ISBN-10:
049508252X
ISBN-13:
9780495082521
Pub. Date:
03/19/2007
Publisher:
CL Engineering
Image Processing, Analysis, and Machine Vision / Edition 3

Image Processing, Analysis, and Machine Vision / Edition 3

Hardcover

Current price is , Original price is $304.95. You

Temporarily Out of Stock Online

Please check back later for updated availability.

This item is available online through Marketplace sellers.

Overview


This robust text provides deep and wide coverage of the full range of topics encountered in the field of image processing and machine vision. As a result, it can serve undergraduates, graduates, researchers, and professionals looking for a readable reference. The book's encyclopedic coverage of topics is wide, and it can be used in more than one course (both image processing and machine vision classes). In addition, while advanced mathematics is not needed to understand basic concepts (making this a good choice for undergraduates), rigorous mathematical coverage is included for more advanced readers. It is also distinguished by its easy-to-understand algorithm descriptions of difficult concepts, and a wealth of carefully selected problems and examples.

Product Details

ISBN-13: 9780495082521
Publisher: CL Engineering
Publication date: 03/19/2007
Edition description: Older Edition
Pages: 872
Product dimensions: 9.30(w) x 7.90(h) x 1.50(d)

About the Author

Milan Sonka is Professor of Electrical and Computer Engineering at the University of Iowa. His research interests include medical image analysis, computer-aided diagnosis, and machine vision.


Vaclav Hlavac is Professor of Cybernetics at the Czech Technical University, Prague. his research interests are knowledge based image analysis, 3D model-based vision and relations between statistical and structural pattern recognition.


Roger Boyle is Professor Emeritus of Computing and was Head of the School of Computing at the University of Leeds, England where his research interests are low-level vision and pattern recognition.

