Shape Analysis and Classification
Theory and Practice
1st Edition
Published on 20. December 2000
Book
Hardback
680 pages
978-0-8493-3493-1 (ISBN)
Description
Advances in shape analysis impact a wide range of disciplines, from mathematics and engineering to medicine, archeology, and art. Anyone just entering the field, however, may find the few existing books on shape analysis too specific or advanced, and for students interested in the specific problem of shape recognition and characterization, traditional books on computer vision are too general.
Shape Analysis and Classification: Theory and Practice offers an integrated and conceptual introduction to this dynamic field and its myriad applications. Beginning with the basic mathematical concepts, it deals with shape analysis, from image capture to pattern classification, and presents many of the most advanced and powerful techniques used in practice. The authors explore the relevant aspects of both shape characterization and recognition, and give special attention to practical issues, such as guidelines for implementation, validation, and assessment.
Shape Analysis and Classification provides a rich resource for the computational characterization and classification of general shapes, from characters to biological entities. Both students and researchers can directly use its state-of-the-art concepts and techniques to solve their own problems involving the characterization and classification of visual shapes.
Shape Analysis and Classification: Theory and Practice offers an integrated and conceptual introduction to this dynamic field and its myriad applications. Beginning with the basic mathematical concepts, it deals with shape analysis, from image capture to pattern classification, and presents many of the most advanced and powerful techniques used in practice. The authors explore the relevant aspects of both shape characterization and recognition, and give special attention to practical issues, such as guidelines for implementation, validation, and assessment.
Shape Analysis and Classification provides a rich resource for the computational characterization and classification of general shapes, from characters to biological entities. Both students and researchers can directly use its state-of-the-art concepts and techniques to solve their own problems involving the characterization and classification of visual shapes.
More details
Series
Language
English
Place of publication
Bosa Roca
United States
Publishing group
Taylor & Francis Inc
Target group
College/higher education
Professional and scholarly
Engineers, biologists, physicians, physicists, computer scientists, neuroscientists, anatomists, archaeologists
Illustrations
13 s/w Photographien bzw. Rasterbilder, 27 s/w Tabellen
13 Halftones, black and white; 27 Tables, black and white
Dimensions
Height: 235 mm
Width: 156 mm
Weight
1270 gr
ISBN-13
978-0-8493-3493-1 (9780849334931)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions
Luciano da Fona Costa | Roberto Marcond Cesar, Jr.
Shape Classification and Analysis
Theory and Practice, Second Edition
Book
04/2009
2nd Edition
CRC Press
€216.65
Shipment within 15-20 days
Persons
Content
INTRODUCTION
Introduction to Shape Analysis
Case Studies
Computational Shape Analysis
Organization of The Book
BASIC MATHEMATICAL CONCEPTS
Basic Concepts
Linear Algebra
Differential Geometry
Multivariate Calculus
Convolution and Correlation
Probability and Statistics
Fourier Analysis
SHAPE ACQUISITION AND PRE-PROCESSING
Image Representation
Image Processing and Filtering
Image Segmentation: Edge Detection
Image Segmentation: Additional Algorithms
Binary Mathematical Morphology
Further Image Processing References
SHAPE CONCEPTS
Introduction to Two-Dimensional Shapes
Continuous Two-Dimensional Shapes
Planar Shape Transformations
Characterizing 2D Shapes in Terms of Features
Classifying 2D Shapes
Representing 2D Shapes
Shape Operations
Shape Metrics
Morphic Transformations
TWO-DIMENSIONAL SHAPE REPRESENTATION
Introduction
Parametric Contour
Sets of Contour Points
Curve Approximations
Digital Straight Lines
Hough Transforms
Exact Dilations
Distance Transforms
Exact Distance Transform through Exact Dilations
Voronoi Diagrams
Scale Space Skeletonization
Bounding Regions
SHAPE CHARACTERIZATION
Statistics for Shape Descriptors
Some General Descriptors
Fractal Geometry and Complexity Descriptors
Curvature
Fourier Descriptors
MULTISCALE SHAPE CHARACTERIZATION
Multiscale Transforms
Fourier-Based Multiscale Curvature
Wavelet-Based Multiscale Contour Analysis
Multiscale Energies
SHAPE RECOGNITION AND CLASSIFICATION
Introduction to Shape Classification
Supervised Pattern Classification
Unsupervised Classification and Clustering
A Case Study: Leaves Classification
Evaluating Classification Methods
EPILOGUE-FUTURE TRENDS IN SHAPE ANALYSIS
Introduction to Shape Analysis
Case Studies
Computational Shape Analysis
Organization of The Book
BASIC MATHEMATICAL CONCEPTS
Basic Concepts
Linear Algebra
Differential Geometry
Multivariate Calculus
Convolution and Correlation
Probability and Statistics
Fourier Analysis
SHAPE ACQUISITION AND PRE-PROCESSING
Image Representation
Image Processing and Filtering
Image Segmentation: Edge Detection
Image Segmentation: Additional Algorithms
Binary Mathematical Morphology
Further Image Processing References
SHAPE CONCEPTS
Introduction to Two-Dimensional Shapes
Continuous Two-Dimensional Shapes
Planar Shape Transformations
Characterizing 2D Shapes in Terms of Features
Classifying 2D Shapes
Representing 2D Shapes
Shape Operations
Shape Metrics
Morphic Transformations
TWO-DIMENSIONAL SHAPE REPRESENTATION
Introduction
Parametric Contour
Sets of Contour Points
Curve Approximations
Digital Straight Lines
Hough Transforms
Exact Dilations
Distance Transforms
Exact Distance Transform through Exact Dilations
Voronoi Diagrams
Scale Space Skeletonization
Bounding Regions
SHAPE CHARACTERIZATION
Statistics for Shape Descriptors
Some General Descriptors
Fractal Geometry and Complexity Descriptors
Curvature
Fourier Descriptors
MULTISCALE SHAPE CHARACTERIZATION
Multiscale Transforms
Fourier-Based Multiscale Curvature
Wavelet-Based Multiscale Contour Analysis
Multiscale Energies
SHAPE RECOGNITION AND CLASSIFICATION
Introduction to Shape Classification
Supervised Pattern Classification
Unsupervised Classification and Clustering
A Case Study: Leaves Classification
Evaluating Classification Methods
EPILOGUE-FUTURE TRENDS IN SHAPE ANALYSIS