Image Recognition Using Generalized Correlation

Abstract

This paper investigates the use of generalized cross-correlation in pattern matching when the objects may be of one or two dimensions. Generalized correlation can be used to determine the amount of dilatation and rotation between a given template and an object, in addition to determining the relative translation. Two techniques are discussed which break this four-dimensional correlation into two two-dimensional correlations making the problem computationally feasible. The techniques were developed for a specific class of images, however they can be applied to a more general class.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1977
Accession Number
ADA051755

Entities

People

  • Lee E. Mcdonald

Organizations

  • University of Utah

Tags

Communities of Interest

  • Air Platforms
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Cartesian Coordinates
  • Computational Science
  • Computations
  • Coordinate Systems
  • Correlation Techniques
  • Cross Correlation
  • Digital Computers
  • Grids
  • Identification Systems
  • Image Processing
  • Image Recognition
  • Interpolation
  • Pattern Recognition
  • Sampling
  • Signal Processing
  • Two Dimensional

Readers

  • Computer Vision.

Technology Areas

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