Shape Classification and Analysis: Theory and Practice, Second Edition, 2nd Edition (Hardback) book cover

Shape Classification and Analysis

Theory and Practice, Second Edition, 2nd Edition

By Luciano da Fona Costa, Roberto Marcond Cesar, Jr.

CRC Press

685 pages | 388 B/W Illus.

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Hardback: 9780849379291
pub: 2009-04-01
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Description

Because the properties of objects are largely determined by their geometric features, shape analysis and classification are essential to almost every applied scientific and technological area. A detailed understanding of the geometrical features of real-world entities (e.g., molecules, organs, materials and components) can provide important clues about their origin and function. When properly and carefully applied, shape analysis offers an exceedingly rich potential to yield useful applications in diverse areas ranging from material sciences to biology and neuroscience.

Get Access to the Authors’ Own Cutting-Edge Open-Source Software Projects—and Then Actually Contribute to Them Yourself!

The authors of Shape Analysis and Classification: Theory and Practice, Second Edition have improved the bestselling first edition by updating the tremendous progress in the field. This exceptionally accessible book presents the most advanced imaging techniques used for analyzing general biological shapes, such as those of cells, tissues, organs, and organisms. It implements numerous corrections and improvements—many of which were suggested by readers of the first edition—to optimize understanding and create what can truly be called an interactive learning experience.

New Material in This Second Edition Addresses

  • Graph and complex networks
  • Dimensionality reduction
  • Structural pattern recognition
  • Shape representation using graphs

Graphically reformulated, this edition updates equations, figures, and references, as well as slides that will be useful in related courses and general discussion. Like the popular first edition, this text is applicable to many fields and certain to become a favored addition to any library.

Visit http://www.vision.ime.usp.br/~cesar/shape/ for Useful Software, Databases, and Videos

Table of Contents

INTRODUCTION

INTRODUCTION TO SHAPE ANALYSIS

CASE STUDIES

COMPUTATIONAL SHAPE ANALYSIS

ADDITIONAL MATERIAL

ORGANIZATION OF THE BOOK

BASIC MATHEMATICAL CONCEPTS

BASIC CONCEPTS

LINEAR ALGEBRA

DIFFERENTIAL GEOMETRY

MULTIVARIATE CALCULUS

CONVOLUTION AND CORRELATION

PROBABILITY AND STATISTICS

FOURIER ANALYSIS

GRAPHS AND COMPLEX NETWORKS

SHAPE ACQUISITION AND 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

SHAPE REPRESENTATION

INTRODUCTION

PARAMETRIC CONTOURS

SETS OF CONTOUR POINTS

CURVE APPROXIMATIONS

DIGITAL STRAIGHT LINES

HOUGH TRANSFORMS

EXACT DILATIONS

DISTANCE TRANSFORMS

EXACT DISTANCE TRANSFORM THROUGH EXACT DILATIONS

VORONOI TESSELLATIONS

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

INTRODUCTION TO SHAPE CLASSIFICATION

SUPERVISED PATTERN CLASSIFICATION

UNSUPERVISED CLASSIFICATION AND CLUSTERING

A CASE STUDY: LEAVES CLASSIFICATION

EVALUATING CLASSIFICATION METHODS

STRUCTURAL SHAPE RECOGNITION

INTRODUCTION

SYNTACTIC PATTERN RECOGNITION

REGION DECOMPOSITION

GRAPH MODELS

SPATIAL RELATIONS

GRAPH MATCHING

CASE STUDY: INTERACTIVE IMAGE SEGMENTATION

COMPLEX NETWORKS FOR IMAGE AND SHAPE ANALYSIS

EPILOGUE

FUTURE TRENDS IN SHAPE ANALYSIS AND CLASSIFICATION

About the Authors/Editor

Luciano da Fontoura Costa is a full professor at the Instituto de Física de São Carlos, University of Sao Paulo, Brazil, and head of the Cybernetic Vision Research Group and the Multidisciplinary Computing Group. He holds BScs in Electronic Engineering and Computer Science, as well as a MSc in Applied Physics and a PhD in Electronic Engineering. Roberto M. Cesar Jr. holds a BSc in Computer Science, a M.Sc. in Electrical Engineering, and a Ph.D in Computational Physics. He is currently a lecturer at the University of Sao Paulo.

About the Series

Image Processing Series

Learn more…

Subject Categories

BISAC Subject Codes/Headings:
COM012000
COMPUTERS / Computer Graphics
TEC015000
TECHNOLOGY & ENGINEERING / Imaging Systems