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This study presents a region-based algorithm for segmenting colour texture image, which uses Voronoi tessellation for partitioning the domain of the image and Markov random field (MRF) for modelling colour texture. In detail, (i) an image domain is divided into polygons (or sub-regions) by Voronoi tessellation; (ii) two MRF models, improved Potts model and multivariate Gaussian MRF model, are used...
There has been significant interest in the use of fully connected graphical models and deep-structured graphical models for the purpose of structured inference. However, fully connected and deep-structured graphical models have been largely explored independently, leaving the unification of these two concepts ripe for exploration. A fundamental challenge with unifying these two types of models is...
Boundary finding is one of the most important aspects in medical image processing. Wavelet edge detector becomes popular in recent years but is known to degrade in noisy situations. This study aimed to develop an advance precision image segmentation algorithm to enhance the blurred edges clearly for medical target definition. A new method of combining wavelet analysis with Markov random field (RBF)...
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