Mryka Hall-Beyer

Tutorial: GLCM Texture

What is texture?   The GLCM   Practical Notes   More Information and References

 Exercises   Examples   Equations


Calculating texture measures from the GLCM

Most texture calculations are weighted averages of the normalized GLCM cell contents.

A weighted average multiplies each value to be used by a factor (a weight) before summing and dividing by the number of values. The weight is intended to express the relative importance of the value.

Example: the most common weighted average that students encounter is the term grade. Exams usually have a higher weight than quizzes. The weights are the % of course grade assigned to each mark.


Creating a texture image

The result of a texture calculation is a single number representing the entire window. This number is put in the place of the centre pixel of the window, then the window is moved one pixel and the process is repeated of calculating a new GLCM and a new texture measure. In this way an entire image is built up of texture values. More information

Edge of image problems Each cell in a window must sit over an occupied image cell. This means that the centre pixel of the window cannot be an edge pixel of the image. If a window has dimension N x N, a strip (N-1)/2 pixels wide around the image will remain unoccupied. The usual way of handling this is to fill in these edge pixels with the nearest texture calculation.

Example: For a 5x5 window, the outer 2 rows and columns of the image receive the texture values calculated in row 3 (top edge), column 3 (left edge), row L-2 (bottom edge) and column P-2 (right edge) where P,L are the dimensions in pixels and lines of the original image. For the illustrated image, L=P=10, so values are calculated from row 3 and column 3 through row 8 and column 8.

Image edge pixels usually represent a very small fraction of total image pixels, so this is only a minor problem. However, if the image is very small or the window is very large, the image edge effect should be remembered when examining the texture image.
Edge effects can be a problem in classification. For an excellent discussion, see Ferro and Warner 2002.


Groups of texture measures

This tutorial groups the texture measures according to the purpose of the weights in the equations. The major groups are briefly listed here. Details for each group are in the links at the top of this page.

Another common way to classify textures is according to their degree, meaning the highest exponent used. Most measures - and all used here - are first or second degree.

Example: If a squared term is used, the measure is second degree. If a cubed term is used, it is third degree.

1. Contrast group: Measures related to contrast use weights related to the distance from the GLCM diagonal.

2. Measures related to orderliness

3. Group using descriptive statistics  of the GLCM texture measures


To go to a particular group click  below.


To continue through the tutorial, click the next button to go to the contrast group.