haralickMatrix {EBImage}R Documentation

Co-occurrence matrices (GLCM) and Haralick texture features

Description

Computes the gray level co-occurrence matrix (GLCM, frequency of pixel intensities given the mean intensity of their 4 neighbouring pixels) and corresponding Haralick features from image objects.

Usage

  haralickFeatures(x, ref, nc = 32)
  haralickMatrix(x, ref, nc = 32)

Arguments

x An Image object or an array containing object masks. Object masks are sets of pixels with the same unique integer value.
ref An Image object or an array, containing the intensity values of the objects.
nc A numeric value. Specifies the number of gray levels used to compute the co-occurrence matrix. Default value is 32.

Details

haralickFeatures computes the following set of statistics on the GLCM matrix:

where:

Computed Haralick features are rotational invariant and good descriptors of object textures.

Value

haralickFeatures returns a matrix (or a list of matrices if x contains multiple frames) of features computed of the objects present in x and using the intensity values of ref.
haralickMatrix returns an array (or a list of arrays if x contains multiple frames) of dimension nc*nc*nobj, where nobj is the number of objects in x, containing the GLCM values of image objects.

Author(s)

Mike Smith, msmith@ebi.ac.uk; Oleg Sklyar, osklyar@ebi.ac.uk, 2007

References

R. M. Haralick, K Shanmugam and Its'Hak Deinstein (1979). Textural Features for Image Classification. IEEE Transactions on Systems, Man and Cybernetics.

See Also

getFeatures, zernikeMoments

Examples

  example(getFeatures)

[Package EBImage version 3.0.5 Index]