Moment Methods for the Identification of Three Dimensional Objects from Optical Images

Abstract

The approach presented here makes use of the theory of two- dimensional moment invariants for planar geometric figures developed by Ming-kue Hu. Complete systems of moment invariants under translation, similitude and orthogonal transformations are derived. By carefully utilizing these properties, a sample set is constructed in which each sample is represented by a vector which characterizes the image for a certain orientation of some object from the given group. A pattern recognition technique is then described in which a parametric representation of the input signal is employed. The decision process using typical samples partitions the space into regions that envelop the chosen samples of a class. A simulation program based on the above outline is successfully developed which not only identifies objects, but also determines their orientation and position in space.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1971
Accession Number
AD0734781

Entities

People

  • Sahibsingh A. Dudani

Organizations

  • Ohio State University

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Air Force
  • Center Of Gravity
  • Computer Programs
  • Computers
  • Coordinate Systems
  • Electrical Engineering
  • Engineering
  • Euler Angles
  • Focal Planes
  • Information Science
  • Machine Learning
  • Optical Images
  • Pattern Recognition
  • Plastic Explosives
  • Simulations
  • Software In The Loop
  • Translations

Readers

  • Calculus or Mathematical Analysis
  • Computer Vision.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Space
  • Space - Space Objects
  • Space - Spacecraft Maneuvers