For evaluating the skin texture objectively, a novel measuring and recognizing model for skin texture is founded based on adopting spatial gray level co-occurrence matrix of image texture analysis to extract important features of skin texture.

Texture Image Retrival Based on Wavelet Decomposition and Gray Level Co-occurrence Matrix;

Texture segmentation on the scale co-occurrence matrix and gray level co-occurrence matrix;

A Self-adaptable Method to Detect Edge in Images Based on Gray level co-occurrence matrix;

Wood Texture Classification and Recognition Based on Spatial GLCM;

Research on Building Method of GLCM Suitable to Wood Texture;

First,GLCM was used to extract the feature parameters of the wood textures.

Study on identification of fabric texture based on gray-level co-occurrence matrix;

Then texture features are extracted based on gray-level co-occurrence matrix.

The traditional gray-level co-occurrence matrix (GLCM) was computationally intensive and discriminatively insufficient.

This paper integrates the advantages of the traditional co-occurrence matrix and generalized image co-occurrence matrix and proposes an improved method based on generalized image co-occurrence matrix.

Based on gray level co-occurrence matrix, we got the features of an image.

This paper studies the extraction of texture features of remote sensing images using gray-scale extraction of co-occurrence matrix,realized the classification and analysis for panchromatic remote sensing image using the shortest distance classifier and filter of the supervised classification methods under MATLAB.