Delayed shape matching benefits from simplicity and symmetry

The aim of this study was to evaluate the influence of complexity and symmetry on shape recognition, by measuring the recognition of unfamiliar shapes (created using Fourier Boundary Descriptors, FBDs) through a delayed matching task. Between complexity levels the shapes differed in the frequency of the FBDs and within complexity levels in their phase. Shapes were calibrated to be physically equally similar for the different complexity levels. Matching two sequentially presented shapes was slower and less accurate when complexity increased and for asymmetrical compared to symmetrical versions of the shapes. Thus, we show that simplicity in general and symmetry in particular enhance the short-term recognition of unfamiliar shapes.