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.

In this paper,the methods for CBIR is based on color co-occurrence matrix-a new conception which proposed on the basis of grey level co-occurrence matrix.

Seven feature parameters of grey level co-occurrence matrix(GLCM) and ten shape feature formulae of Hu invariant moments were combined when discussing the parameters of Panthera tigris altaica individual recognition.

This paper investigates the collection of textural parameters according to the analysis of grey level co-occurrence matrix and classification of Brodatz texture database by means of BP neural network ensemble.