Aane Integral Invariants for Extracting Symmetry Axes

In this paper, we propose integral invariants based on group invariant parameterisation. The new invariants do not suuer from occlusion problems, do not require any correspondence of image features unlike existing algebraic invariants, and are less sensitive to noise than diier-ential invariants. Our framework applies aane diierential geometry to derive novel aane integral invariants. The new invariants are exploited for extracting the symmetry axes of planar objects viewed under weak perspective. The proposed method is tested on natural leaves and is shown to extract symmetry axes reliably.