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...
—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...
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...
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...
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...