greycomatrix(image, distances, angles, levels=None, symmetric=False, normed=False)
A grey level co-occurrence matrix is a histogram of co-occurring greyscale values at a given offset over an image.
Integer typed input image. Only positive valued images are supported. If type is other than uint8, the argument :None:None:`levels` needs to be set.
List of pixel pair distance offsets.
List of pixel pair angles in radians.
The input image should contain integers in [0, :None:None:`levels`-1], where levels indicate the number of grey-levels counted (typically 256 for an 8-bit image). This argument is required for 16-bit images or higher and is typically the maximum of the image. As the output matrix is at least :None:None:`levels` x :None:None:`levels`, it might be preferable to use binning of the input image rather than large values for :None:None:`levels`.
If True, the output matrix :None:None:`P[:, :, d, theta]` is symmetric. This is accomplished by ignoring the order of value pairs, so both (i, j) and (j, i) are accumulated when (i, j) is encountered for a given offset. The default is False.
If True, normalize each matrix :None:None:`P[:, :, d, theta]` by dividing by the total number of accumulated co-occurrences for the given offset. The elements of the resulting matrix sum to 1. The default is False.
The grey-level co-occurrence histogram. The value :None:None:`P[i,j,d,theta]` is the number of times that grey-level :None:None:`j` occurs at a distance d and at an angle :None:None:`theta` from grey-level i. If :None:None:`normed` is :None:None:`False`, the output is of type uint32, otherwise it is float64. The dimensions are: levels x levels x number of distances x number of angles.
Calculate the grey-level co-occurrence matrix.
Compute 2 GLCMs: One for a 1-pixel offset to the right, and one for a 1-pixel offset upwards.
This example is valid syntax, but we were not able to check execution>>> image = np.array([[0, 0, 1, 1],This example is valid syntax, but we were not able to check execution
... [0, 0, 1, 1],
... [0, 2, 2, 2],
... [2, 2, 3, 3]], dtype=np.uint8)
... result = greycomatrix(image, [1], [0, np.pi/4, np.pi/2, 3*np.pi/4],
... levels=4)
... result[:, :, 0, 0] array([[2, 2, 1, 0], [0, 2, 0, 0], [0, 0, 3, 1], [0, 0, 0, 1]], dtype=uint32)
>>> result[:, :, 0, 1] array([[1, 1, 3, 0], [0, 1, 1, 0], [0, 0, 0, 2], [0, 0, 0, 0]], dtype=uint32)This example is valid syntax, but we were not able to check execution
>>> result[:, :, 0, 2] array([[3, 0, 2, 0], [0, 2, 2, 0], [0, 0, 1, 2], [0, 0, 0, 0]], dtype=uint32)This example is valid syntax, but we were not able to check execution
>>> result[:, :, 0, 3] array([[2, 0, 0, 0], [1, 1, 2, 0], [0, 0, 2, 1], [0, 0, 0, 0]], dtype=uint32)See :
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skimage.feature.texture.greycomatrix
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