An Experiment on Target Tracking via Image Segmentation.

Abstract

A target tracking and detection experiment is reported that uses the Fisher's linear discriminant for pixel classification to segment simulated static and dynamic scenes. The results clearly demonstrate that the segmentation method performs better than other work on the same static scene. Detection performance versus the learning sample sizes for dynamic scenes is empirically determined. It indicates that a small target can still be detected if a sufficiently large learning sample size is available. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 11, 1982
Accession Number
ADA109618

Entities

People

  • Chia‐Hung Chen
  • Wen-hsing Yang

Organizations

  • University of Massachusetts Dartmouth

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Computer Vision
  • Detection
  • Electrical Engineering
  • Engineering
  • Gaussian Distributions
  • Image Segmentation
  • Images
  • Infrared Images
  • Learning
  • Military Research
  • Probability
  • Statistics
  • Target Detection
  • Target Tracking
  • Targets

Fields of Study

  • Computer science

Readers

  • Image Processing and Computer Vision.
  • Neural Network Machine Learning.