Optimal Design of Binary Phase-Only Filters Using Genetic Algorithms

Abstract

The genetic algorithm is a mathematical optimization technique, which has generally been applied to one-dimensional problems. In this work, the genetic algorithm was applied to a two-dimensional problem--the construction of binary phase-only spatial filters for optical pattern recognition. Spatial filters that are invariant to range and aspect changes are required for robust pattern recognition. Construction of invariant filters is an optimization problem where the correlation is the objective function for the genetic algorithm. Results are presented for correlation of a genetic algorithm- constructed filter with a multiple aspect angle target set. Filters using a hill-climber algorithm were also constructed and tested.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1993
Accession Number
ADA268737

Entities

People

  • Kalyanmoy Deb

Organizations

  • University of Illinois Urbana–Champaign

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Classification
  • Coding
  • Construction
  • Detectors
  • Engineering
  • Filters
  • Image Recognition
  • Matched Filters
  • Mathematical Programming
  • Optical Correlators
  • Optical Filters
  • Optimization
  • Pattern Recognition
  • Simulations
  • Two Dimensional
  • United States

Fields of Study

  • Physics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Vision.
  • Optical Physics and Photonics.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Biotechnology