Performance Modelling of Autonomous Electro-Optical Sensors

Abstract

The Performance Modeling of Autonomous Electro-Optical Sensors (PM) program is a basic research effort aimed at the fundamental analysis of image processing methodology. To this end, an investigation into the the use of LADAR imagery for target recognition was initiated. Preliminary research and methodology development occurred from November 1986 to May 1987. Research and implementation are continuing and this report details the investigation performed and results obtained during the period from May 15, 1987 through November 15, 1987. During the previous six months, the LADAR target recognition investigation has focused on the area of object segmentation. The issues that were addressed include: Surface segmentation via region growing, Robust planar surface estimation, background plane removal, Smoothing of the image prior to the estimation of derivatives, and, Crease edge detection. The introduction to Section 2.0 contains a general problem definition and a brief methodology overview. The various subsections describe those aspects of segmentation that were addressed in this reporting period. Specific techniques being investigated are detailed, along with any pertinent demonstrations that have been performed.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1987
Accession Number
ADA206471

Entities

People

  • Margaret A. Lepley
  • Rama Chellappa
  • William G. Hanley

Organizations

  • Hughes Aircraft Company

Tags

Communities of Interest

  • Air Platforms
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Change Detection
  • Computations
  • Computer Vision
  • Data Sets
  • Detection
  • Detectors
  • Electro-Optical Sensors
  • Geometry
  • Image Processing
  • Laser Radar
  • Optical Detectors
  • Physical Properties
  • Recognition
  • Target Recognition
  • Two Dimensional

Readers

  • Business Analytics
  • Image Processing and Computer Vision.
  • Technical Research and Report Writing.