weightedPairsDistance: Distance between color clusters with user-specified...

In colordistance: Distance Metrics for Image Color Similarity

Description

Distance metric with optional user input for specifying how much the bin size similarity and color similarity should be weighted when pairing clusters from different color cluster sets.

Usage

weightedPairsDistance(
  T1,
  T2,
  ordering = FALSE,
  size.weight = 0.5,
  color.weight = 0.5
)

Arguments

T1	Dataframe (especially a dataframe as returned by extractClusters or getImageHist, but first three columns must be coordinates).
T2	Another dataframe like T1.
ordering	Logical. Should clusters by paired in order to minimize overall distance scores or evaluated in the order given?
size.weight	Weight of size similarity in determining overall score and ordering (if ordering=T).
color.weight	Weight of color similarity in determining overall score and ordering (if ordering=T). Color and size weights do not necessarily have to sum to 1.

Value

Similarity score based on size and color similarity of each pair of points in provided dataframes.

Note

Use with caution, since weights can easily swing distance scores more dramatically than might be expected. For example, if size.weight = 1 and color.weight = 0, two clusters of identical color but different sizes would not be compared.

Examples

cluster.list <- colordistance::getKMeansList(system.file("extdata",
"Heliconius/Heliconius_B", package="colordistance"), lower=rep(0.8, 3),
upper=rep(1, 3))
cluster.list <- colordistance::extractClusters(cluster.list, ordering=TRUE)
colordistance:::weightedPairsDistance(cluster.list[[1]], cluster.list[[2]],
size.weight=0.8, color.weight=0.2)

colordistance documentation built on March 21, 2021, 1:06 a.m.