# bwulterode

Ultimate erosion

## Syntax

``BW2 = bwulterode(BW)``
``BW2 = bwulterode(BW,method)``
``BW2 = bwulterode(___,conn)``

## Description

example

````BW2 = bwulterode(BW)` computes the ultimate erosion of the binary image `BW`. The ultimate erosion of `BW` consists of the regional maxima of the Euclidean distance transform of the complement of `BW`.```
````BW2 = bwulterode(BW,method)` specifies the distance transform method.```
````BW2 = bwulterode(___,conn)` specifies the pixel connectivity.```

## Examples

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Read a binary image into the workspace and display it.

```originalBW = imread('circles.png'); imshow(originalBW)``` Perform the ultimate erosion of the image and display it.

```ultimateErosion = bwulterode(originalBW); figure, imshow(ultimateErosion)``` ## Input Arguments

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Binary image, specified as a numeric or logical array of any dimension. For numeric input, any nonzero pixels are considered to be `1` (`true`).

Example: `BW = imread('circles.png')`;

Data Types: `single` | `double` | `int8` | `int16` | `int32` | `int64` | `uint8` | `uint16` | `uint32` | `uint64` | `logical`

Distance transform method, specified as one of the values in this table.

Method

Description

`'chessboard'`

In 2-D, the chessboard distance between (x1,y1) and (x2,y2) is

max(│x1x2│,│y1y2│).

`'cityblock'`

In 2-D, the cityblock distance between (x1,y1) and (x2,y2) is

x1x2│ + │y1y2

`'euclidean'`

In 2-D, the Euclidean distance between (x1,y1) and (x2,y2) is

`$\sqrt{{\left({x}_{1}-{x}_{2}\right)}^{2}+{\left({y}_{1}-{y}_{2}\right)}^{2}}.$`

`'quasi-euclidean'`

In 2-D, the quasi-Euclidean distance between (x1,y1) and (x2,y2) is

Pixel connectivity, specified as one of the values in this table. The default connectivity is `8` for 2-D images, and `26` for 3-D images.

Value

Meaning

Two-Dimensional Connectivities

4-connected

Pixels are connected if their edges touch. The neighborhood of a pixel are the adjacent pixels in the horizontal or vertical direction. 8-connected

Pixels are connected if their edges or corners touch. The neighborhood of a pixel are the adjacent pixels in the horizontal, vertical, or diagonal direction. Three-Dimensional Connectivities

6-connected

Pixels are connected if their faces touch. The neighborhood of a pixel are the adjacent pixels in:

• One of these directions: in, out, left, right, up, and down 18-connected

Pixels are connected if their faces or edges touch. The neighborhood of a pixel are the adjacent pixels in:

• One of these directions: in, out, left, right, up, and down

• A combination of two directions, such as right-down or in-up 26-connected

Pixels are connected if their faces, edges, or corners touch. The neighborhood of a pixel are the adjacent pixels in:

• One of these directions: in, out, left, right, up, and down

• A combination of two directions, such as right-down or in-up

• A combination of three directions, such as in-right-up or in-left-down For higher dimensions, `bwulterode` uses the default value `conndef(ndims(BW),'maximal')`.

Connectivity can also be defined in a more general way for any dimension by specifying a 3-by-3-by- ... -by-3 matrix of `0`s and `1`s. The `1`-valued elements define neighborhood locations relative to the center element of `conn`. Note that `conn` must be symmetric about its center element. See Specifying Custom Connectivities for more information.

Data Types: `double` | `logical`

## Output Arguments

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Eroded image, returned as a logical array of the same size as `BW`.

Data Types: `logical`