imgKDKMeans: Image clustering

In matiasb/biOps: Image processing and analysis

Description

This function performs an unsupervised classification through the k-means algorithm. This implementation uses kd-trees for nearest neighbor queries. It is useful for big values of k.

Usage

imgKDKMeans (imgdata, k, maxit=10)

Arguments

imgdata	The image
k	Number of clusters
maxit	Max number of iterations

Value

return an imagedata object, the result of the classification

See Also

imgKMeans imgEKMeans imgIsoData

Examples

	## Not run: 
		x <- readJpeg(system.file("samples", "violet.jpg", package="biOps"))
		y <- imgKDKMeans(x, 4)
	
## End(Not run)

matiasb/biOps documentation built on May 21, 2019, 12:55 p.m.