A hexagon-based method for polygon generalization using morphological operators

Numerous methods based on square rasters have been proposed for polygon generalization. However, these ignore the inconsistent distance measurement among neighborhoods of squares, which may result in an imbalanced generalization different directions. As alternative raster, a hexagon has consistent connectivity and isotropic neighborhoods. This study hexagon-based method using morphological operators. First, we defined three operators: aggregation, elimination, line simplification, hexagonal operations. We then used corrective operations with selection, skeleton, exaggeration to detect, classify, correct unreasonably reduced narrow parts polygons. To assess effectiveness method, conducted experiments comparing raster vector data. Unlike vector-based various algorithms simplified either areal objects or exterior boundaries, performed both simplifications simultaneously. Compared square-based results were more balanced all neighborhood directions, matched better original polygons, had smoother boundaries. Moreover, it shorter running time than where minimal difference was less 1 min, maximal reached 50 mins.