watershed {EBImage} | R Documentation

## Watershed transformation and watershed based object detection

### Description

Watershed transformation and watershed based object detection.

### Usage

      ## S4 method for signature 'Image':
      watershed(x, tolerance=1, ext=1, ...)

### Arguments

`x` | An object of `Image` in the `Grayscale` mode.
`tolerance` | The minimum height of the object in the units of image intensity between its highest point (seed) and the point where it contacts another object (checked for every contact pixel). If the height is smaller than the tolerance, the object will be combined with one of its neighbors, which is the highest. It is assumed that the function is run on a distance map, therefore the default value is 1. If running the function on an original grayscale image with intensity range `[0,1]` one should modify this value, down to 0.1 or other which is image specific.
`ext` | Extension of the neighborhood for the detection of neighboring objects. Higher value smoothes out small objects.
`...` | Reserved.

### Details

The algorithm identifies and separates objects that stand out of the background (zero), in other words to use the water fill, the source image is flipped upside down and the resulting valleys (values with higher intensities) are filled in first until another object or background is met. The deepest valleys (pixels with highest intensity) become indexed first.

### Value

An object of `Image` in the `Grayscale` with separate objects indexed be positive integers starting from 1. To preview the results visually, use `display( normalize(result) )` or use it in combination with `paintObjects`.

### Author(s)

Oleg Sklyar, osklyar@ebi.ac.uk, 2007

### See Also

`Image, distmap, thresh, getFeatures, \code{matchObjects}`

### Examples

      ## load images
      f <- paste( system.file(package="EBImage"), "images/Gene1_G.tif", sep="/" )
      ii = readImage(f)
      ## normalize images
      ii = normalize(ii, separate=TRUE)
      ## segment
      mask = thresh(ii, 25, 25, 0.02)
      ## refine segmentation with morphology filters
      mk3 = morphKern(3)
      mk5 = morphKern(5)
      mask = dilate(erode(closing(mask, mk5), mk3), mk5)
      ## index objects with 'watershed'
      io = watershed( distmap(mask), 1.5, 1)
      if (interactive()) display(io)

[Package EBImage version 2.2.0 Index]