Bayesian texture segmentation of weed and crop images using reversible jump Markov chain Monte Carlo methods Article

Dryden, IL, Scarr, MR, Taylor, CC. (2003). Bayesian texture segmentation of weed and crop images using reversible jump Markov chain Monte Carlo methods . The Journal of the Royal Statistical Society, Series C (Applied Statistics), 52 31-50. 10.1111/1467-9876.00387

Industry Collaboration International Collaboration

cited authors

  • Dryden, IL; Scarr, MR; Taylor, CC

sustainable development goals

authors

publication date

  • January 1, 2003

published in

keywords

  • COMPUTATION
  • Gaussian Markov random field
  • Ising model
  • Markov chain Monte Carlo methods
  • Mathematics
  • Metropolis-Hastings algorithm
  • Physical Sciences
  • Potts model
  • RANDOM-FIELDS
  • SPATIAL INTERACTION
  • STATISTICAL-ANALYSIS
  • SYSTEMS
  • Science & Technology
  • Statistics & Probability
  • classification
  • image analysis
  • mixture models

Digital Object Identifier (DOI)

start page

  • 31

end page

  • 50

volume

  • 52