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» Modeling Image Textures by Gibbs Random Fields
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ICIP
2003
IEEE
14 years 11 months ago
A probabilistic framework for image segmentation
A new probabilistic image segmentation model based on hypothesis testing and Gibbs Random Fields is introduced. First, a probabilistic difference measure derived from a set of hyp...
Slawo Wesolkowski, Paul W. Fieguth
PAMI
1998
103views more  PAMI 1998»
13 years 9 months ago
Synchronous Random Fields and Image Restoration
—We propose a general synchronous model of lattice random fields which could be used similarly to Gibbs distributions in a Bayesian framework for image analysis, leading to algor...
Laurent Younes
CVPR
2008
IEEE
14 years 11 months ago
Combining appearance models and Markov Random Fields for category level object segmentation
Object models based on bag-of-words representations can achieve state-of-the-art performance for image classification and object localization tasks. However, as they consider obje...
Diane Larlus, Frédéric Jurie

Book
5396views
15 years 8 months ago
Markov Random Field Modeling in Computer Vision
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
Stan Z. Li
AIPR
2004
IEEE
14 years 1 months ago
An Image Retrieval System Using Multispectral Random Field Models, Color, and Geometric Features
This paper describes a novel color texture-based image retrieval system for the query of an image database to find similar images to a target image. The retrieval process involves...
Orlando J. Hernandez, Alireza Khotanzad