Watershed transformation and watershed based object detection
Watershed transformation and watershed based object detection.
watershed(x, tolerance=1, ext=1)
x |
An |
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. Tolerance should be chosen
according to the range of |
ext |
Radius of the neighborhood in pixels for the detection of neighboring objects. Higher value smoothes out small objects. |
The algorithm identifies and separates objects that stand out of the background (zero). It inverts the image and uses water to fill the resulting valleys (pixels with high intensity in the source image) until another object or background is met. The deepest valleys become indexed first, starting from 1.
The function bwlabel is a simpler, faster alternative to
segment connected objects from binary images.
An Grayscale Image object or an array, containing the
labelled version of x.
Oleg Sklyar, osklyar@ebi.ac.uk, 2007
x = readImage(system.file('images', 'shapes.png', package='EBImage'))
x = x[110:512,1:130]
display(x, title='Binary')
y = distmap(x)
display(normalize(y), title='Distance map')
w = watershed(y)
display(normalize(w), title='Watershed')Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.