Clustering of Collinear Line Segments

Abstract

A number of methods are presented for finding clusters in collinear collections of line segments. The methods are of two kinds--merging methods and splitting methods. Both make use of an evaluation function, and several alternative functions are illustrated. The methods are evaluated using randomly generated clusters on backgrounds containing varying amounts of noise.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1980
Accession Number
ADA109557

Entities

People

  • Ann Scher
  • Azriel Rosenfeld
  • Michael Shneier

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Clustering
  • Computer Vision
  • Data Sets
  • Detection
  • Detectors
  • Image Processing
  • Night Vision
  • Pattern Recognition
  • Psychology
  • Recognition
  • Sequences
  • Splitting
  • Test And Evaluation
  • Visual Perception
  • Waveforms

Readers

  • Regression Analysis.