# bwconncomp

Find and count connected components in binary image

## Syntax

``CC = bwconncomp(BW)``
``CC = bwconncomp(BW,conn)``

## Description

example

````CC = bwconncomp(BW)` finds and counts the connected components `CC` in the binary image `BW`. The `CC` output structure contains the total number of connected components, such as regions of interest (ROIs), in the image and the pixel indices assigned to each component. `bwconncomp` uses a default connectivity of 8 for two dimensions and 26 for three dimensions.```

example

````CC = bwconncomp(BW,conn)` specifies the desired connectivity `conn` for the connected components.```

## Examples

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Create a small sample 3-D array.

```BW = cat(3, [1 1 0; 0 0 0; 1 0 0],... [0 1 0; 0 0 0; 0 1 0],... [0 1 1; 0 0 0; 0 0 1]);```

Find the connected components in the array.

`CC = bwconncomp(BW)`
```CC = struct with fields: Connectivity: 26 ImageSize: [3 3 3] NumObjects: 2 PixelIdxList: {[5x1 double] [3x1 double]} ```

Calculate centroids of the objects in the array.

`S = regionprops(CC,'Centroid')`
```S=2×1 struct array with fields: Centroid ```

Read image into the workspace and display it.

```BW = imread('text.png'); imshow(BW)```

Find the number of connected components in the image.

`CC = bwconncomp(BW)`
```CC = struct with fields: Connectivity: 8 ImageSize: [256 256] NumObjects: 88 PixelIdxList: {1x88 cell} ```

Determine which is the largest component in the image and erase it (set all the pixels to 0).

```numPixels = cellfun(@numel,CC.PixelIdxList); [biggest,idx] = max(numPixels); BW(CC.PixelIdxList{idx}) = 0;```

Display the image, noting that the largest component happens to be the two consecutive f's in the word different.

```figure imshow(BW)```

## 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`).

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

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`

Pixels are connected if their edges touch. Two adjoining pixels are part of the same object if they are both on and are connected along the horizontal or vertical direction.

Current pixel is shown in gray.

`8`

Pixels are connected if their edges or corners touch. Two adjoining pixels are part of the same object if they are both on and are connected along the horizontal, vertical, or diagonal direction.

Current pixel is shown in gray.

Three-Dimensional Connectivities

`6`

Pixels are connected if their faces touch. Two adjoining pixels are part of the same object if they are both on and are connected in:

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

Current pixel is center of cube.

`18`

Pixels are connected if their faces or edges touch. Two adjoining pixels are part of the same object if they are both on and are connected in:

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

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

Current pixel is center of cube.

`26`

Pixels are connected if their faces, edges, or corners touch. Two adjoining pixels are part of the same object if they are both on and are connected 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

Current pixel is center of cube.

For higher dimensions, `bwconncomp` 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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Connected components, returned as a structure with four fields.

FieldDescription
`Connectivity`Connectivity of the connected components (objects)
`ImageSize`Size of `BW`
`NumObjects`Number of connected components (objects) in `BW`
`PixelIdxList`

1-by-`NumObjects` cell array where the k-th element in the cell array is a vector containing the linear indices of the pixels in the k-th connected component.

## Tips

• This function sorts the connected components from left to right based on the `top-left` extremum of each component. When multiple components have the same horizontal position, the function then sorts those components from top to bottom, and again along any higher dimensions. This figure illustrates the extrema of two different regions.

• The functions `bwlabel`, `bwlabeln`, and `bwconncomp` all compute connected components for binary images. `bwconncomp` uses significantly less memory and is sometimes faster than the other functions.

FunctionInput DimensionOutput FormMemory UseConnectivity
`bwlabel`2-DLabel matrix with double-precisionHigh4 or 8
`bwlabeln`N-DDouble-precision label matrixHighAny
`bwconncomp`N-D`CC` structLowAny
• To extract features from a binary image using `regionprops` with default connectivity, pass `BW` directly into `regionprops` using the command `regionprops(BW)`.

• To compute a label matrix having more memory-efficient data type (for instance, `uint8` versus `double`), use the `labelmatrix` function on the output of `bwconncomp`.

## Version History

Introduced in R2009a

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