Equations for 3D Haralick Texture Feature
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− | --<math>p_{x+y}(k):</math> <math> p_{x+y}(k) = \sum_{i= | + | --<math>p_{x+y}(k):</math> <math> p_{x+y}(k) = \sum_{i=1}^{N_g} \sum_{j=1,i+j=k}^{N_g} p(i,j), k=2,3,...,2N_g </math> |
− | --<math>p_{x-y}(k):</math> <math> p_{x-y}(k) = \sum_{i= | + | --<math>p_{x-y}(k):</math> <math> p_{x-y}(k) = \sum_{i=1}^{N_g} \sum_{j=1,|i-j|=k}^{N_g} p(i,j), k=0,1,...,N_g-1 </math> |
+ | |||
+ | ==Textural Features== | ||
+ | * 1) Angular Second Moment:<math>f_1 = \sum_{i=1}^{N_g} \sum_{j=1}^{N_g} p(i,j)^2 </math> | ||
+ | * 2) Contrast:<math>f_2 = \sum_{n=0}^{N_g - 1} n^2 {\sum_{i=1}^{N_g} \sum_{j=1,|i-j|=n}^{N_g} p(i,j)} </math> | ||
+ | * 3) Correlation:<math>f_3 = \cfrac{\sum_i \sum_j (i,j)p(i,j)-u_x u_y}{\sigma_x \sigma_y}</math> | ||
+ | * 4) Sum of the Squares of Variance: <math>f_4 = \sum_{i=1}^{N_g} \sum_{j=1}^{N_g} (i-j)^2 p(i,j)</math> | ||
+ | * 5) Inverse Difference Moment: <math>f_5 = \sum_i \sum_j \cfrac{1}{1+(i-j)^2}p(i,j)</math> |
Revision as of 02:47, 27 April 2009
Notation
--p(i,j): (i,j)th entry in a normalized gray-tone spatial dependence matrix, p(i,j) = P(i,j) / R * P(i,j) is the co-occurrence matrix and R is the sum of values in it, thus P(i,j) can be considered as the joint distribution of i and j, which are gray levels of the original image. The value of entry p(i,j) is supposed to be very small due to the large size of the co-occurrence matrix.
--px(i) / py(i): ith entry in the marginal-probability distribution matrix obtained by summing the rows/columns of p(i,j).
--Ng: Number of distinct gray levels in the image.
--px + y(k):
--px − y(k):
Textural Features
- 1) Angular Second Moment:
- 2) Contrast:
- 3) Correlation:
- 4) Sum of the Squares of Variance:
- 5) Inverse Difference Moment: