  We investigate the estimation of specific intrinsic volumes of stationary
Boolean models by local digital algorithms; that is, by weighted sums of $n
\times\ldots \times n$ configuration counts. We show that asymptotically
unbiased estimators for the specific surface area or integrated mean curvature
do not exist if the dimension is at least two or three, respectively. For
3-dimensional stationary, isotropic Boolean models, we derive asymptotically
unbiased estimators for the specific surface area and integrated mean
curvature. For a Boolean model with balls as grains we even obtain an
asymptotically unbiased estimator for the specific Euler characteristic.
