We propose a novel framework for perceptual grouping based on the idea of mixture models, called Bayesian hierarchical grouping (BHG). In BHG, we assume that the configuration of image elements is generated by a mixture of distinct objects, each of which generates image elements according to some generative assumptions. Grouping, in this framework, means estimating the number and the parameters...

Perceptual grouping is usually defined by principles that associate distinct elements by virtue of image properties such as proximity, similarity, and occurrence within common regions. What role does learning play in forming a perceptual group? This study provides evidence that learning of shape associations leads to perceptual grouping. Participants were repeatedly exposed to pairs of unique s...

This paper addresses the cell formation problem with alternative process plans and machine capacity constraints. The problem of Generalized Cell Formation consists in defining the preferential process and the preferential routing for each part optimizing the grouping of machines into independent manufacturing cells. The problem is reduced in two grouping problems: grouping operations (including...

in order to assess and identify genetic diversity and genetic relationships of the 64 kabuli chickpeas genotypes, an experimental design was carried out in a simple lattice design (8×8) in 2009-2010 cropping season on the research field of college of agriculture and natural resource of tehran university. the results of phenotypic correlation showed that grain yield per plant had significant and...

Image denoising by block matching and threedimensionaltransform filtering (BM3D) is a two steps state-ofthe-art algorithm that uses the redundancy of similar blocks innoisy image for removing noise. Similar blocks which can havesome overlap are found by a block matching method and groupedto make 3-D blocks for 3-D transform filtering. In this paper wepropose a new block grouping algorithm in th...