# Documentation

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# bwperim

Find perimeter of objects in binary image

## Syntax

``BW2 = bwperim(BW)``
``BW2 = bwperim(BW,conn)``

## Description

example

````BW2 = bwperim(BW)` returns a binary image that contains only the perimeter pixels of objects in the input image `BW`. A pixel is part of the perimeter if it is nonzero and it is connected to at least one zero-valued pixel. The default connectivity is 4 for two dimensions, 6 for three dimensions, and `conndef(ndims(BW), 'minimal')` for higher dimensions. If you do not specify a return value, `bwperim` displays the result in a figure window.```
````BW2 = bwperim(BW,conn)` where `conn` specifies the desired connectivity.```

## Examples

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

Calculate the perimeters of objects in the image.

`BW2 = bwperim(BW,8);`

Display the original image and the perimeters side-by-side.

`imshowpair(BW,BW2,'montage')`

## Input Arguments

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Input binary image, specified as a logical or numeric matrix that must be 2-D, real, and nonsparse.

Example: `BW = imread('circles.png'); BW2 = bwperim(BW);`

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

Connectivity, specified as one of the values in this table or a 3-by-3-by-...-by-3 array 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 around its center element.

Value

Meaning

Two-dimensional connectivities

4

4-connected neighborhood

8

8-connected neighborhood

Three-dimensional connectivities

6

6-connected neighborhood

18

18-connected neighborhood

26

26-connected neighborhood

Example: `BW2 = bwperim(BW,8);`

Data Types: `double` | `logical`

## Output Arguments

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Output image containing only perimeter pixels of objects, returned as a logical array.