graycoprops
Properties of gray-level co-occurrence matrix (GLCM)
Description
calculates the statistics specified in stats
= graycoprops(glcm
,properties
)properties
from the
gray-level co-occurrence matrix glcm
.
graycoprops
normalizes the gray-level co-occurrence matrix (GLCM) so that
the sum of its elements is equal to 1. Each element
(r,c) in the normalized GLCM is the joint
probability occurrence of pixel pairs with a defined spatial relationship having
gray level values r and c in the image.
graycoprops
uses the normalized GLCM to calculate
properties
.
Examples
Create simple sample GLCM.
glcm = [0 1 2 3;1 1 2 3;1 0 2 0;0 0 0 3]
glcm = 4×4
0 1 2 3
1 1 2 3
1 0 2 0
0 0 0 3
Calculate statistical properties of the GLCM.
stats = graycoprops(glcm)
stats = struct with fields:
Contrast: 2.8947
Correlation: 0.0783
Energy: 0.1191
Homogeneity: 0.5658
Read grayscale image into the workspace.
I = imread('circuit.tif');
Create two gray-level co-occurrence matrices (GLCM) from the image, specifying different offsets.
glcm = graycomatrix(I,'Offset',[2 0;0 2])
glcm = glcm(:,:,1) = 14205 2107 126 0 0 0 0 0 2242 14052 3555 400 0 0 0 0 191 3579 7341 1505 37 0 0 0 0 683 1446 7184 1368 0 0 0 0 7 116 1502 10256 1124 0 0 0 0 0 2 1153 1435 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 glcm(:,:,2) = 13938 2615 204 4 0 0 0 0 2406 14062 3311 630 23 0 0 0 145 3184 7371 1650 133 0 0 0 2 371 1621 6905 1706 0 0 0 0 0 116 1477 9974 1173 0 0 0 0 0 1 1161 1417 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Get statistics on contrast and homogeneity of the image from the GLCMs.
stats = graycoprops(glcm,{'contrast','homogeneity'})
stats = struct with fields:
Contrast: [0.3420 0.3567]
Homogeneity: [0.8567 0.8513]
Input Arguments
GLCM, specified as one of the following. You can use the graycomatrix
function to
create a GLCM.
An m-by-n matrix of nonnegative integers for a single GLCM
An m-by-n-by-p array of nonnegative integers for p valid GLCMs.
Data Types: single
| double
| int8
| int16
| int32
| int64
| uint8
| uint16
| uint32
| uint64
| logical
Statistical properties of the image derived from GLCM, specified as a
comma-separated list string scalars or character vectors, cell array of
string scalars or character vectors, string array, space-separated character
vector, or "all"
. You can specify any of the property
names listed in this table.
Property | Description | Formula |
---|---|---|
| Returns a measure of the intensity contrast between a pixel and its neighbor over the whole image. Range = [0 (size(GLCM,1)-1)^2] Contrast is 0 for a constant image. The property Contrast is also known as variance and inertia. | |
| Returns a measure of how correlated a pixel is to its neighbor over the whole image.
Correlation is 1 or -1 for a
perfectly positively or negatively correlated image.
Correlation is | |
| Returns the sum of squared elements in the GLCM. Range = [0 1] Energy
is The property Energy is also known as uniformity, uniformity of energy, and angular second moment. | |
| Returns a value that measures the closeness of the distribution of elements in the GLCM to the GLCM diagonal. Range = [0 1] Homogeneity is 1 for a diagonal GLCM. |
Example: "Contrast","Homogeneity"
specifies two
properties as a comma-separated list of string scalars
Example: ["Contrast","Homogeneity"]
specifies two
properties as an array of string scalars
Example: {"Contrast","Homogeneity"}
specifies two
properties as cell array of string scalars
Example: 'Contrast Homogeneity'
specifies two properties
as a space-separated character vector
Data Types: char
| string
| cell
Output Arguments
Statistics derived from the GLCM, returned as a structure with fields that
are specified by properties
. Each field contains a
1-by-p array, where p is the
number of gray-level co-occurrence matrices in glcm
.
For example, if glcm
is an 8-by-8-by-3 array and
properties is "Energy"
, then stats
is
a structure containing the field Energy
, which contains a
1-by-3 array.
Version History
Introduced before R2006a
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