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# bwlabeln() - Image Processing

### Syntax

### Example

### Output / Return Value

### Limitations

### Alternatives / See Also

### Reference

L = bwlabeln(BW) returns a label matrix, L, containing labels for the connected components in BW. The input image BW can have any dimension; L is the same size as BW. The elements of L are integer values greater than or equal to 0. The pixels labeled 0 are the background. The pixels labeled 1 make up one object; the pixels labeled 2 make up a second object; and so on. The default connectivity is 8 for two dimensions, 26 for three dimensions, and conndef(ndims(BW), 'maximal') for higher dimensions.[L, NUM] = bwlabeln(BW) returns in NUM the number of connected objects found in BW.[L, NUM] = bwlabeln(BW, conn) specifies the desired connectivity. conn can have any of the following scalar values.ValueMeaning Two-dimensional connectivities 44-connected neighborhood 88-connected neighborhood Three-dimensional connectivities 66-connected neighborhood 1818-connected neighborhood 2626-connected neighborhood Connectivity can also be defined in a more general way for any dimension by using for conn a 3-by-3-by- ...-by-3 matrix of 0s and 1s. The 1-valued elements define neighborhood locations relative to the central element of conn. Note that conn must be symmetric about its central element.The functions bwlabel, bwlabeln, and bwconncomp all compute connected components for binary images. bwconncomp replaces the use of bwlabel and bwlabeln. It uses significantly less memory and is sometimes faster than the older functions.FunctionInput DimensionOutput FormMemory UseConnectivity bwlabel2-DDouble-precision label matrixHigh4 or 8 bwlabelnN-DDouble-precision label matrixHighAny bwconncompN-DCC structLowAny

L = bwlabeln(BW)[L, NUM] = bwlabeln(BW)[L, NUM] = bwlabeln(BW, conn)

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]) bwlabeln(BW) ans(:,:,1) = 1 1 0 0 0 0 2 0 0 ans(:,:,2) = 0 1 0 0 0 0 0 2 0 ans(:,:,3) = 0 1 1 0 0 0 0 0 2