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wvtool (version 1.0)

haralick: Haralick Texture Features Calculated from GLCM

Description

A function returns 15 Halarick features for 4 directions, their average and range.

Usage

haralick(x)

Arguments

x
output of glcm() function from a TIFF data

Value

Details

15 outputs are #1 Angular Second Moment / Homogeniety "asm" #2 Contrast "con" #3 inverse Difference Moment "idm" #4 Entropy "ent" #5 Correlation "cor" #6 Variance in Haralick 1973 "var" #7 Sum Average "sav" #8 Sum Entropy "sen" #9 Difference Entropy "den" #10 Difference Variance "dva" #11 Sum Variance "sva" #12 Information Measures of Correlation "f12" #13 Information Measures of Correlation "f13" #14 Cluster Shade "sha" #15 Cluster prominence "pro", respectively

References

R.M. Haralick, K. Shangmugam, Its'hak Dinstein (1973) Textural Features for Image Classification, IEEE Transactions on Systems, Man, and Cybernetics, SMC-3(6), 610-621. Albregtsen F (1995) Statistical texture measures computed from gray level cooccurrence matrices. In: Technical Note, Department of Informatics, University of Oslo, Norway

K. Kobayashi, M. Akada, T. Torigoe, S. Imazu, J. Sugiyama (2015) Automated recognition of wood used in traditional Japanese sculptures by texture analysis of their low-resolution computerd comography data. J. Wood Sci., 61, 630-640.

See Also

glcm

Examples

Run this code
data(camphora)
haralick(glcm(camphora,6,1))

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