Documentation

regionprops

Measure properties of image regions

Syntax

  • stats = regionprops(BW,properties)
    example
  • stats = regionprops(CC,properties)
  • stats = regionprops(L,properties)
  • stats = regionprops(___,I,properties)
  • stats = regionprops(output,___)
    example
  • stats = regionprops(gpuarrayImg,___)
    example

Description

example

stats = regionprops(BW,properties) returns measurements for the set of properties specified by properties for each connected component (object) in the binary image, BW. stats is struct array containing a struct for each object in the image. You can use regionprops on contiguous regions and discontiguous regions (see Algorithms).

stats = regionprops(CC,properties) returns measurements for the set of properties specified by properties for each connected component (object) in CC. CC is a structure returned by bwconncomp.

stats = regionprops(L,properties) returns measurements for the set of properties specified by properties for each labeled region in the label matrix L.

stats = regionprops(___,I,properties) returns measurements for the set of properties specified by properties for each labeled region in the image I. The first input to regionprops (BW, CC, or L) identifies the regions in I. The size of the first input must match the size of the image, that is, size(I) must equal size(BW), CC.ImageSize, or size(L).

example

stats = regionprops(output,___) returns measurements for a set of properties, where output specifies the type of return value. regionprops can return these values in a struct or a table.

example

stats = regionprops(gpuarrayImg,___) performs the measurements on a GPU. gpuarrayImg can be a 2-D binary image (logical gpuArray) or a gpuArray label matrix. The connected component structure (CC) returned by bwconncomp is not supported on the GPU.

When run on a GPU, regionprops does not support the following properties: 'ConvexArea', 'ConvexHull', 'ConvexImage', 'EulerNumber', 'FilledArea', 'FilledImage', and'Solidity'.

Code Generation support: Yes.

MATLAB® Function Block support: No.

Examples

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Calculate Centroids and Superimpose Locations on Image

Read binary image into workspace.

BW = imread('text.png');

Calculate centroids for connected components in the image using regionprops.

s = regionprops(BW,'centroid');

Concatenate structure array containing centroids into a single matrix.

centroids = cat(1, s.Centroid);

Display binary image with centroid locations superimposed.

imshow(BW)
hold on
plot(centroids(:,1),centroids(:,2), 'b*')
hold off

Calculate Centroids and Superimpose Locations on Image on a GPU

Read binary image into a gpuArray.

BW = gpuArray(imread('text.png'));

Calculate the centroids of objects in the image.

s  = regionprops(BW,'centroid');

Plot the centroids on the image.

centroids = cat(1, s.Centroid);
imshow(BW)
hold on
plot(centroids(:,1), centroids(:,2), 'b*')
hold off

Estimate Center and Radii of Circular Objects and Plot Circles

Estimate the center and radii of circular objects in an image and use this information to plot circles on the image. In this example, regionprops returns the information it calculates in a table.

Read an image into workspace.

a = imread('circlesBrightDark.png');

Turn the input image into a binary image.

bw = a < 100;
imshow(bw)
title('Image with Circles')

Calculate properties of regions in the image and return the data in a table.

stats = regionprops('table',bw,'Centroid',...
    'MajorAxisLength','MinorAxisLength')
stats = 

        Centroid        MajorAxisLength    MinorAxisLength
    ________________    _______________    _______________

     256.5     256.5    834.46             834.46         
       300       120    81.759             81.759         
    330.47    369.83    111.78             110.36         
       450       240    101.72             101.72         

Get centers and radii of the circles.

centers = stats.Centroid;
diameters = mean([stats.MajorAxisLength stats.MinorAxisLength],2);
radii = diameters/2;

Plot the circles.

hold on
viscircles(centers,radii);
hold off

Input Arguments

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BW — Input binary imagelogical array of any dimension

Input binary image, specified as a logical array of any dimension.

Example: BW = imread('text.png'); s = regionprops(BW,'basic');

Data Types: logical

properties — Type of measurementstring | comma-separated list of strings | cell array of strings | 'all' | 'basic'

Type of measurement, specified as a string, comma-separated list of strings, cell array of strings, or the string 'all' or 'basic'. Property name strings are case-insensitive and can be abbreviated. When used with code generation, regionprops does not support cell arrays of strings.

