generated rough surfaces [@hu1992ijmtm; @meakin1998fractals] (as soon as they are not given by analytical functions) are also discrete, i.e. the surface roughness is determined by a matrix of heights $z_{ij}$, where lower indices $i,j$ determine the in-plane position as $z_{ij} = z(i\Delta x, j\Delta y)$, where $\Delta x,\Delta y$ are the sampling intervals in $x,y$ directions, respectively. For such a representation, every potential summit $z'_{ij}$ is identified if the nearest and next-nearest (diagonal) neighbour points are lower: $z'_{ij} > z\left[(k+i)\Delta x,(l+j)\Delta y\right]$, where $k,l$ may take values $\{-1,0,1\}$ except $\{k,l\}=\{0,0\}$. Using the finite differences, for all generalized summits the following values of the components of the fundamental matrix ${\boldsymbol{A}}$ can be estimated as: $$a = \frac12{\frac{\partial ^2\!z}{\partial x^2}} \approx \frac{z_{i+1j}+z_{i-1j}-2z_{ij}}{2\Delta x^2};\quad b=\frac12{\frac{\partial ^2\!z}{\partial y^2}} \approx\frac{z_{ij+1}+z_{ij-1}-2z_{ij}}{2\Delta y^2}$$ $$c = \frac12{\frac{\partial ^2\!z}{\partial x\partial y}} \approx \frac{z_{i+1j+1}+z_{i-1j-1}-z_{i+1j-1}-z_{i-1j+1}}{8\Delta x \Delta y}.$$ The principal curvatures and radii then can be found from . If both curvatures are negative the generalized summit is the real summit. If the principal curvatures have a different sign $\kappa_1\kappa_2 < 0$ this “summit” is a saddle point masked by discretization. The algebraic $\kappa_a$ and the geometric $\kappa_g$ mean curvatures are defined as follows $$\kappa_a = \frac12(\kappa_1+\kappa_2) = \frac12(a+b)$$ $$\kappa_g = 