Some Experiments in Point Pattern Matching

Abstract

Given two pictures of a scene taken by different sensors or at different times, one way of matching the two pictures is to extract a set of distinctive local features from each, and then match the resulting point patterns. This paper investigates the sensitivity of point pattern matching to various types of noise and distortion, including omissions and additions, random walks, rotation and rescaling, as well as the use of different feature detection operators to extract the points. The effects of additional information (e.g., feature types) in overcoming the effects of noise is also studied.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1978
Accession Number
ADA074853

Entities

People

  • Alan Danker
  • Azriel Rosenfeld
  • Daryl J. Kahl

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Clustering
  • Computer Science
  • Computer Vision
  • Computers
  • Correlation Techniques
  • Detection
  • Detectors
  • Distortion
  • Feature Extraction
  • Image Processing
  • Information Processing
  • Mathematics
  • Night Vision
  • Random Walk
  • Rotation

Readers

  • Image Processing and Computer Vision.
  • Systems Analysis and Design
  • Vision Science/Vision Psychology/Cognitive Neuroscience.