Feature Extraction and Recognition of Two-Dimensional Data by the Method of Moments

Abstract

A pattern recognition system applicable to two dimensional data is presented, and training algorithms for generating pattern classifiers are surveyed. The method of moments is used by the system as a feature extractor. The Mahalanobis distance measure is presented as a criterion for the selection of moment pairs to be used as descriptors. Experiments conducted using simulated high resolution radar images demonstrate the effectiveness of the system using unstructured data. Classification results for the system are compared to those of human interpreters.

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Document Details

Document Type
Technical Report
Publication Date
Jan 15, 1977
Accession Number
ADA037445

Entities

People

  • J. M. Harris
  • R. C. Gonzalez

Organizations

  • University of Tennessee

Tags

Communities of Interest

  • Air Platforms
  • Biomedical
  • Ground and Sea Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Artificial Intelligence
  • Character Recognition
  • Classification
  • Data Processing
  • Electrical Engineering
  • Feature Extraction
  • Information Processing
  • Information Science
  • Machine Learning
  • Method Of Moments
  • Pattern Recognition
  • Radar Images
  • Recognition
  • Transport Aircraft
  • Two Dimensional

Readers

  • Image Processing and Computer Vision.
  • Regression Analysis.
  • Speech Processing/Speech Recognition.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks