This is machine translation

Translated by Microsoft
Mouseover text to see original. Click the button below to return to the English verison of the page.

Note: This page has been translated by MathWorks. Please click here
To view all translated materals including this page, select Japan from the country navigator on the bottom of this page.

Texture Analysis

Entropy, range, and standard deviation filtering; create gray-level co-occurrence matrix


entropy Entropy of grayscale image
entropyfilt Local entropy of grayscale image
rangefilt Local range of image
stdfilt Local standard deviation of image
graycomatrix Create gray-level co-occurrence matrix from image
graycoprops Properties of gray-level co-occurrence matrix

Examples and How To

Detect Regions of Texture in Images

This example shows how to detect regions of texture in an image using the texture filter functions

Specify Offset Used in GLCM Calculation

By default, the graycomatrix function creates a single GLCM, with the spatial relationship, or offset, defined as two horizontally adjacent pixels.

Derive Statistics from GLCM and Plot Correlation

This example shows how to create a set of GLCMs and derive statistics from them.


Texture Analysis

Texture analysis refers to the characterization of regions in an image by their texture content.

Texture Analysis Using the Gray-Level Co-Occurrence Matrix (GLCM)

A statistical method of examining texture that considers the spatial relationship of pixels is the gray-level co-occurrence matrix (GLCM), also known as the gray-level spatial dependence matrix.

Create a Gray-Level Co-Occurrence Matrix

To create a GLCM, use the graycomatrix function.

Was this topic helpful?