Shape Analysis and Classification: Theory and Practice

Published:
December 20, 2000 by CRC Press - 680 Pages
Author(s):
Luciano da Fontoura Costa, University of S¿o Paulo, S¿o Carlos, Brazil; Roberto Marcond Cesar, Jr., University of S¿o Paulo, Brazil

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Hardback
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ISBN 9780849334931
Cat# 3493
 

Features

  • Serves as both an introduction to and a reference for computer-based analysis and recognition of shapes
  • Includes a comprehensive review of the basic mathematical concepts involved
  • Examines various techniques for shape characterization and analysis, including shape contour analysis and extraction of different shape measures for statistical classification
  • Explains several multiscale techniques, such as wavelets and multiscale skeletonization
  • Focuses on two-dimensional shapes but includes concepts and techniques that can be generalized for 3-D shapes
  • Identifies future trends and developments
  • Includes numerous illustrations and real-world examples

    • Summary

    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.

    Table of Contents

    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

    Editorial Reviews

    "The authors of this book have done an admirable job of discussing the diverse approaches utilized in this area…clearly written and is a valuable resource for scientists interested in visual shape analysis."
    -Journal of Mathematical Psychology

    "This book begins with the basic mathematical concepts and examines shape analysis, from image capture to pattern classification."
    -IEEE Signal Processing, November 2001

    "It is presented as a self-contained introductory textbook… Therefore it is the intention of the authors to make the concepts covered in the book accessible to a broad range of readers… The way in which the book is written clearly illustrates the authors' enthusiasm is, in my opinion, beneficial to any prospective reader… The presence of numerous examples and clearly explained algorithms are definitely helpful… a good acquisition for any researcher in the field of shape and image analysis as a general reference of the subject… Overall, I recommend this book. It is easy to read and well laid out with many examples, diagrams and figures."
    -Dr. Paul McDonnell, Department of Statistics, University of Leeds in British Machine Vision Association Newsletter

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