The following tables list all the properties that provide shape measurements. The properties listed in the Pixel Value Measurements table are only valid when you specify a grayscale image. If you specify 'all', regionprops computes all the shape measurements and, if you specified a grayscale image, the pixel value measurements. If you specify the string 'basic', or do not specify the properties argument, regionprops computes only the 'Area', 'Centroid', and 'BoundingBox' measurements. You can calculate the following properties on N-D inputs: 'Area', 'BoundingBox', 'Centroid', 'FilledArea', 'FilledImage', 'Image', 'PixelIdxList', 'PixelList', and 'SubarrayIdx'.

Shape Measurements

Property Name StringDescriptionN-D SupportGPU SupportCode Generation
'Area'Returns a scalar that specifies the actual number of pixels in the region. (This value might differ slightly from the value returned by bwarea, which weights different patterns of pixels differently.)YesYesYes
'BoundingBox'Returns the smallest rectangle containing the region, specified as a 1-by-Q*2 vector, where Q is the number of image dimensions, for example, [ul_corner width]. ul_corner specifies the upper-left corner of the bounding box in the form [x y z ...]. width specifies the width of the bounding box along each dimension in the form [x_width y_width ...]. regionprops uses ndims to get the dimensions of label matrix or binary image, ndims(L), and numel to get the dimensions of connected components, numel(CC.ImageSize).YesYesYes
'Centroid'Returns a 1-by-Q vector that specifies the center of mass of the region. The first element of Centroid is the horizontal coordinate (or x-coordinate) of the center of mass, and the second element is the vertical coordinate (or y-coordinate). All other elements of Centroid are in order of dimension. This figure illustrates the centroid and bounding box for a discontiguous region. The region consists of the white pixels; the green box is the bounding box, and the red dot is the centroid. YesYesYes
'ConvexArea'Returns a scalar that specifies the number of pixels in 'ConvexImage'.2-D onlyNoNo
'ConvexHull'Returns a p-by-2 matrix that specifies the smallest convex polygon that can contain the region. Each row of the matrix contains the x- and y-coordinates of one vertex of the polygon.2-D onlyNoNo
'ConvexImage'Returns a binary image (logical) that specifies the convex hull, with all pixels within the hull filled in (set to on). The image is the size of the bounding box of the region. (For pixels that the boundary of the hull passes through, regionprops uses the same logic as roipoly to determine whether the pixel is inside or outside the hull.) 2-D onlyNoNo
'Eccentricity'Returns a scalar that specifies the eccentricity of the ellipse that has the same second-moments as the region. The eccentricity is the ratio of the distance between the foci of the ellipse and its major axis length. The value is between 0 and 1. (0 and 1 are degenerate cases. An ellipse whose eccentricity is 0 is actually a circle, while an ellipse whose eccentricity is 1 is a line segment.)2-D onlyYesYes
'EquivDiameter'Returns a scalar that specifies the diameter of a circle with the same area as the region. Computed as sqrt(4*Area/pi).2-D onlyYesYes
'EulerNumber'Returns a scalar that specifies the number of objects in the region minus the number of holes in those objects. This property is supported only for 2-D label matrices. regionprops uses 8-connectivity to compute the Euler number measurement. To learn more about connectivity, see Pixel Connectivity.YesNoYes
'Extent'Returns a scalar that specifies the ratio of pixels in the region to pixels in the total bounding box. Computed as the Area divided by the area of the bounding box.2-D onlyYesYes
'Extrema'Returns an 8-by-2 matrix that specifies the extrema points in the region. Each row of the matrix contains the x- and y-coordinates of one of the points. The format of the vector is [top-left top-right right-top right-bottom bottom-right bottom-left left-bottom left-top]. This figure illustrates the extrema of two different regions. In the region on the left, each extrema point is distinct. In the region on the right, certain extrema points (e.g., top-left and left-top) are identical. 2-D onlyYesYes
'FilledArea'Returns a scalar that specifies the number of on pixels in FilledImage.YesNoYes
'FilledImage'Returns a binary image (logical) of the same size as the bounding box of the region. The on pixels correspond to the region, with all holes filled in, as shown in this figure. YesNoYes
'Image'Returns a binary image (logical) of the same size as the bounding box of the region. The on pixels correspond to the region, and all other pixels are off.YesYesYes
'MajorAxisLength'Returns a scalar that specifies the length (in pixels) of the major axis of the ellipse that has the same normalized second central moments as the region.2-D onlyYesYes
'MinorAxisLength'Returns a scalar that specifies the length (in pixels) of the minor axis of the ellipse that has the same normalized second central moments as the region.2-D onlyYesYes
'Orientation'Returns a scalar that specifies the angle between the x-axis and the major axis of the ellipse that has the same second-moments as the region. The value is in degrees, ranging from -90 to 90 degrees. This figure illustrates the axes and orientation of the ellipse. The left side of the figure shows an image region and its corresponding ellipse. The right side shows the same ellipse with the solid blue lines representing the axes, the red dots are the foci, and the orientation is the angle between the horizontal dotted line and the major axis. 2-D onlyYesYes
'Perimeter'Returns a scalar that specifies the distance around the boundary of the region. regionprops computes the perimeter by calculating the distance between each adjoining pair of pixels around the border of the region. If the image contains discontiguous regions, regionprops returns unexpected results. This figure illustrates the pixels included in the perimeter calculation for this object. 2-D onlyYesv
'PixelIdxList'Returns a p-element vector that contains the linear indices of the pixels in the region. YesYesYes
'PixelList'Returns a p-by-Q matrix that specifies the locations of pixels in the region. Each row of the matrix has the form [x y z ...] and specifies the coordinates of one pixel in the region.YesYesYes
'Solidity'Returns a scalar specifying the proportion of the pixels in the convex hull that are also in the region. Computed as Area/ConvexArea.2-D onlyNoNo
'SubarrayIdx'Returns a cell array that contains indices such that L(idx{:}) extracts the elements of L inside the object bounding box.YesYesNo

