ROC Analysis of IR Segmentation Techniques.

Abstract

Receiver Operating Characteristic (ROC) curves are used to compare the effectiveness of IR image processing techniques. Two non-parametric error estimation techniques (k-Nearest Neighbor and Parzen Window) are used to create estimates of the probability density functions for the data. These pdfs are used in the creation of the ROC curves for both resubstitution and leave-one-out estimates. These estimates generate the upper and lower bounds, respectively, on the ROC curves. The ROC curve analysis is performed on the outputs of various image processing techniques and the resulting ROC curves are used to compare the techniques. Of the image processing techniques used in this thesis, the close minus open (CMO) morphological filter operation produced the best results.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1994
Accession Number
ADA289252

Entities

People

  • Georgia K. Harrup

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Advanced Electronics
  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Cancer
  • Classification
  • Computer Vision
  • Data Science
  • Electrical Engineering
  • Feature Extraction
  • Image Processing
  • Information Processing
  • Information Science
  • Probability
  • Probability Density Functions
  • Recognition
  • Signal Processing
  • Standards
  • Target Recognition
  • Two Dimensional

Readers

  • Computer Vision.
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference