morphology function

Morphology

Apply a morphology method. This is a very flexible function which can be used to apply any morphology method with custom parameters. See imagemagick website

for examples.

image_morphology(
  image,
  method = "convolve",
  kernel = "Gaussian",
  iterations = 1,
  opts = list()
)

image_convolve(
  image,
  kernel = "Gaussian",
  iterations = 1,
  scaling = NULL,
  bias = NULL
)

Arguments

• image: magick image object returned by image_read() or image_graph()

• method: a string with a valid method from morphology_types()

• kernel: either a square matrix or a string. The string can either be a parameterized kerneltype such as: "DoG:0,0,2" or "Diamond"

  or it can contain a custom matrix (see examples)

• iterations: number of iterations

• opts: a named list or character vector with custom attributes

• scaling: string with kernel scaling. The special flag "!" automatically scales to full dynamic range, for example: "50%!"

• bias: output bias string, for example "50%"

Examples

#example from IM website:
if(magick_config()$version > "6.8.8"){
pixel <- image_blank(1, 1, 'white') |> image_border('black', '5x5')

# See the effect of Dilate method
pixel |> image_scale('800%')
pixel |> image_morphology('Dilate', "Diamond") |> image_scale('800%')

# These produce the same output:
pixel |> image_morphology('Dilate', "Diamond", iter = 3) |> image_scale('800%')
pixel |> image_morphology('Dilate', "Diamond:3") |> image_scale('800%')

# Plus example
pixel |> image_morphology('Dilate', "Plus", iterations = 2) |> image_scale('800%')

# Rose examples
rose |> image_morphology('ErodeI', 'Octagon', iter = 3)
rose |> image_morphology('DilateI', 'Octagon', iter = 3)
rose |> image_morphology('OpenI', 'Octagon', iter = 3)
rose |> image_morphology('CloseI', 'Octagon', iter = 3)

# Edge detection
man <- demo_image('man.gif')
man |> image_morphology('EdgeIn', 'Octagon')
man |> image_morphology('EdgeOut', 'Octagon')
man |> image_morphology('Edge', 'Octagon')

# Octagonal Convex Hull
 man |>
   image_morphology('Close', 'Diamond') |>
   image_morphology('Thicken', 'ConvexHull', iterations = 1)

# Thinning down to a Skeleton
man |> image_morphology('Thinning', 'Skeleton', iterations = 1)

# Specify custom kernel matrix usingn a string:
img <- demo_image("test_mag.gif")
i <- image_convolve(img, kernel = '4x5:
       0 -1  0  0
      -1 +1 -1  0
      -1 +1 -1  0
      -1 +1 +1 -1
       0 -1 -1  0 ', bias = "50%")
}

See Also

Other image: _index_, analysis, animation, attributes(), color, composite, defines, device, edges, editing, effects(), fx, geometry, ocr, options(), painting, segmentation, transform(), video