Table of Contents


1. Introduction Motivation / Why is Computer Vision Difficult? / Image Representation and Image Analysis Tasks / Summary / References 2. The Image, its Representations and Properties Image Representations, a Few Concepts / Image Digitization / Sampling / Quantization / Digital Image Properties / Metric and Topological Properties of Digital Images / Histograms / Entropy / Visual Perception of the Image / Image Quality / Noise in Images / Color Images / Physics of Color / Color Perceived by Humans / Color Spaces / Palette Images / Color Constancy / Cameras: An Overview / Photosensitive Sensors / A Monochromatic Camera / A Color Camera / Summary / References 3. The Image, its Mathematical and Physical Background Overview / Linearity / The Dirac Distribution and Convolution / Linear Integral Transforms / Images as Linear Systems / Introduction to Linear Integral Transforms / 1D Fourier Transform / 2D Fourier Transform / Sampling and the Shannon Constraint / Discrete Cosine Transform / Wavelet Transform / Eigen-Analysis / Singular Value Decomposition / Principle Component Analysis / Other Orthogonal Image Transforms / Images as Stochastic Processes / Image Formation Physics / Images as Radiometric Measurements / Image Capture and Geometric Optics / Lens Aberrations and Radial Distortion / Image Capture from a Radiometric Point of View / Surface Reflectance / Summary / References 4. Data Structures for Image Analysis Levels of Image Data Representation / Traditional Image Data Structures / Matrices / Chains / Topological Data Structures / Relational Structures / Hierarchical Data Structures / Pyramids / Quadtrees / Other Pyramidal Structures / Summary / References 5. Image Pre-Processing Pixel Brightness Transformations / Position-Dependent Brightness Correction / Gray-Scale Transformation / Geometric Transformations / Pixel Co-ordinate Transformations / Brightness Interpolation / Local Pre-Processing / Image Smoothing / Edge Detectors / Zero-Crossings of the Second Derivative / Scale in Image Processing / Canny Edge Detection / Parametric Edge Models / Edges in Multi-Spectral Images / Local Detection by Local Pre-Processing Operators / Detection of Corners (Interest Points) / Detection of Maximally Stable Extremal Regions / Image Restoration / Degradations That are Easy to Restore / Inverse Filtration / Wiener Filtration / Summary / References 6. Segmentation I Thresholding / Threshold Detection Methods / Optimal Thresholding / Multi-Spectral Thresholding / Edge Based Segmentation / Edge Image Thresholding / Edge Relaxation / Border Tracing / Border Detection as graph Searching / Border Detection as Dynamic Programming / Hough Transforms / Border Detection Using Border Location Information / Region Construction from Borders / Region Based Segmentation / Region Merging / Region Splitting / Splitting and Merging / Watershed Segmentation / Region Growing Post-Processing / Matching / Matching Criteria / Control Strategies of Matching / Evaluation Issues in Segmentation / Supervised Evaluation / Unsupervised Evaluation / Summary / References 7. Segmentation II Mean Shift Segmentation / Active Contour Models - Snakes / Traditional Snakes and Balloons / Extensions / Gradient Vector Flow Snakes / Geometric Deformable Models - Level Sets and Geodesic Active Contours / Fuzzy Connectivity / Towards 3D Graph-Based Image Segmentation / Simultaneous Detection of Border Pairs / Sub-optimal Surface Detection / Graph Cut Segmentation / Optimal Single and Multiple Surface Segmentation / Summary / References 8. Shape Representation and Description Region Identification / Contour-Based Shape Representation and Description / Chain Codes / Simple Geometric Border Representation / Fourier Transforms of Boundaries / Boundary Description using Segment Sequences / B-Spline Representation / Other Contour-Based Shape Description Approaches / Shape Invariants / Region-Based Shape Representation and Description / Simple Scalar Region Descriptors / Moments / Convex Hull / Graph Representation Based on Region Skeleton / Region Decomposition / Region Neighborhood Graphs / Shape Classes / Summary / References 9. Object Recognition Knowledge Representation / Statistical Pattern Recognition / Classification Principles / Classifier Setting / Classifier Learning / Support Vector Machines / Cluster Analysis / Neural Nets / Feed-Forward Networks / Unsupervised Learning / Hopefield Neural Nets / Syntactic Pattern Recognition / Grammars and Languages / Syntactic Analysis, Syntactic Classifier / Syntactic Classifier Learning, Grammar Inference / Recognition as Graph Matching / Isomorphism of Graphs and Sub-Graphs / Similarity of Graphs / Optimization Techniques in Recognition / Genetic Algorithms / Simulated Annealing / Fuzzy Systems / Fuzzy Sets and Fuzzy Membership Functions / Fuzzy Set Operators / Fuzzy reasoning / Fuzzy System Design and Training / Boosting in Pattern Recognition / Summary / References 10. Image Understanding Image Understanding Control Strategies / Parallel and Serial Processing Control / Hierarchical Control / Bottom-Up Control / Model-Based Control / Combined Control / Non-Hierarchical Control / RANSAC: Fitting via Random Sample Consensus / Point Distribution Models / Active Appearance Models / Pattern Recognition Methods in Image Understanding / Classification-Based Segmentation / Contextual Image Classification / Boosted Cascade of Classifiers for Rapid Object Detection / Scene Labeling and Constraint Propagation / Discrete Relaxation / Probabilistic Relaxation / Searching Interpretation Trees / Semantic Image Segmentation and Understanding / Semantic Region Growing / Genetic Image Interpretation / Hidden Markov Models / Coupled HMMs / Bayesian Belief Networks / Gaussian Mixture Models and Expectation-Maximization / Summary / References 11. 