The pixel value measurement properties in the following table are valid only when you specify a grayscale image, I.

Pixel Value Measurements

Property Name StringDescriptionN-D SupportGPU SupportCode Generation
'MaxIntensity'Returns a scalar that specifies the value of the pixel with the greatest intensity in the region. NoYesYes
'MeanIntensity'Returns a scalar that specifies the mean of all the intensity values in the region. NoYesYes
'MinIntensity'Returns a scalar that specifies the value of the pixel with the lowest intensity in the region.NoYesYes
'PixelValues'Returns a p-by-1 vector, where p is the number of pixels in the region. Each element in the vector contains the value of a pixel in the region.NoYesYes
'WeightedCentroid'Returns a p-by-Q vector of coordinates specifying the center of the region based on location and intensity value. The first element of WeightedCentroid is the horizontal coordinate (or x-coordinate) of the weighted centroid. The second element is the vertical coordinate (or y-coordinate). All other elements of WeightedCentroid are in order of dimension. NoYesYes

Data Types: char

CC — Connected componentsstructure

Connected components, specified as a structure returned by bwconncomp.

Example: BW = imread('text.png'); CC = bwconncomp(BW); s = regionprops(CC,'basic');

Data Types: struct

L — Labeled regionslabel matrix

Labeled regions, specified as a label matrix. L can have any numeric class and any dimension. regionprops treats negative-valued pixels as background and rounds down input pixels that are not integers. Positive integer elements of L correspond to different regions. For example, the set of elements of L equal to 1 corresponds to region 1; the set of elements of L equal to 2 corresponds to region 2; and so on.

Example: BW = imread('text.png'); L = bwlabel(BW); s = regionprops(L,'basic');

Data Types: single | double | int8 | int16 | int32 | uint8 | uint16 | uint32

I — Image to be measuredgrayscale image

Image to be measured, specified as a grayscale image.

Example: I = imread('cameraman.tif'); s = regionprops(L,I,'basic');

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

output — Return type'struct' (default) | 'table'

Return type, specified as either of these strings.

StringDescription
'struct'Returns an array of structures with length equal to the number of objects in BW, CC.NumObjects, or max(L(:)). The fields of the structure array denote different properties for each region, as specified by properties. If you do not specify this argument, regionprops returns a struct by default.
'table'Returns a MATLAB table with height (number of rows) equal to the number of objects in BW, CC.NumObjects, or max(L(:)). The variables (columns) denote different properties for each region, as specified by properties. To learn more about MATLAB tables, see table.

Not supported on a GPU.

Example: s = regionprops('table',BW,'basic');

Data Types: char

gpuarrayImg — Input image2D logical gpuArray | label matrix gpuArray

Input image, specified as a 2-D logical gpuArray or label matrix gpuArray.

