Stable Feature Extraction in Aerial Reconnaissance Images

Abstract

The problem of extracting stable features in aerial reconnaissance images is addressed in this report. Fractal models of image features are proposed an concept of fractal error is introduced. Fractal error is a metric that quantifies the "closeness of fit" of the image feature to a fractal model. Using this metric one can discriminate between natural and man-made features in an image. Fractal error also presents a useful approach to extracting edges in images. Methods are given for computing and approximating fractal error using networks and genetic algorithms.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1998
Accession Number
ADA355591

Entities

People

  • Darrel L. Chenoweth

Organizations

  • University of Kentucky

Tags

Communities of Interest

  • Advanced Electronics
  • Air Platforms
  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Aerial Photography
  • Aerial Reconnaissance
  • Algorithms
  • Artificial Intelligence
  • Computational Science
  • Computer Languages
  • Computer Vision
  • Detectors
  • Electrical Engineering
  • Image Processing
  • Information Science
  • Information Theory
  • Machine Learning
  • Pattern Recognition
  • Random Variables
  • Target Recognition
  • Two Dimensional

Fields of Study

  • Computer science
  • Physics

Readers

  • Computational Modeling and Simulation
  • Computer Vision.

Technology Areas

  • AI & ML
  • Biotechnology