3D Vision, Geometry 3D Vision Tasks / Marrs Theory / Other Vision Paradigms: Active and Purposive Vision / Basics of Projective Geometry / Points and Hyperplanes in Projective Space / Homography / Estimating Homography from Point Correspondences / A Single Perspective Camera / Camera Model / Projection and Back-Projection in Homogeneous Coordinates / Camera Calibration from a Known Scene / Scene Reconstruction from Multiple Views / Triangulation / Projective Reconstruction / Matching Constraints. Bundle Adjustment / Upgrading the Projective Reconstruction, Self Calibration / Two Cameras, Stereopsis / Epipolar Geometry; Fundamental Matrix / Relative Motion of the Camera; Essential Matrix / Decomposing the Fundamental Matrix from Point Correspondences / Rectified Configuration of Two Cameras / Computing Rectification / Three Cameras and Trifocal Tensor / Stereo Correspondence Algorithms / Active Acquisition of Range Images / 3D Information from Radiometric Measurements / Shape from Shading / Photometric Stereo / Summary / References 12. Use of 3D Vision Shape from X / Shape from Motion / Shape from Texture / Other Shape from X Techniques / Full 3D Objects / 3D Objects, Models, and Related Issues / Line Labeling / Volumetric Representation, Direct Measurements / Volumetric Modeling Strategies / Surface Modeling Strategies / Registering Surface Patches and their Fusion to get a Full 3D Model / 3D Model-Based Vision / General Considerations / Goads Algorithm / Model-Based Recognition of Curved Objects from Intensity Images / Model-Based Recognition Based on Range Images / 2D View-Based Representations of a 3D Scene / Viewing Space / Multi-View Representations and Aspect Graphs / Geons as a 2D View-based Structural Representation / Visualizing 3D Real-World Scenes Using Stored Collections of 2D Views / 3D Reconstruction from an Unorganized Set of 2D Vies - A Case Study / Summary / References 13. Mathematical Morphology Basic Morphological Concepts / Four Morphological Principles / Binary Dilation and Erosion / Hit or Miss Transformation / Opening and Closing / Gray-Scale Dilation and Erosion / Top Surface, Umbra, and Gray-Scale Dilation and Erosion / Umbra Homeomorphism Theorem, Properties of Erosion and Dilation, Opening and Closing / Top Hat Transformation / Skeletons and Object Marking / Homotopic Transformations / Skeleton, Maximal Ball / Thinning, Thickening, and Homotopic Skeleton / Quench Function, Ultimate Erosion / Ultimate Erosion and Distance Functions / Geodesic Transformations / Morphological Reconstruction / Granulometry / Morphological Segmentation and Watersheds / Particles Segmentation, Marking, and Watersheds / Binary Morphological Segmentation / Gray-Scale Segmentation, Watersheds / Summary / References 14. Image Data Compression Image Data Properties / Discrete Image Transforms in Image Data Compression / Predictive Compression methods / Vector Quantization / Hierarchical and Progressive Compression Methods / Comparison of Compression Methods / Other Techniques / Coding / JPEG and MPEG - Still Image Compression / JPEG - 2000 Compression / MPEG - Full Motion Video Compression / Summary / References 15. Texture Statistical Texture Description / Methods Based on Spatial Frequencies / Co-occurrence Matrices / Edge Frequency / Primitive Length (Run Length) / Laws Texture Energy Measures / Fractal Texture Description / Multiscale Texture Description - Wavelet Domain Approaches / other Statistical Methods of Texture Description / Syntactic Texture Description Methods / Shape Chain Grammars / Graph Grammars / Primitive Grouping in Hierarchical Textures / Hybrid Texture Description methods / Texture Recognition Method Applications / Summary / References 16. Motion Analysis Differential Motion analysis Methods / Optical Flow Computation / Global and Local Optical Flow Estimation / Combined Local - Global Optical Flow Estimation / Optical Flow in Motion Analysis / Analysis Based on Correspondence of Interest Points / Detection of Interest Points / Detection of Interest Points / Correspondence of Interest Points / Detection of Specific Motion Patterns / Video Tracking / Background Modeling / Kernel-Based Tracking / Object Path Analysis / Motion Models to Aid Tracking / Kalman Filters / Particle Filters / Summary / References

Customer Reviews

Most Helpful Customer Reviews

See All Customer Reviews