bwmorph (Image Processing Toolbox User's Guide)

Image Processing Toolbox User's Guide

Perform morphological operations on binary images

Syntax

BW2 = bwmorph(BW,operation)
BW2 = bwmorph(BW,operation,n)

Description

BW2 = bwmorph(BW,operation) applies a specific morphological operation to the binary image BW.

BW2 = bwmorph(BW,operation,n) applies the operation n times. n can be Inf, in which case the operation is repeated until the image no longer changes.

operation is a string that can have one of the values listed below.

Operation
Description

'bothat'
Performs the morphological "bottom hat" operation, which is closing (dilation followed by erosion) and subtracts the original image.

'bridge'

Bridges unconnected pixels, that is, sets 0-valued pixels to 1 if they have two nonzero neighbors that are not connected. For example:

1 0 0 1 1 0 1 0 1 becomes 1 1 1 0 0 1 0 1 1

'clean'

Removes isolated pixels (individual 1's that are surrounded by 0's), such as the center pixel in this pattern.

0 0 0 0 1 0 0 0 0

'close'
Performs morphological closing (dilation followed by erosion).

'diag'

Uses diagonal fill to eliminate 8-connectivity of the background. For example:

0 1 0 0 1 0 1 0 0 becomes 1 1 0 0 0 0 0 0 0

'dilate'
Performs dilation using the structuring element ones(3).

'erode'
Performs erosion using the structuring element ones(3)

'fill'

Fills isolated interior pixels (individual 0's that are surrounded by 1's), such as the center pixel in this pattern.

1 1 1 1 0 1 1 1 1

'hbreak'

Removes H-connected pixels. For example:

1 1 1 1 1 1 0 1 0 becomes 0 0 0 1 1 1 1 1 1

'majority'
Sets a pixel to 1 if five or more pixels in its 3-by-3 neighborhood are 1's; otherwise, it sets the pixel to 0.

'open'
Peforms morphological opening (erosion followed by dilation).

'remove'
Removes interior pixels. This option sets a pixel to 0 if all its 4-connected neighbors are 1, thus leaving only the boundary pixels on.

'shrink'
With n = Inf, shrinks objects to points. It removes pixels so that objects without holes shrink to a point, and objects with holes shrink to a connected ring halfway between each hole and the outer boundary. This option preserves the Euler number

'skel'
With n = Inf, removes pixels on the boundaries of objects but does not allow objects to break apart. The pixels remaining make up the image skeleton. This option preserves the Euler number.

'spur'

Removes spur pixels. For example:

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 becomes 0 0 0 0 0 1 0 0 0 1 0 0 1 1 0 0 1 1 0 0

'thicken'
With n = Inf, thickens objects by adding pixels to the exterior of objects until doing so would result in previously unconnected objects being 8-connected. This option preserves the Euler number.

'thin'
With n = Inf, thins objects to lines. It removes pixels so that an object without holes shrinks to a minimally connected stroke, and an object with holes shrinks to a connected ring halfway between each hole and the outer boundary. This option preserves the Euler number

'tophat'
Performs morphological "top hat" operation, returning the image minus the morphological opening of the image.

Operation	Description
`'bothat'`	Performs the morphological "bottom hat" operation, which is closing (dilation followed by erosion) and subtracts the original image.
`'bridge'`	Bridges unconnected pixels, that is, sets 0-valued pixels to `1` if they have two nonzero neighbors that are not connected. For example: 1 0 0 1 1 0 1 0 1 becomes 1 1 1 0 0 1 0 1 1
`'clean'`	Removes isolated pixels (individual 1's that are surrounded by 0's), such as the center pixel in this pattern. 0 0 0 0 1 0 0 0 0
`'close'`	Performs morphological closing (dilation followed by erosion).
`'diag'`	Uses diagonal fill to eliminate 8-connectivity of the background. For example: 0 1 0 0 1 0 1 0 0 becomes 1 1 0 0 0 0 0 0 0
`'dilate'`	Performs dilation using the structuring element `ones(3)`.
`'erode'`	Performs erosion using the structuring element `ones(3)`
`'fill'`	Fills isolated interior pixels (individual 0's that are surrounded by 1's), such as the center pixel in this pattern. 1 1 1 1 0 1 1 1 1
`'hbreak'`	Removes H-connected pixels. For example: 1 1 1 1 1 1 0 1 0 becomes 0 0 0 1 1 1 1 1 1
`'majority'`	Sets a pixel to `1` if five or more pixels in its 3-by-3 neighborhood are 1's; otherwise, it sets the pixel to `0`.
`'open'`	Peforms morphological opening (erosion followed by dilation).
`'remove'`	Removes interior pixels. This option sets a pixel to `0` if all its 4-connected neighbors are `1`, thus leaving only the boundary pixels `on`.
`'shrink'`	With `n` `=` `Inf`, shrinks objects to points. It removes pixels so that objects without holes shrink to a point, and objects with holes shrink to a connected ring halfway between each hole and the outer boundary. This option preserves the Euler number
`'skel'`	With `n` `=` `Inf`, removes pixels on the boundaries of objects but does not allow objects to break apart. The pixels remaining make up the image skeleton. This option preserves the Euler number.
`'spur'`	Removes spur pixels. For example: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 becomes 0 0 0 0 0 1 0 0 0 1 0 0 1 1 0 0 1 1 0 0
`'thicken'`	With `n` `=` `Inf`, thickens objects by adding pixels to the exterior of objects until doing so would result in previously unconnected objects being 8-connected. This option preserves the Euler number.
`'thin'`	With `n` `=` `Inf`, thins objects to lines. It removes pixels so that an object without holes shrinks to a minimally connected stroke, and an object with holes shrinks to a connected ring halfway between each hole and the outer boundary. This option preserves the Euler number
`'tophat'`	Performs morphological "top hat" operation, returning the image minus the morphological opening of the image.

Class Support

The input image BW can be numeric or logical. It must be 2-D, real and nonsparse. The output image BW2 is of class logical.

Example

BW = imread('circles.png');
imshow(BW);


BW2 = bwmorph(BW,'remove');
figure, imshow(BW2)


BW3 = bwmorph(BW,'skel',Inf);
figure, imshow(BW3)

See Also

bweuler, bwperim, imdilate, imerode

References

[1] Haralick, Robert M., and Linda G. Shapiro, Computer and Robot Vision, Volume I, Addison-Wesley, 1992.

[2] Pratt, William K., Digital Image Processing, John Wiley & Sons, Inc., 1991.

[3] Lam, L., Seong-Whan Lee, and Ching Y. Suen, "Thinning Methodologies-A Comprehensive Survey," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol 14, No. 9, September 1992, page 879, bottom of first column through top of second column.

bwlabeln bwpack