A histogram-based segmentation method for characterization of self-assembled hexagonal lattices

Lattice characterization techniques are often used to quantify the effects of different anodization conditions on nano-porous anodized aluminum oxides. In this work, we develop a comprehensive hexagonal lattice characterization method to evaluate the amount of ordering of the lattice and localize the domains of the image and report their characteristics. A robust preprocessing is proposed to find pores’ centroids. Different domains of SEM images usually have different orientations. Pores orientation distribution is analyzed using angle-histogram. The valleys of angle-histogram are employed as thresholds to separate different dominant orientations. We show that using orientation as a distinguishing feature of different domains, significantly improves the robustness of the algorithm against tolerance parameters. Some new parameters are introduced to exactly characterize each of the domains and the whole lattice.