Straight skeletons for binary shapes
M. Demuth, F. Aurenhammer, and A. Pinz
This paper reviews the concept of straight skeletons, which is well known in
computational geometry, and applies it to binary shapes that are used in
vision-based shape and object recognition. We devise a novel algorithm for
computing discrete straight skeletons from binary input images, which is
based on a polygonal approximation of the input shape and a hybrid method
that combines continuous and discrete geometry. In our experiments, we
analyze the potential of straight skeletons in shape recognition, by
comparing their performance with medial-axis based shock graphs on the Kimia
shape databases. Our discrete straight skeleton algorithm is not only
outperforming typical skeleton algorithms in terms of computational
complexity, it also delivers surprisingly good results in its straightforward
application to shape recognition.
Reference: M. Demuth, F. Aurenhammer, and A. Pinz.
Straight skeletons for binary shapes.
In Workshop on non-rigid shape analysis and deformable image
alignment (NORDIA'10), San Francisco, USA, 2010.