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Preface.
Chapter 1 Practical Aspects of a Vision System - Image Display, Input/Output, and Library Calls.
OpenCV.
The Basic OpenCV Code.
The IplImage Data Structure.
Reading and Writing Images.
Image Display.
An Example.
Image Capture.
Interfacing with the AIPCV Library.
Website Files.
References.
Chapter 2 Edge-Detection Techniques.
The Purpose of Edge Detection.
Traditional Approaches and Theory.
Models of Edges.
Noise.
Derivative Operators.
Template-Based Edge Detection.
Edge Models: The Marr-Hildreth Edge Detector.
The Canny Edge Detector.
The Shen-Castan (ISEF) Edge Detector.
A Comparison of Two Optimal Edge Detectors.
Color Edges.
Source Code for the Marr-Hildreth Edge Detector.
Source Code for the Canny Edge Detector.
Source Code for the Shen-Castan Edge Detector.
Website Files.
References.
Chapter 3 Digital Morphology.
Morphology Defined.
Connectedness.
Elements of Digital Morphology-Binary Operations.
Binary Dilation.
Implementing Binary Dilation.
Binary Erosion.
Implementation of Binary Erosion.
Opening and Closing.
MAX-A High-Level Programming Language for Morphology.
The ´Hit-and-Miss´ Transform.
Identifying Region Boundaries.
Conditional Dilation.
Counting Regions.
Grey-Level Morphology.
Opening and Closing.
Smoothing.
Gradient.
Segmentation of Textures.
Size Distribution of Objects.
Color Morphology.
Website Files.
References.
Chapter 4 Grey-Level Segmentation.
Basics of Grey-Level Segmentation.
Using Edge Pixels.
Iterative Selection.
The Method of Grey-Level Histograms.
Using Entropy.
Fuzzy Sets.
Minimum Error Thresholding.
Sample Results From Single Threshold Selection.
The Use of Regional Thresholds.
Chow and Kaneko.
Modeling Illumination Using Edges.
Implementation and Results.
Comparisons.
Relaxation Methods.
Moving Averages.
Cluster-Based Thresholds.
Multiple Thresholds.
Website Files.
References.
Chapter 5 Texture and Color.
Texture and Segmentation.
A Simple Analysis of Texture in Grey-Level Images.
Grey-Level Co-Occurrence.
Maximum Probability.
Moments.
Contrast.
Homogeneity.
Entropy.
Results from the GLCM Descriptors.
Speeding Up the Texture Operators.
Edges and Texture.
Energy and Texture.
Surfaces and Texture.
Vector Dispersion.
Surface Curvature.
Fractal Dimension.
Color Segmentation.
Color Textures.
Website Files.
References.
Chapter 6 Thinning.
What Is a Skeleton?
The Medial Axis Transform.
Iterative Morphological Methods.
The Use of Contours.
Choi/Lam/Siu Algorithm.
Treating the Object as a Polygon.
Triangulation Methods.
Force-Based Thinning.
Definitions.
Use of a Force Field.
Subpixel Skeletons.
Source Code for Zhang-Suen/Stentiford/Holt Combined Algorithm.
Website Files.
References.
Chapter 7 Image Restoration.
Image Degradations-The RealWorld.
The Frequency Domain.
The Fourier Transform.
The Fast Fourier Transform.
The Inverse Fourier Transform.
Two-Dimensional Fourier Transforms.
Fourier Transforms in OpenCV.
Creating Artificial Blur.
The Inverse Filter.
TheWiener Filter.
Structured Noise.
Motion Blur-A Special Case.
The Homomorphic Filter-Illumination.
Frequency Filters in General.
Isolating Illumination Effects.
Website Files.
References.
Chapter 8 Classification.
Objects, Patterns, and Statistics.
Features and Regions.
Training and Testing.
Variation: In-Class and Out-Class.
Minimum Distance Classifiers.
Distance Metrics.
Distances Between Features.
Cross Validation.
Support Vector Machines.
Multiple Classifiers-Ensembles.
Merging Multiple Methods.
Merging Type 1 Responses.
Evaluation.
Converting Between Response Types.
Merging Type 2 Responses.
Merging Type 3 Responses.
Bagging and Boosting.
Bagging.
Boosting.
Website Files.
References.
Chapter 9 Symbol Recognition.
The Problem.
OCR on Simple Perfect Images.
OCR on Scanned Images-Segmentation.
Noise.
Isolating