Management of Uncertainty in Military Scene Analysis

Abstract

Research into modeling and managing uncertainty in military scene analysis is presented. A new method of logical inference was developed for the case where propositions are modeled by possibility distributions. This scheme was tested in a prototype fuzzy rule-based system for automatic target recognition. An information fusion technique based on the fuzzy integral was also developed. This was inserted into a numeric uncertainty propagation ATR prototype system. Fractal geometry was exploited for scene description and segmentation. Results concerning dimension calculation, texture description and segmentation, and surface orientation from fractal features is presented. Fast solutions to two problems in linear discriminant analysis are contained herein. Both techniques avoid the potentially disastrous errors from calculating large- cross product matrices. Finally, preliminary work on modifying confidence values for hypotheses based on external or scene derived context are presented. Keywords: Uncertainty; Fuzzy logic; Belief theory; Fuzzy integral; Rule-based automatic target recognition; Fractal geometry; Texture analysis; Linear discriminant analysis; Context.

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Document Details

Document Type
Technical Report
Publication Date
Jul 26, 1988
Accession Number
ADA219930

Entities

People

  • James M. Keller
  • Richard M. Crownover
  • Robert W. Mclaren

Organizations

  • University of Missouri

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Human Systems
  • Materials and Manufacturing Processes
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Computer Vision
  • Computers
  • Databases
  • Detection
  • Detectors
  • Discriminant Analysis
  • Fuzzy Logic
  • Fuzzy Sets
  • Geometry
  • Image Processing
  • Information Science
  • Recognition
  • Rule Based Systems
  • Target Recognition

Readers

  • Computer Vision.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference