Image Processing Toolbox User's Guide |

Properties of a gray-level co-occurrence matrix

**Syntax**

**Description**

```
stats = graycoprops(glcm, properties)
```

calculates the statistics specified in `properties`

from the gray-level co-occurence matrix `glcm`

. `glcm`

is an *m*-by-*n*-by-*p* array of valid gray-level co-occurrence matrices. If `glcm`

is an array of GLCMs, `stats`

is an array of statistics for each `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`

.

`properties`

can be a comma-separated list of strings, a cell array containing strings, the string `'all'`

, or a space separated string. The property names can be abbreviated and are not case sensitive.

`stats`

is a structure with fields that are specified by `properties`

. Each field contains a 1 x p array, where p is the number of gray-level co-occurrence matrices in GLCM. For example, if GLCM is an 8 x 8 x 3 array and properties is `'Energy'`

, then `stats`

is a structure containing the field Energy, which contains a 1 x 3 array.

**Notes**

Energy is also known as uniformity, uniformity of energy, and angular second moment.

Contrast is also known as variance and inertia.

**Class Support **

`glcm`

can be logical or numeric, and it must contain real, non-negative, finite, integers. `stats`

is a structure.

**Example**

GLCM = [0 1 2 3;1 1 2 3;1 0 2 0;0 0 0 3]; stats = graycoprops(GLCM) I = imread('circuit.tif'); GLCM2 = graycomatrix(I,'Offset',[2 0;0 2]); stats = graycoprops(GLCM2,{'contrast','homogeneity'})

**See Also**

graycomatrix | grayslice |

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