Example: gpuarrayBW = gpuArray(imread('text.png')); s = regionprops(gpuarrayBW,'basic');

Data Types: single | double | int8 | int16 | int32 | uint8 | uint16 | uint32

Output Arguments

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stats — Measurement valuesstruct array (default) | table

Measurement values, returned as an array of structs or a table. The number of structs in the array, or the number of rows in the table, corresponds to the number of objects in BW, CC.NumObjects, or max(L(:)). The fields of each struct, or the variables in each row, denote the properties calculated for each region, as specified by properties.

When run on a GPU, regionprops can only return struct arrays.

More About

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Code Generation

This function supports the generation of C code using MATLAB Coder™. Note that if you choose the generic MATLAB Host Computer target platform, the function generates code that uses a precompiled, platform-specific shared library. Use of a shared library preserves performance optimizations but limits the target platforms for which code can be generated. For more information, see Understanding Code Generation with Image Processing Toolbox.

When generating code, regionprops has the following limitations.

  • Supports only 2-D input images or label matrices.

  • Specifying the output type 'table' is not supported.

  • Passing a cell array of properties is not supported. Use a comma-separated list instead.

  • All properties are supported except ‘ConvexArea', ‘ConvexHull', 'ConvexImage', 'Solidity', and 'SubarrayIdx'.

Tips

  • The function ismember is useful in conjunction with regionprops, bwconncomp, and labelmatrix for creating a binary image containing only objects or regions that meet certain criteria. For example, these commands create a binary image containing only the regions whose area is greater than 80 and whose eccentricity is less than 0.8.

    cc = bwconncomp(BW); 
    stats = regionprops(cc, 'Area','Eccentricity'); 
    idx = find([stats.Area] > 80 & [stats.Eccentricity] < 0.8); 
    BW2 = ismember(labelmatrix(cc), idx);  
    
  • The comma-separated list syntax for structure arrays is very useful when you work with the output of regionprops. For example, for a field that contains a scalar, you can use this syntax to create a vector containing the value of this field for each region in the image. For instance, if stats is a structure array with field Area, then the following expression:

    stats(1).Area, stats(2).Area, ..., stats(end).Area
    

    is equivalent to:

    stats.Area
    

    Therefore, you can use these calls to create a vector containing the area of each region in the image. allArea is a vector of the same length as the structure array stats.

    stats = regionprops(L, 'Area');
    allArea = [stats.Area];
    
  • 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 other functions.

    FunctionInput DimensionOutput FormMemory UseConnectivity
    bwlabel2-DLabel matrix with double-precisionHigh4 or 8
    bwlabelnN-DDouble-precision label matrixHighAny
    bwconncompN-DCC structLowAny

    The output of bwlabel and bwlabeln is a double-precision label matrix. To compute a label matrix using a more memory-efficient data type, use the labelmatrix function on the output of bwconncomp:

    CC = bwconncomp(BW);
    L = labelmatrix(CC);

    If you are measuring components in a binary image with default connectivity, it is no longer necessary to call bwlabel or bwlabeln first. You can pass the binary image directly to regionprops, which then uses the memory-efficient bwconncomp function to compute the connected components automatically. If you need to specify nondefault connectivity, call bwconncomp and then pass the result to regionprops.

    CC = bwconncomp(BW, CONN);
    S = regionprops(CC);
  • Most of the measurements take very little time to compute. However, these measurements can take significantly longer, depending on the number of regions in L:

    • 'ConvexHull'

    • 'ConvexImage'

    • 'ConvexArea'

    • 'FilledImage'

  • Computing certain groups of measurements takes about the same amount of time as computing just one of them because regionprops takes advantage of intermediate computations used in both computations. Therefore, it is fastest to compute all the desired measurements in a single call to regionprops.

Algorithms

Contiguous regions are also called "objects," "connected components," or "blobs." A label matrix containing contiguous regions might look like this:

1 1 0 2 2 0 3 3
1 1 0 2 2 0 3 3
Elements of L equal to 1 belong to the first contiguous region or connected component; elements of L equal to 2 belong to the second connected component; and so on.

Discontiguous regions are regions that might contain multiple connected components. A label matrix containing discontiguous regions might look like this:

1 1 0 1 1 0 2 2
1 1 0 1 1 0 2 2
Elements of L equal to 1 belong to the first region, which is discontiguous and contains two connected components. Elements of L equal to 2 belong to the second region, which is a single connected component.

Introduced before R2006a

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