Investigation of Feature Selection Criteria for Pattern Recognition Models Including the Fourier Transmission.

Abstract

Feature selection is of fundamental importance in pattern recognition. The investigation evaluates and compares 10 feature selection criteria. The two-dimensional, discrete Fourier transform is specified so that the low-pass spatial filter criterion can be included in the comparison. Feature space extraction and feature space evaluation processes are modeled and implemented. Two sets of data consisting of handprinted characters are used in a series of experiments that extract feature spaces corresponding to the various criteria and evaluate the feature spaces by a class separability measure and an error estimate. The results are tabulated for comparison and conclusions are drawn on the empirical and theoretic bases established. (Modified author abstract)

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1973
Accession Number
AD0760762

Entities

People

  • Edwin A. Olson

Organizations

  • Air Force Institute of Technology

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Discrete Fourier Transforms
  • Extraction
  • Feature Extraction
  • Feature Selection
  • Pattern Recognition
  • Personality
  • Recognition
  • Test And Evaluation
  • Two Dimensional

Readers

  • Approximation Theory.
  • Neural Network Machine Learning.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • Space