Table 2.

Texture features and their implications.

Textural features	Formula	Implication of the formula
Contrast(Con) (Szantoi et al., 2013)	$C_{\mathbf{\text{OM}}}=\sum _i\sum _{j}P(i,j){(i-j)}^{\mathbf{2}}$	Indicates localized changes in the image
Entroy(Ent) (Szantoi et al., 2013)	$E_{\mathbf{\text{NT}}}=-\mathbf{\sum }_i\mathbf{\sum }_{j}P(i,j)\mathbf{\text{log}}(P(i,j))$	Indicates the randomness of the amount of information contained in the image
Angular Second Moment(Asm) (Szantoi et al., 2013)	$A_{\mathbf{\text{SM}}}=\mathbf{\sum }_i\mathbf{\sum }_{j}P{(i,j)}^{\mathbf{2}}$	Indicates the uniformity of the gray level distribution of the image and the thickness of the texture
Correlation(Cor) (Szantoi et al., 2013)	$C=\sum _{i=\mathbf{0}}^{\mathbf{\text{quank}}}\sum _{j=\mathbf{0}}^{\mathbf{\text{quantk}}}\frac{(i-M_{\mathbf{\text{ean}}})\times (j-M_{\mathbf{\text{ean}}})\times P(i,j)}{V_{\mathbf{\text{ar}}}}$	Indicates the similarity of image gray levels in the row or column direction