graycoprops

Properties of gray-level co-occurrence matrix (GLCM)

Syntax

stats = graycoprops(glcm,properties)

Description

stats = graycoprops(glcm,properties) calculates the statistics specified in 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

Calculate Statistics from Gray-level Co-occurrence Matrix

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

Calculate Contrast and Homogeneity from Multiple GLCMs

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 — GLCM

matrix of nonnegative integers | array of nonnegative integers

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

properties — Statistical properties

"all" (default) | comma-separated list of string scalars or character vectors | cell array of string scalars or character vectors | string array | space-separated character vector

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
"Contrast"	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.	$${{\displaystyle \sum _{i,j}\left|i-j\right|}}^{2}p(i,j)$$
"Correlation"	Returns a measure of how correlated a pixel is to its neighbor over the whole image. Range = [-1 1] Correlation is 1 or -1 for a perfectly positively or negatively correlated image. Correlation is NaN for a constant image.	$${\displaystyle \sum _{i,j}\frac{(i-\mu i)(j-\mu j)p(i,j)}{{\sigma }_i{\sigma }_j}}$$
"Energy"	Returns the sum of squared elements in the GLCM. Range = [0 1] Energy is 1 for a constant image. The property Energy is also known as uniformity, uniformity of energy, and angular second moment.	$${\displaystyle \sum _{i,j}p{(i,j)}^2}$$
"Homogeneity"	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.	$${\displaystyle \sum _{i,j}\frac{p(i,j)}{1+\left|i-j\right|}}$$

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

stats — Statistics derived from GLCM

structure

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