximations
Minimum Perimeter Polygons
Merging Techniques
Splitting Techniques
Signatures
Boundary Signatures
Complex Coordinates
Skeletons
Medial Axis Transform
Morphological Skeleton
Boundary Descriptors
Simple Descriptors
Length and Perimeter
Diameter
Major and Minor Axes
Eccentricity
Shape Numbers
Definition and Computation
Invariance Properties
Fourier Descriptors
Fourier Transform of Boundary
Normalization for Invariance
Reconstruction
Statistical Moments
Boundary Moments
Central Moments
Normalized Moments
Regional Descriptors
Simple Descriptors
Area
Perimeter
Compactness
Circularity
Topological Descriptors
Euler Number
Connectivity Number
Holes and Connected Components
Texture Descriptors
Statistical Approaches
First-Order Statistics
Mean
Variance
Skewness
Kurtosis
Second-Order Statistics
Co-occurrence Matrices
Contrast
Correlation
Energy
Homogeneity
Higher-Order Statistics
Structural Approaches
Texture Primitives
Spatial Relationships
Texture Grammar
Spectral Approaches
Fourier Spectrum Features
Gabor Filters
Wavelet Features
Moment Invariants
Geometric Moments
Central Moments
Hu Moments
Zernike Moments
Dimensionality Reduction
Principal Component Analysis
Covariance Matrix Computation
Eigenvalue Decomposition
Feature Space Transformation
Dimensionality Selection
Linear Discriminant Analysis
Between-Class and Within-Class Scatter
Fisher's Linear Discriminant
Independent Component Analysis
Statistical Independence
Applications in Feature Extraction
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8. Image Segmentation
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10. Pattern Recognition and Classification