1109.3819 (R. Piasecki et al.)

Speeding up microstructure reconstruction. I. Application to labyrinth
patterns    [PDF]

R. Piasecki, W. Olchawa

Recently, entropic descriptors based the Monte Carlo hybrid reconstruction of binary/greyscale pattern's microstructure has been proposed [10]. 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 the suitable synthetic pattern created by cellular automaton. The occurrence of the target's characteristic attributes is the key factor for reducing the computational cost that can be measured by the total number of needed MC steps. For the same set of basic parameters, we investigate 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 for each scenario were done. To obtain comparable accuracy of the reconstructions, at 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, as well as the best average tolerance value among the all scenarios gives the mixed #2m method that is also the fastest one. The slightly slower the alternative #2b and #2rp variants provide comparable though less satisfactory results.

View original: http://arxiv.org/abs/1109.3819