A novel technique for unsupervised texture segmentation

IEEE International Conference on Image Processing

Volumn 1, Issue , 2001, Pages 58-61

  Roula, M A ^a   Bouridane, A ^a   Amira, A ^a   Sage, P ^a   Milligan, P ^a  

^a QUEEN'S UNIVERSITY BELFAST   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; FEATURE EXTRACTION; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; PROBABILITY DENSITY FUNCTION; RANDOM PROCESSES;

EXPECTATION-MAXIMISATION ALGORITHM; UNSUPERVISED TEXTURE SEGMENTATION;

IMAGE SEGMENTATION;

EID: 0035172104     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

1. Random field models in image analysis
2. Unsupervised texture segmentation using Markov random field models
3. Multiple resolution segmentation of textured images
4. Bayesian pixel classification using spatially variant finite mixures and generalised EM algorithm
5. EM algorithm initialised by a tree structure scheme
6. Maximum likelihood from incomplete data via the EM algorithm
7. Probabilistic models of digital region maps based on Markov random fields with short and long-range interaction
8. Stochastic relaxation Gibbs distribution and Bayesian restoration of images
9. Modeling and segmentation of noisy and textured images using Gibbs random fields
10. Unsupervised segmentation of Markov random field modeled textured images using selectionist relaxation