Morphological Operations

morph applies various morphological operations (see Note) to an Image object.

Usage

morph(
  image,
  operation,
  kernel = NULL,
  k_shape = "rectangle",
  k_height = 5,
  k_width = 5,
  iterations = 1,
  target = "new",
  in_place = NULL
)

Arguments

image

An Image object.

operation

A string corresponding to the name of a morphological operation to apply to the image (see Note).

kernel

A binary matrix.

k_shape

A string corresponding to the shape of the kernel for the morphological operation (see Note; default: "rectangle"). Ignored if a custom kernel is provided.

k_height

The half-height in pixels of the kernel. Ignored if a custom kernel is provided.

k_width

The half-width in pixels of the kernel. Ignored if a custom kernel is provided.

iterations

The number of times the morphological operations should be applied.

target

The location where the results should be stored. It can take 3 values:

"new":a new Image object is created and the results are stored inside (the default).
"self":the results are stored back into image (faster but destructive).
An Image object:the results are stored in another existing Image object. This is fast and will not replace the content of image but will replace that of target. Note that if target does not have the same dimensions, number of channels, and bit depth as image, an error will be thrown.

in_place

Deprecated. Use target instead.

Value

If target="new", the function returns an Image

object. If target="self", the function returns nothing and modifies

image in place. If target is an Image object, the function returns nothing and modifies that Image object in place.

Note

There are 8 types of morphological operations that can be achieved with this function:

"erode":for each point, returns the minimum of the points in its neighborhood, with that neighborhood defined by the kernel.
"dilate":for each point, returns the maximum of the points in its neighborhood, with that neighborhood defined by the kernel.
"open":erosion followed by dilation.
"close":dilation followed by erosion.
"gradient":difference between the dilation and the erosion of an image.
"tophat":difference between an input image and its opening.
"blackhat":difference between the closing and its input image.
"hitmiss":(1) erodes the image with kernel > 0; (2) erodes the complement of the image with kernel < 0; (3) returns the intersection (AND) of step 1 and step 2. The hit-or-miss transform is the basis of more advanced morphological operations such as thinning or pruning.

There are 3 types of predetermined kernel shapes that can be used with this function when a custom kernel is not provided:

"rectangle" (the default):
"cross"
"ellipse"

Author

Simon Garnier, garnier@njit.edu

Examples