Basic Pattern Recognition Principles
The following sections are included:
Data Pre-processing
Input Scaling and Normalisation
Feature Extraction
Feature Measurement Types
Nominal Feature Variables
Ordinal Feature Variables
Interval Feature Variables
Ratio Feature Variables
2-D Shape Feature Example
Classification
K-Nearest Neighbour Classifier
Distance Measures in a Feature Space
Statistical Classifiers
ANN Classifiers
Decision Criteria and Output Thresholds
Design Procedure for an ANN Classifier
A Simple Classification Example
Principle Component Analysis (PCA)
References