NEW!

SHAPE ANALYSIS AND CLASSIFICATION: THEORY AND PRACTICE


by Luciano da Fontoura Costa

and Roberto M. Cesar Junior

CRC Press


Chapter 8

Shape Classification

8.1 INTRODUCTION TO SHAPE CLASSIFICATION

  • 8.1.1 The Importance of Classification
  • 8.1.2 Some Basic Concepts in Classification
  • 8.1.3 A Simple Case Study in Classification
  • 8.1.4 Some Additional Concepts in Classification
  • 8.1.5 Feature Extraction
  • 8.1.6 Feature Normalization

8.2 SUPERVISED PATTERN CLASSIFICATION

  • 8.2.1 Bayes Decision Theory Principles
  • 8.2.2 Bayesian Classification Involving Multiple Classes and Dimensions
  • 8.2.3 Bayesian Classification of Leaves
  • 8.2.4 Nearest Neighbours

8.3 UNSUPERVISED CLASSIFICATION AND CLUSTERING

  • 8.3.1 Basic Concepts and Issues
  • 8.3.2 Scatter Matrices and Dispersion Measures
  • 8.3.3 Partitional Clustering
  • 8.3.4 Hierarchical Clustering

8.4 A CASE STUDY: LEAVES CLASSIFICATION

  • 8.4.1 Choice of Method
  • 8.4.2 Choice of Metric
  • 8.4.3 Choice of Features
  • 8.4.4 Effects of Unit Variance Normalization and Principal Component Analysis
  • 8.4.5 Validation Considering the Cophenetic Correlation Coefficient

8.5 EVALUATING CLASSIFICATION METHODS


General Information about the Book

http://www.ime.usp.br/~cesar/shape_crc


This page is maintained by Roberto M. Cesar Junior, cesar@ime.usp.br and by

Luciano da Fontoura Costa, luciano@if.sc.usp.br