### Transcription of Machine Vision - USF

1 **Machine** **Vision** **Machine** **Vision** . Ramesh Jain, Rangachar Kasturi, Brian G. Schunck Published by McGraw-Hill, Inc., ISBN 0-07-032018-7, 1995. The field of **Machine** **Vision** , or computer **Vision** , has been growing at a fast pace. As in most fast-developing fields, not all aspects of **Machine** **Vision** that are of interest to active researchers are useful to the designers and users of a **Vision** system for a specific application. This text is intended to provide a balanced introduction to **Machine** **Vision** . Basic concepts are introduced with only essential mathematical elements. The details to allow implementation and use of **Vision** algorithm in practical application are provided, and engineering aspects of techniques are emphasized. This text intentionally omits theories of **Machine** **Vision** that do not have sufficient practical applications at the time. This book is designed for people who want to apply **Machine** **Vision** to solve problems. Chapter Index: Front Matter Chapter 1.

2 Introduction (pp. 1-24). **Machine** **Vision** Relationships to Other Fields Role of Knowledge Image Geometry 1 Perspective Projection Coordinate Systems Sam ling and Quantization Image Definitions Levels of Computation Point Level Local Level Global Level Object Level Road Map Chapter 2. Binary Image Processing (pp. 25-72). Thresholding Geometric Properties Size Position Orientation Projections Run-Length Encoding Binary Algorithms Definitions Component Labeling Size Filter Euler Number Region Boundary Area and Perimeter Compactness Distance Measures Distance Transforms Medial Axis Thinning Expanding and Shrinking Morphological Operators Optical Character Recognition Chapter 3. Regions (pp. 73-111). Regions and Edges Region Segmentation Automatic Thresholding Limitations of Histogram Methods Region Representation Array Representation Hierarchical Representations Symbolic Representations Data Structures for Segmentation Split and Merge Region Merging Removing Weak Edges Region Splitting Split and Merge Region Growing Chapter 4.

3 Image Filtering (pp. 112-139). Image Filtering Histogram Modification Linear Systems Linear Filters Median Filter Gaussian Smoothing Rotational Symmetry Fourier Transform Property Gaussian Separability Cascading Gaussians Designing Gaussian Filters Discrete Gaussian Filters Chapter 5. Edge Detection (pp. 140-185). Gradient Steps in Edge Detection Roberts Operator Sobel Operator Prewitt Operator Comparison Second Derivative Operators Laplacian Operator Second Directional Derivative Laplacian of Gaussian Image Approximation Gaussian Edge Detection Canny Edge Detector Subpixel Location Estimation Edge Detector Performance Methods for Evaluating Performance Figure of Merit Sequential Methods Line Detection Chapter 6. Contours (pp. 186-233). Geometry of Curves Digital Curves Chain Codes Slope Representation Slope Density Function Curve Fitting Polyline Representation Polyline Splitting Segment Merging Split and Merge Hop-Along Algorithm Circular Arcs Conic Sections Spline Curves Curve Approximation Total Regression Estimating Corners Robust Regression Hough Transform Fourier Descriptors Chapter 7.

4 Texture (pp. 234-248). Introduction Statistical Methods of Texture Analysis Structural Analysis of Ordered Texture Model-Based Methods for Texture Analysis Shape from Texture Chapter 8. Optics (pp. 249-256). Lens Equation Image Resolution Depth of Field View Volume Exposure Chapter 9. Shading (pp. 257-275). Image Irradiance Illumination Reflectance Surface Orientation The Reflectance Map Diffuse Reflectance Scanning Electron Microscopy Shape from Shading Photometric Stereo Chapter 10. Color (pp. 276-288). Color Physics Color Terminology Color Perception Color Processing Color Constancy Discussion Chapter 11. Depth (pp. 289-308). Stereo Imaging Cameras in Arbitrary Position and Orientation Stereo Matching Edge Matching Region Correlation Shape from X. Range Imaging Structured Lighting Imaging Radar Active **Vision** Chapter 12. Calibration (pp. 309-364). Coordinate Systems Rigid Body Transformations Rotation Matrices Axis of Rotation Unit Quaternions Absolute Orientation Relative Orientation Rectification Depth from Binocular Stereo Absolute Orientation with Scale Exterior Orientation Calibration Example Interior Orientation Camera Calibration Simple Method for Camera Calibration Affine Method for Camera Calibration Nonlinear Method for Camera Calibration Binocular Stereo Calibration Active Triangulation Robust Methods Conclusions Chapter 13.

5 Curves and Surfaces (pp. 365-405). Fields Geometry of Curves Geometry of Surfaces Planes Differential Geometry Curve Representations Cubic Spline Curves Surface Representations Polygonal Meshes Surface Patches Tensor-Product Surfaces Surface Interpolation Triangular Mesh Interpolation Bilinear Interpolation Robust Interpolation Surface Approximation Regression Splines Variational Methods Weighted Spline Approximation Surface Segmentation Initial Segmentation Extending Surface Patches Surface Registration Chapter 14. Dynamic **Vision** (pp. 406-458). Change Detection Difference Pictures Static Segmentation and Matching Segmentation Using Motion Time-Varying Edge Detection Stationary Camera Motion Correspondence Image Flow Computing Image Flow Feature-Based Methods Gradient-Based Methods Variational Methods for Image Flow Robust Computation of Image Flow Information in Image Flow Segmentation Using a Moving Camera Ego-Motion Complex Log Mapping Depth Determination Tracking Deviation Function for Path Coherence Path Coherence Function Path Coherence in the Presence of Occlusion Modified Greedy Exchange Algorithm Shape from Motion Chapter 15.

6 Object Recognition (pp. 459-491). System Components Complexity of Object Recognition Object Representation Observer-Centered Representations Object-Centered Representations Feature Detection Recognition Strategies Classification Matching Feature Indexing Verification Template Matching Morphological Approach Symbolic Analogical Methods Appendix A. Mathematical Concepts (pp. 492-501). Analytic Geometry Linear Algebra Variational Calculus Numerical Methods Appendix B. Statistical Methods (pp. 502-510). Measurement Errors Error Distributions Linear Regression Nonlinear Regression Appendix C. Programming Techniques (pp. 511-518). Image Descriptors Mapping operations Image File Formats Bibliography (pp. 519-541). Index (pp. 542-549). file:///C|/Users/mshreve/Desktop/ [7/13/2010 3:50:43 PM].