Haralick's texture features [28] were calculated using
the kharalick() function of the cytometry tool box
[29] for Khoros (version 2.1 Pro, Khoral Research,
Inc., Albuquerque, NM USA; http://www.khoral.com). The basis
for these features is the gray-level co-occurrence matrix
(
G in Equation 2.6). This matrix is square
with dimension N_{g}, where N_{g} is the number of gray levels in the
image. Element [i,j] of the matrix is generated by counting the
number of times a pixel with value i is adjacent to a pixel with
value j and then dividing the entire matrix by the total number of
such comparisons made. Each entry is therefore considered to be the
probability that a pixel with value i will be found adjacent to a
pixel of value j.
Zernike moments through degree 12 were calculated (Z_{nl} such that in Equation 2.4) using the code in Section 5.2.1 (p. ). Since the moments themselves are complex numbers and are sensitive to rotation of the image, the magnitudes of the moments were used as features (i.e. |Z_{nl}|) [21]. This provided 49 descriptive features for each image.
Haralick then described 14 statistics that can be calculated from the co-occurrence matrix with the intent of describing the texture of the image:
Since rotation invariance is a primary criterion for any features used with these images, a kind of invariance was achieved for each of these statistics by averaging them over the four directional co-occurrence matrices. The maximal correlation coefficient was not calculated due to computational instability so there were 13 texture features for each image.