Optical Linear Feature Detection Based on Model Pose.

Abstract

Low-level edge detection in optical imagery can be problematic in the ATR domain where highly complex scenes are the norm. Feature detection algorithms typically take a global approach, resulting in the discovery of many fragmented lines which are not directly related to stored model information. For this domain, we have taken a top-down approach which searches an optical image for the locally optimal features based on the current hypothesized object pose. The resulting linear features can then be matched against a CAD model.

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Document Details

Document Type
Technical Report
Publication Date
Dec 16, 1995
Accession Number
ADA308546

Entities

People

  • J. R. Beveridge
  • Mark R. Stevens

Organizations

  • Colorado State University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Artificial Intelligence
  • Change Detection
  • Classification
  • Colorado
  • Computer Science
  • Computer Vision
  • Detection
  • Detectors
  • Image Processing
  • Images
  • Military Research
  • Object Recognition
  • Optical Images
  • Recognition
  • Target Recognition

Fields of Study

  • Computer science

Readers

  • Computer Vision.