Image Segmentation Using Simple Markov Field Models.

Abstract

By modelling a picture as a two-state Markov field, MAP estimation techniques are used to develop suboptimal but computationally tractable binary segmentation algorithms. The algorithms are shown to perform well at low signal to noise ratios, and analytical procedures are developed for estimating the Markov field transition probabilities. In addition, extensions of this approach to the multi-spectral and multi-region cases are discussed. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1981
Accession Number
ADA112914

Entities

People

  • F. R. Hansen
  • H. Elliott

Organizations

  • Colorado State University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Colorado
  • Computer Vision
  • Dynamic Programming
  • Electrical Engineering
  • Engineering
  • Image Processing
  • Image Segmentation
  • Information Processing
  • Markov Chains
  • Pattern Recognition
  • Probability
  • Random Variables
  • Signal Processing
  • Stochastic Processes
  • Two Dimensional
  • Universities

Readers

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