Hypothesis Integration in Image Understanding Systems.

Abstract

The goal of this research is to develop a robust control strategy for constructing image understanding systems (IUS). This paper proposes a general framework based on the integration of 'related' hypotheses. Hypotheses are regarded as predictions of the occurrences of objects in the image. Related hypotheses are clustered together. A 'composite hypothesis' is computed for each cluster. The goal of the IUS is to verify the hypotheses. We constructed an image understanding system, SIGMA, based on this framework and demonstrated its performance on an aerial image of a suburban housing development. Keywords include: image understanding systems, SIGMA, and robust control strategy.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1985
Accession Number
ADA160129

Entities

People

  • L. S. Davis
  • T. Matsuyama
  • V. S. S. Hwang

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Artificial Intelligence
  • Artificial Intelligence Computing
  • Automation
  • Composite Materials
  • Computer Vision
  • Computers
  • Consistency
  • Construction
  • Databases
  • Demographic Cohorts
  • Expert Systems
  • Image Processing
  • Maryland
  • New York
  • Taxonomy
  • Universities

Readers

  • Computer Vision.
  • Statistical inference.
  • Systems Analysis and Design