Texture Analysis Using the GrayLevel CoOccurrence Matrix (GLCM) A statistical method of examining texture that considers the spatial relationship of pixels is the graylevel cooccurrence matrix (GLCM), also known as the graylevel spatial dependence matrix. Feb 22, 2018 Calculates texture features from the input GLCMs# Matlab# ImageProcessing# MatlabDublin The graylevel cooccurrence matrix can reveal certain properties about the spatial distribution of the gray levels in the texture image.
For example, if most of the entries in the GLCM are concentrated along the diagonal, the texture is Jan 08, 2010 glcm graycomatrix(I) creates a graylevel cooccurrence matrix (GLCM) from image I.
graycomatrix creates the GLCM by calculating how often a pixel with graylevel (grayscale intensity) value i occurs A cooccurrence matrix or cooccurrence distribution is a matrix that is defined over an image to be the distribution of cooccurring pixel values (grayscale values, or colors) at a GrayLevel Cooccurrence Matrices (GLCMs) Consider the image (below left). If we use the position operator 1 pixel to the right and 1 pixel down then we get the graylevel cooccurrence matrix (below right) 0 0 0 1 2 Problems associated with the cooccurrence matrix methods: 1.
they require a lot of computation (many matrices to be tabulated in a cooccurrence matrix, and specific statistical measures are com puted from this matrix to produce the filtered value for the target cell. A gray level cooccurrence matrix is illustrated above for a 5 by 5 glcms graycomatrix(I) creates a graylevel cooccurrence matrix (GLCM) from image I. Another name for a graylevel cooccurrence matrix is a graylevel spatial dependence matrix.
Also, the word cooccurrence is frequently used in the literature without a hyphen, cooccurrence.