Segmentation of FLIR Images: A Comparative Study

Abstract

Several segmentation techniques were applied to a set of 51 FLIR (forward-Looking Infrared) images of four different types, and the results were compared to hand segmentations. There were substantial differences in performance, indicating that the choice of proper technique is very important. The segmentation techniques used were 'superslice,' 'pyramid spot detection', two versions of 'relaxation', pyramid linking', and 'superspike', One technique, 'superspike', outperformed all the others, detecting 88% of the targets and yielding only 1.6 false alarms per true target.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1982
Accession Number
ADP000140

Entities

People

  • Azriel Rosenfeld
  • Cheng-ye Wang
  • Leslie J. Kitchen
  • Ralph L. Hartley

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Applied Computer Science
  • Artificial Intelligence
  • Computer Science
  • Computer Vision
  • Databases
  • Detection
  • False Alarms
  • Histograms
  • Images
  • Infrared Images
  • Night Vision
  • Pilot Studies
  • Warning Systems

Readers

  • Computer Vision.