patLanW: Extracts color pattern from landmark transformed image using...

In StevenVB12/patternize: Quantification of Color Pattern Variation

Extracts color pattern from landmark transformed image using watershed segmentation. This function works interactively by allowing to pick a starting pixel within each pattern element from which the watershed will extract the pattern. This function works best for patterns with sharp boundaries.

Description

Extracts color pattern from landmark transformed image using watershed segmentation. This function works interactively by allowing to pick a starting pixel within each pattern element from which the watershed will extract the pattern. This function works best for patterns with sharp boundaries.

Usage

patLanW(
  sampleList,
  landList,
  IDlist = NULL,
  adjustCoords = FALSE,
  transformRef = "meanshape",
  resampleFactor = NULL,
  transformType = "tps",
  maskOutline = NULL,
  cartoonID = NULL,
  correct = FALSE,
  blur = TRUE,
  sigma = 3,
  bucketfill = TRUE,
  cleanP = NULL,
  splitC = NULL,
  plotTransformed = FALSE,
  plotCorrect = FALSE,
  plotEdges = FALSE,
  plotPriority = FALSE,
  plotWS = FALSE,
  plotBF = FALSE,
  plotFinal = FALSE
)

Arguments

sampleList	List of RasterStack objects.
landList	Landmark list as returned by makeList.
IDlist	List of sample IDs should be specified when masking outline and transformRef is 'meanshape'.
adjustCoords	Adjust landmark coordinates in case they are reversed compared to pixel coordinates (default = FALSE).
transformRef	ID or landmark matrix of reference sample for shape to which color patterns will be transformed to. Can be 'meanshape' for transforming to mean shape of Procrustes analysis.
resampleFactor	Integer for downsampling image used by redRes.
transformType	Transformation type as used by computeTransform (default ='tps').
maskOutline	When outline is specified, everything outside of the outline will be masked for the color extraction (default = NULL).
cartoonID	ID of the sample for which the cartoon was drawn and will be used for masking (should be set when transformRef = 'meanShape').
correct	Correct image illumination using a linear model (default = FALSE).
blur	Blur image for priority map extraction (default = TRUE).
sigma	Size of sigma for Gaussian blurring (default = 5).
bucketfill	Use a bucket fill on the background to fill holes (default = TRUE).
cleanP	Integer to remove spurious areas with width smaller than cleanP (default = NULL).
splitC	Integer to split selected patterns into connected components and remove ones with areas smaller than splitC (default = NULL).
plotTransformed	Plot transformed image (default = FALSE).
plotCorrect	Plot corrected image, corrected for illumination using a linear model (default = FALSE).
plotEdges	Plot image gradient (default = FALSE).
plotPriority	Plot priority map (default = FALSE).
plotWS	Plot watershed result (default = FALSE).
plotBF	Plot bucketfill (default = FALSE).
plotFinal	Plot extracted patterns (default = FALSE).

Value

List of raster objects.

Examples

## Not run: 
IDlist <- c('BC0077','BC0071','BC0050','BC0049','BC0004')
prepath <- system.file("extdata",  package = 'patternize')
extension <- '_landmarks_LFW.txt'

landmarkList <- makeList(IDlist, 'landmark', prepath, extension)

extension <- '.jpg'
imageList <- makeList(IDlist, 'image', prepath, extension)

outline_BC0077 <- read.table(paste(system.file("extdata",  package = 'patternize'),
'/BC0077_outline.txt', sep=''), header = FALSE)

rasterList_W <- patLanW(imageList, landmarkList, IDlist, transformRef = 'meanshape',
adjustCoords = TRUE, plotTransformed = FALSE, correct = TRUE, plotCorrect = FALSE, blur = FALSE,
sigma = 2, bucketfill = FALSE, cleanP = 0, splitC = 10, plotPriority = TRUE, plotWS = TRUE,
plotBF = TRUE, plotFinal = TRUE, maskOutline = outline_BC0077, cartoonID = 'BC0077')

## End(Not run)

StevenVB12/patternize documentation built on Nov. 2, 2023, 8:01 p.m.