postdataseg: Data segmentation

In dpmixsim: Dirichlet Process Mixture Model Simulation for Clustering and Image Segmentation

Description

postdataseg performs data segmentation based on labelled cluster estimates.

Usage

postdataseg(x, z, ngrid, dbg=FALSE)

Arguments

x	full-sized scaled image data prepared by premask
z	cluster labels produced by postdpmixciz
ngrid	dimension of the grid used in estimation
dbg	logical variable to show debugging output (default = FALSE)

Details

Once the distributions of the indicator variables z_i are calculated we can separate the components of the mixture. Individual components are selected according to the most probable z_i value in a given region of the distributional space, leading to a partition of this space into regions. Intensity threshold values are associated with the partition of the distributional space to drive the image segmentation. In brief, the partition of the distributional space induced by the z values is used to segment the data space. From a computational point of view, the use of these two separate spaces enables us to optimize the MCMC implementation.

Value

cx	vector of image cluster values

Author(s)

A. Ferreira da Silva, Universidade Nova de Lisboa, Faculdade de Ciencias e Tecnologia,
[e-mail].

See Also

dpmixsim, readsliceimg, premask, postdpmixciz

Examples

## Not run: 
## see Example 2 in dpmixsim.

## End(Not run)

dpmixsim documentation built on May 1, 2019, 7:29 p.m.