I have two shapes in a 2D space, not necessarily convex, and I'd like to compare how similar they are. How can I define a robust distance metric to measure their similarity, and how can I compute it?
I am looking for a method which provides a short distance in case of:
- perhaps local scaling or rotation.
I see two possible solutions:
- transform the shapes into pixel-based matrices (bitmap) and compute a Levenshtein distance (but without enough robustness in the distance, in case of rotation for instance);
- transform the shapes into graphs and try to define a distance between them.