Morphological Operations (Image Processing Toolbox)

Image Processing Toolbox

Dilation- and Erosion-Based Functions

This section describes two common image processing operations that are based on dilation and erosion:

This table lists other functions in the toolbox that perform common morphological operations that are based on dilation and erosion. For more information about these functions, see their reference pages.

Table 9-3: Dilation- and Erosion-Based Functions
Function
Morphological Definition

bwhitmiss
Logical AND of an image, eroded with one structuring element, and the image's complement, eroded with a second structuring element.

imbothat
Subtracts the original image from a morphologically closed version of the image. Can be used to find intensity troughs in an image.

imclose
Dilates an image, and then erodes the dilated image using the same structuring element for both operations.

imopen
Erodes an image and then dilates the eroded image using the same structuring element for both operations.

imtophat
Subtracts a morphologically opened image from the original image. Can be used to enhance contrast in an image.

**Table 9-3: Dilation- and Erosion-Based Functions**
Function	Morphological Definition
`bwhitmiss`	Logical `AND` of an image, eroded with one structuring element, and the image's complement, eroded with a second structuring element.
`imbothat`	Subtracts the original image from a morphologically closed version of the image. Can be used to find intensity troughs in an image.
`imclose`	Dilates an image, and then erodes the dilated image using the same structuring element for both operations.
`imopen`	Erodes an image and then dilates the eroded image using the same structuring element for both operations.
`imtophat`	Subtracts a morphologically opened image from the original image. Can be used to enhance contrast in an image.

Skeletonization

To reduce all objects in an image to lines, without changing the essential structure of the image, use the bwmorph function. This process is known as skeletonization.

BW1 = imread('circbw.tif'); 
BW2 = bwmorph(BW1,'skel',Inf);
imshow(BW1)
figure, imshow(BW2)

Figure 9-5: Circbw.tif Before and After Skeletonization

Perimeter Determination

The bwperim function determines the perimeter pixels of the objects in a binary image. A pixel is considered a perimeter pixel if it satisfies both of these criteria:

The pixel is on.
One (or more) of the pixels in its neighborhood is off.

For example, this code finds the perimeter pixels in a binary image of a circuit board.

BW1 = imread('circbw.tif'); 
BW2 = bwperim(BW1);
imshow(BW1)
figure, imshow(BW2)

Figure 9-6: Circbw.tif Before and After Perimeter Determination

Combining Dilation and Erosion Morphological Reconstruction