UTLN-Reflection

Existing datasets  for reflection symmetry detection contain shapes which are single contour shapes, thus they are not really challenging. We also need to consider how well a symmetry detector works on complex/compound shapes where traditional methods based on contour approach can not. On the other hand, there is only one symmetrical axes for every shape of this dataset. Therefore, this fails to evaluate how a symmetry detector works on a shape containing several symmetrical axis and how good the detection is when the number of symmetrical axis is unknown. In order to address those above shortcomings, we introduce in this paper a new dataset, called ``UTLN Reflection dataset'', designed for evaluation of reflectional symmetry detection. The dataset, which is created by collecting free images on the Internet, contains two test suites: SRA (Single Reflection Axis) and MRA (Multiple Reflection Axes).