Texture Analysis in MATLAB

Texture analysis refers to characterizing regions in an image by their texture content. Texture analysis attempts to quantify intuitive qualities described by terms such as rough, smooth, silky, or bumpy as a function of spatial variation in pixel intensity. In this sense, roughness or non-uniformity refers to variations in intensity values ​​or gray levels.

Texture Analysis defines some functionality as follows.

• entropy – it’s a statistical measure of randomness.
• entropyfilt – it’s used to measure some relative changes in the image.
• rangefilt – it’s can return an array of output pixels. 
• graycomatrix – it’s used to calculate the GLCM form of an image.
• graycoprops – it can normalize the gray-level co-occurrence matrix (GLCM).

GLCM stands for Gray Level Co-occurrence Matrix. In image processing, The GLCM function computes how often pairs of pixels with a particular value and in a particular spatial relationship occur in an image, constructs a GLCM, and extracts statistical measures from this matrix to determine the texture of an image. characterize the (The texture filter functions described in Computing Statistical Texture Measures cannot provide information about the shape, that is, the spatial relationship of pixels in an image.)