  Recently, entropic descriptors based the Monte Carlo hybrid reconstruction of
the microstructure of a binary/greyscale pattern has been proposed (Piasecki
2011 Proc. R. Soc. A 467 806). We try to speed up this method applied in this
instance to the reconstruction of a binary labyrinth target. Instead of a
random configuration, we propose to start with a suitable synthetic pattern
created by cellular automaton. The occurrence of the characteristic attributes
of the target is the key factor for reducing the computational cost that can be
measured by the total number of MC steps required. For the same set of basic
parameters, we investigated the following simulation scenarios: the
biased/random alternately mixed #2m approach, the strictly biased #2b and the
random/partially biased #2rp one. The series of 25 runs were performed for each
scenario. To maintain comparable accuracy of the reconstructions, during the
final stages the only selection procedure we used was the biased one. This
allowed us to make the consistent comparison of the first three scenarios. The
purely random #2r approach of low efficiency was included only for completeness
of the approaches. Finally, for the conditions established, the best single
reconstruction and the best average tolerance value among all the scenarios
were given by the mixed #2m method, which was also the fastest one. The
slightly slower the alternative #2b and #2rp variants provided comparable but
less satisfactory results.
