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Recently, entropic descriptors based the Monte Carlo hybrid reconstruction ofthe microstructure of a binary/greyscale pattern has been proposed (Piasecki2011 Proc. R. Soc. A 467 806). We try to speed up this method applied in thisinstance to the reconstruction of a binary labyrinth target. Instead of arandom configuration, we propose to start with a suitable synthetic patterncreated by cellular automaton. The occurrence of the characteristic attributesof the target is the key factor for reducing the computational cost that can bemeasured by the total number of MC steps required. For the same set of basicparameters, we investigated the following simulation scenarios: thebiased/random alternately mixed #2m approach, the strictly biased #2b and therandom/partially biased #2rp one. The series of 25 runs were performed for eachscenario. To maintain comparable accuracy of the reconstructions, during thefinal stages the only selection procedure we used was the biased one. Thisallowed us to make the consistent comparison of the first three scenarios. Thepurely random #2r approach of low efficiency was included only for completenessof the approaches. Finally, for the conditions established, the best singlereconstruction and the best average tolerance value among all the scenarioswere given by the mixed #2m method, which was also the fastest one. Theslightly slower the alternative #2b and #2rp variants provided comparable butless satisfactory results.

Speeding up of microstructure reconstruction: I. Application to labyrinth patterns