grabcut
Segment image into foreground and background using iterative graph-based segmentation
Syntax
Description
BW = grabcut(___,Name,Value)
Examples
Segment Foreground from Background in Image Using Grabcut
Read an RGB image into the workspace.
RGB = imread('peppers.png');Generate label matrix.
L = superpixels(RGB,500);
Specify a region of interest and create a mask image.
figure imshow(RGB) h1 = drawpolygon(gca,'Position',[72,105; 1,231; 0,366; 104,359;... 394,307; 518,343; 510,39; 149,72]);
roiPoints = h1.Position; roi = poly2mask(roiPoints(:,1),roiPoints(:,2),size(L,1),size(L,2));
Perform the grab cut operation, specifying the original image, the label matrix and the ROI.
BW = grabcut(RGB,L,roi); figure imshow(BW)
Create masked image.
maskedImage = RGB; maskedImage(repmat(~BW,[1 1 3])) = 0; figure; imshow(maskedImage)
Segment 3-D Volume Using Grabcut
Load 3-D volumetric data.
load mristack
V = mristack;Create a 2-D mask for initial foreground and background seed points.
seedLevel = 10; fseed = V(:,:,seedLevel) > 75; bseed = V(:,:,seedLevel) == 0;
Display foreground and background seed points.
imshow(fseed)
imshow(bseed)
Place seed points into empty 3-D mask.
fmask = zeros(size(V)); bmask = fmask; fmask(:,:,seedLevel) = fseed; bmask(:,:,seedLevel) = bseed;
Create initial region of interest.
roi = false(size(V)); roi(10:end-10,10:end-10,:) = true;
Generate label matrix.
L = superpixels3(V,500);
Perform GrabCut.
bw = grabcut(V,L,roi,fmask,bmask);
Display 3D segmented image.
montage(reshape(bw,size(V)))
Input Arguments
A — Image to segment
2-D grayscale image | 2-D truecolor image | 3-D grayscale volume
Input image or volume, specified as a 2-D grayscale image, 2-D truecolor
image, or 3-D grayscale volume. Only grayscale images can be data type
int16.
Data Types: single | double | int16 | uint8 | uint16
L — Label matrix
numeric array
Label matrix, specified as a numeric array.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | logical
ROI — Region of interest
logical array
Region of interest, specified as a logical array. All pixels that define
the region of interest are equal to true.
Data Types: logical
foremask — Foreground mask
logical array
Foreground mask, specified as a logical array.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | logical
backmask — Background mask
logical array
Background mask, specified as a logical array.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | logical
foreind — Indices of pixels in foreground
vector
Indices of pixels in foreground, specified as a vector of linear indices.
Data Types: double
backind — Indices of pixels in background
vector
Indices of pixels in background, specified as a vector of linear indices.
Data Types: double
Name-Value Pair Arguments
Specify optional
comma-separated pairs of Name,Value arguments. Name is
the argument name and Value is the corresponding value.
Name must appear inside quotes. You can specify several name and value
pair arguments in any order as
Name1,Value1,...,NameN,ValueN.
BW = grabcut(A,L,ROI,'Connectivity',4)'Connectivity' — Connectivity of connected components
4 | 8 | 6 | 18 | 26
Connectivity of connected components, specified as one of the following values. The default connectivity is 8 for 2–D images, and 26 for 3–D images.
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
|
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
'MaximumIterations' — Maximum number of iterations
5 (default) | positive scalar
Maximum number of iterations performed by the algorithm. The algorithm can converge to a solution before reaching the maximum number of iterations.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
Output Arguments
Tips
For
doubleandsingleimages,grabcutassumes the range of the image to be[0 1]. Foruint16,int16, anduint8images,grabcutassumes the range to be the full range for the given data type.For grayscale images, the size of
L,foremask, andbackmaskmust match the size of the imageA. For color and multi-channel images,L,foremask, andbackmaskmust be 2-D arrays with the first two dimensions identical to the first two dimensions of the imageA.
Algorithms
The algorithm treats all subregions fully or spatially outside the ROI mask as belonging to the background. To get an optimal segmentation, make sure the object to be segmented is fully contained within the ROI, surrounded by a small number of background pixels.
Do not mark a subregion of the label matrix as belonging to both the foreground mask and the background mask. If a region of the label matrix contains pixels belonging to both the foreground mask and background mask, the algorithm effectively treats the region as unmarked.
The algorithm assumes all subregions outside the region of interest belong to the background. Marking one of these subregions as belonging to foreground or background mask has no effect on the resulting segmentation.
References
[1] Rother, C., V. Kolmogorov, and A. Blake. "GrabCut - Interactive Foreground Extraction using Iterated Graph Cuts". ACM Transactions on Graphics (SIGGRAPH). Vol. 23, Number 3, 2004, pp. 309–314.