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

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

#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%")
}